TRANSLATION: The following text is a translation from a German version into English. For the translation I am using the software @chatGPT4o with manual modifications.
In text No. 4, “WHAT IS LIFE? … When Life is ‘More,’ ‘Much More’ …”, there is a central passage that should be recalled here. Following the revelation of the empirically strong acceleration in the development of complexity of life on this planet, it states:
“The curve tells the ‘historical reality’ that ‘classical biological systems’ up to Homo sapiens were able to generate with their ‘previous means.’ However, with the emergence of the ‘Homo’ type, and especially with the life form ‘Homo sapiens,’ entirely new properties come into play. With the sub-population of Homo sapiens, there is a life form that, through its ‘cognitive’ dimension and its novel ‘symbolic communication,’ can generate the foundations for action at an extremely faster and more complex level.”
Following this “overall picture,” much suggests that the emergence of Homo sapiens (that is, us) after approximately 3.5 billion years of evolution, preceded by about 400 million years of molecular development, does not occur randomly. It is hard to overlook that the emergence of Homo sapiens lies almost at the “center of the developmental trajectory.” This fact can—or must?—raise the question of whether a “special responsibility” for Homo sapiens derives from this, concerning the “future of all life” on this planet—or even beyond? This leads to the second quotation from text No. 4:
“How can a ‘responsibility for global life’ be understood by us humans, let alone practically implemented by individual human beings? How should humans, who currently live approximately 60–120 years, think about a development that must be projected millions or even more years into the future?”
Such “responsibility with a view toward the future” would—from the perspective of life as a whole—only make sense if Homo sapiens were indeed the “only currently existing life form” that possesses exactly those characteristics required for “assuming responsibility” in this current phase of life’s development.
PRELIMINARY NOTE
The following text will gradually explain how all these elements are interconnected. At this stage, references to relevant literature will be kept to a minimum, as each section would otherwise require countless citations. Nevertheless, occasional remarks will be made. If the perspective presented in the “What is Life” texts proves fundamentally viable, it would need to be further refined and embedded into current specialized knowledge in a subsequent iteration. This process could involve contributions from various perspectives. For now, the focus is solely on developing a new, complex working hypothesis, grounded in existing knowledge.
THE HOMO SAPIENS EVENT
In modern science fiction novels and films, extraterrestrials are a popular device used to introduce something extraordinary to planet Earth—whether futuristic advancements or adventurous developments from the future appearing on Earth. Of course, these are thought constructs, through which we humans tell ourselves stories, as storytelling has been an essential part of human culture since the very beginning.
Against this backdrop, it is remarkable that the Homo Sapiens Event (HSE) has not yet received a comparable level of empathic attention. Yet, the HSE possesses all the ingredients to surpass even the boldest science fiction novels and films known to us. The developmental timeline on planet Earth alone spans approximately 3.9 billion years.
If we open ourselves to the idea that the biological might be understood as the direct unfolding of properties inherently present in the non-biological—and thus ultimately in energy itself, from which the entire known universe emerged—then we are dealing with a maximal event whose roots are as old as the known universe.
Ultimately—since energy remains more unknown than known to us—the HSE, as a property of energy, could even be older than the known universe itself.
IMAGE 1: Homo Sapiens Event (HSE)
PHILOSOPHICAL APPROACH
In this text, the Homo Sapiens Event (HSE) is discussed or written about because this is the only way in which the author’s brain can exchange thoughts with the brains of readers. This means that—regardless of the content—without some form of communication, there can be no exchange between different brains.
For Homo sapiens, such communication has, from the very beginning, occurred through a symbolic language, embedded in a variety of actions, gestures, facial expressions, vocal tones, and more. Therefore, it makes sense to render this mechanism of symbolic language within a human communication process transparent enough to understand when and what kind of content can be exchanged via symbolic communication.
When attempting to explain this mechanism of symbolic communication, it becomes evident that certain preconditions must be made explicit in advance—without these, the subsequent explanation cannot function.
To encompass the broadest possible perspective on the symbolic communication occurring here, the author of this text adopts the term “philosophical perspective”—in the sense that it is intended to include all known and conceivable perspectives.
Three Isolated Perspectives (Within Philosophy)
In addition to the perspective of biology (along with many other supporting disciplines), which has been used to describe the development of the biological on planet Earth up to the Homo Sapiens Event (HSE), some additional perspectives will now be introduced. These perspectives, while grounded in the biological framework, can provide valuable insights:
Empirical Neuroscience: It is concerned with the description and analysis of observable processes in the human brain.
Phenomenology: A subdiscipline of both philosophy and psychology, it serves to describe and analyze subjective experiences.
Empirical Psychology: It focuses on the description and analysis of observable human behavior.
IMAGE 2: (Hand-drawn sketch, illustrating the developmental process) Philosophical Perspective with the subdisciplines ‘Phenomenology,’ ‘(Empirical) Psychology,’ and ‘Neuroscience’
If these three perspectives are arranged side by side, the phenomenological view includes only our own (subjective) experiences, without a direct connection to the body or the world outside the body. This is the perspective with which every human is born and which accompanies them throughout life as the “normal view of things.”
From the perspective of empirical psychology, observable behavior of humans is the central focus (other life forms can also be studied in this way, though this falls more under biology). However, the phenomena of subjective experience are not accessible within the framework of empirical psychology. While the observable properties of the brain as an empirical object, as well as those of the body, are in principle accessible to empirical psychology, the empirical properties of the brain are generally assigned to (empirical) neuroscience, and those of the body to (empirical) physiology.
From the perspective of (empirical) neuroscience, the observable properties of the brain are accessible, but not the phenomena of subjective experience or observable behavior (nor the observable properties of the body).
It becomes clear that in the chosen systematic approach to scientific perspectives, each discipline has its own distinct observational domain, which is completely separate from the observational domains of the other disciplines! This means that each of these three perspectives can develop views of its object that differ fundamentally from those of the others. Considering that all three perspectives deal with the same real object—concrete instances of Homo sapiens (HS)—one must ask: What status should we assign to these three fundamentally different perspectives, along with their partial representations of Homo sapiens? Must we, in the scientific view, divide one material object into three distinct readings of Homo sapiens (HS): the HS-Phenomenal, the HS-Behavioral, and the HS-Brain?
In scientific practice, researchers are, of course, aware that the contents of the individual observational perspectives interact with one another in some way. Science today knows that subjective experiences (Ph) strongly correlate with certain brain events (N). Similarly, it is known that certain behaviors (Vh) correlate both with subjective experiences (Ph) and with brain events (N). In order to at least observe these interactions between different domains (Ph-Vh, Ph-N, N-Vh), interdisciplinary collaborations have long been established, such as Neurophenomenology (N-Ph) and Neuropsychology (N-Vh). The relationship between psychology and phenomenology is less clear. Early psychology was heavily introspective and thus hardly distinguishable from pure phenomenology, while empirical psychology still struggles with theoretical clarity today. The term “phenomenological psychology (Ph-Vh)” appears occasionally, though without a clearly defined subject area.
While there are some interdisciplinary collaborations, a fully integrated perspective is still nowhere to be found.
The following section will attempt to present a sketch of the overall system, highlighting important subdomains and illustrating the key interactions between these areas.
Sketch of the Overall System
The following “sketch of the overall system” establishes a conceptual connection between the domains of subjective experiences (Ph), brain events (N), bodily events (BDY), the environment of the body (W), and the observable behavior (Vh) of the body in the world.
IMAGE 3: (Hand-drawn sketch, illustrating the developmental process) Depicting the following elements: (1) Subjective experiences (Ph), (2) Brain events (N), (3) Bodily events (BDY), (4) Observable behavior (Vh) of the body in the world, (5) The environment of the body (W). In the lower-left corner of the image, a concrete instance of Homo sapiens (HS) is indicated, observing the world (W) along with the various bodies (BDY) of other Homo sapiens individuals. This HS can document its observations in the form of a text, using language (L).
IMAGE 3b: Hand-drawn sketch, illustrating the developmental process – The core idea for the concept of ‘Contextual Consciousness (CCONSC)’
As can be seen, the different domains are numbered from (1) to (5), with number (1) assigned to the domain of subjective experiences (Ph). This is motivated by the fact that, due to the structure of the human body, we perceive ourselves and all other events in the form of such subjective experiences as phenomena. Where these phenomena originate—whether from the brain, the body, or the surrounding world—is not directly apparent from the phenomena themselves. They are our phenomena.
While philosophers like Kant—and all his contemporaries—were still limited to considering the possible world and themselves solely from the perspective of their own phenomena, empirical sciences since around 1900 have gradually uncovered the processes behind the phenomena, localized in the brain, allowing them to be examined more concretely. Over time, increasingly precise correlations in time between brain events (N) and subjective experiences (Ph) were discovered.
One significant breakthrough was the ability to establish a temporal relationship between subjective experiences (Ph) and brain events (N). This suggested that while our subjective experiences cannot be measured directly as experiences, their temporal relationships with brain events allow for the localization of specific areas in the brain whose functioning appears to be a prerequisite for our subjective experience. This also provided a first empirical concretization of the common concept of consciousness, which can be formulated as a working hypothesis:
What we refer to as consciousness (CONSC, 1) corresponds to subjective experiences (Ph) that are enabled by brain events (N) occurring in specific areas of the brain. How exactly this can be understood will be explained further below.
The brain events (N) localized in the brain (BRAIN, 2) form a complex event space that has been increasingly researched since around 1900. It is generally clear that this space is highly dynamic, manifesting in the fact that all events interact with each other in multiple ways. The brain is structurally distinct from the rest of the body, but at the same time, it maintains exchange processes with thebody (BDY, 3)and the brain’s event space (BRAIN, 2). This exchange occurs via interfaces that can (i) translate body events into brain events and (ii) translate brain events into bodily events.
Examples of (i) include our sensory organs (eyes, ears, smell), which transform light, sound, or airborne molecules into brain events. Examples of (ii) include brain events that, for instance, activate muscles, leading to movements, or regulate glandular secretions, which influence bodily processes in various ways.
The body space (BODY, 4)is approximately 450 times larger than the space of brain events. It consists of multiple regions known as organs, which have complex internal structures and interact in diverse ways. Bodily events also maintain a complex exchange with brain events.
With the surrounding world (W,5), there are two types of exchange relationships. First, (i) interfaces where bodily events appear as excretions in the event space of the world (W), and second, (ii) bodily events that are directly controlled by brain events (e.g., in the case of movements). Together, these two forms of events constitute the OUTPUT (4a) of the body into the surrounding world (W). Conversely, there is also an INPUT (4b) from the world into the body’s event space. Here, we can distinguish between (i) events of the world that directly enter the body (e.g., nutrition intake) and (ii) events of the world that, through sensory interfaces of the body, are translated into brain events (e.g., seeing, hearing).
Given this setup, an important question arises:
How does the brain distinguish among the vast number of brain events (N)—whether an event is (i) an N originating from within the brain itself, (ii) an N originating from bodily events (BDY), or (iii) an N originating—via the body—from the external world (W)?
In other words: How can the brain recognize whether a given brain event (N) is (i) N from N, (ii) N from BDY, or (iii) N from W?
This question will be addressed further with a proposed working hypothesis.
Concept of ‘Consciousness’; Basic Assumptions
In the preceding section, an initial working hypothesis was proposed to characterize the concept of consciousness: what we refer to as consciousness (CONSC, 1) pertains to subjective experiences (Ph) that are enabled by brain events (N) occurring in specific regions of the brain.
This working hypothesis will now be refined by introducing additional assumptions. While all of these assumptions are based on scientific and philosophical knowledge, which are supported by various forms of justification, many details remain unresolved, and a fully integrated theory is still lacking. The following additional assumptions apply:
Normally, all phenomena that we can explicitly experience subjectively are classified as part of explicit consciousness (ECONSC ⊆ CONSC). We then say that we are aware of something.
However, there is also a consciousness of something that is not directly correlated with any explicit phenomenon. These are situations in which we assume relationships between phenomena, even though these relationships themselves are not experienced as phenomena. Examples include:
Spoken sounds that refer to phenomena,
Comparative size relations between phenomena,
Partial properties of a phenomenon,
The relationship between current and remembered phenomena,
The relationship between perceived and remembered phenomena. This form of consciousness that exists in the context of phenomena but is not itself a phenomenon will be referred to here as contextual consciousness (CCONSC ⊆ CONSC). Here, too, we can say that we are aware of something, but in a somewhat different manner.
This distinction between explicit consciousness (ECONSC) and contextual consciousness (CCONSC) suggests that the ability to be aware of something is broader than what explicit consciousness alone implies. This leads to the working hypothesis that what we intuitively call consciousness (CONSC) is the result of the way our brain operates.
Basic Assumptions on the Relationship Between Brain Events and Consciousness
Given today’s neuroscientific findings, the brain appears as an exceedingly complex system. For the considerations in this text, the following highly simplified working hypotheses are formulated:
Empirical brain events are primarily generated and processed by specialized cells called neurons (N). A neuron can register events from many other neurons and generate exactly one event, which can then be transmitted to many other neurons. This output event can also be fed back as an input event to the generating neuron (direct feedback loops). Time and intensity also play a role in the generation and transmission of events.
The arrangement of neurons is both serial (an event can be transmitted from one neuron to the next, and so on, with modifications occurring along the way) and hierarchical (layers exist in which events from lower layers can be represented in a compressed or abstracted form in higher layers).
From this, the basic assumptions about the relationship between brain events and conscious events are as follows:
Some brain events become explicitly conscious phenomena (ECONSC).
Contextual consciousness (CCONSC) occurs when a network of neurons represents a relationship between different units. The relationship itself is then consciously known, but since a relationship is not an object (not an explicit phenomenon), we can know these relationships, but they do not appear explicitly as phenomena (e.g., the explicit phenomenon of a “red car” in text and the perceptual object of a “red car”—we can know the relationship between them, but it is not explicitly given).
The concept of consciousness (CONSC)thus consists at least of explicit phenomenal consciousness (ECONSC) and contextual consciousness (CCONSC). A more detailed analysis of both the phenomenal space (Ph) and the working processes of the brain (N) as the domain of all brain events will allow for further differentiation of these working hypotheses.
After these preliminary considerations regarding the different event spaces in which a Homo sapiens (HS) can participate through different access modalities (W – BDY – N(CONSC)), the following section will provide an initial sketch of the role of language (L) (with further elaborations to follow).
Descriptive Texts
As previously indicated, within each of the listed observational perspectives—observable behavior (Vh), subjective experiences (Ph), and brain events (N) (see IMAGE 2)—texts are created through which actors exchange their individual views. Naturally, these texts must be formulated in a language that all participants can understand and actively use.
Unlike everyday language, modern scientific discourse imposes minimal requirements on these texts. Some of these requirements can be described as follows:
For all linguistic expressions that refer to observable events within the domain of a given perspective, it must be clear how their empirical reference to a real objectcan be verified intersubjectively. In the verification process, it must be possible to determine at least one of the following: (i) It applies (is true), (ii) It does not apply (is false), (iii) A decision is not possible (undetermined)
It must also be clear: (i) Which linguistic expressions are not empirical but abstract, (ii) How these abstract expressions relate to other abstract expressions or empirical expressions, (iii) To what extent expressions that are themselves not empirical can still be evaluated in terms of truth or falsehood through their relationships to other expressions
How these requirements are practically implemented remains, in principle, open—as long as they function effectively among all participating actors.
While these requirements can, in principle, be fulfilled within the perspective of empirical psychology and neuroscience, a phenomenological perspective cannot fully meet at least the first requirement, since the subjective phenomena of an individual actor cannot be observed by other actors. This is only possible—and even then, only partially—through indirect means.
For example, if there is a subjective phenomenon (such as an optical stimulus, a smell, or a sound) that correlates with something another actor can also perceive, then one could say: “I see a red light,” and the other actor can assume that the speaker is seeing something similar to what they themselves are seeing.
However, if someone says, “I have a toothache,” the situation becomes more difficult—because the other person may never have experienced toothache before and therefore does not fully understand what the speaker means. With the vast range of bodily sensations, emotions, dreams, and other subjective states, it becomes increasingly challenging to synchronize perceptual content.
The Asymmetry Between Empirical and Non-Empirical Perspectives
This indicates a certain asymmetry between empirical and non-empirical perspectives. Using the example of empirical psychology and neuroscience, we can demonstrate that we can engage empirically with the reality surrounding us—yet, as actors, we remain irreversibly anchored in a phenomenological (subjective) perspective.
The key question arises: How can we realize a transition from the inherently built-in phenomenological perspective to an empirical perspective?
Where is the missing link? What constitutes the possible connection that we cannot directly perceive?
Referring to IMAGE 3, this question can be translated into the following format: How can the brain recognize whether a given brain event (N) originates from (i) another brain event (N from N), (ii) a bodily event (N from BDY), (iii) an external world event (N from W)?
This question will be explored further in the following sections.
Outlook
The following text will provide a more detailed explanation of the functioning of symbolic language, particularly in close cooperation with thinking. It will also illustrate that individual intelligence unfolds its true power only in the context of collective human communication and cooperation.
A localization of philosophy within the overall context:
Author: Gerd Doeben-Henisch
Changelog: Jan 21, 2025 – Jan 28, 20225
AUTHOR: I have changed the title “WHAT IS LIFE? … PHILOSOPHY OF THE WORLD” to “WHAT IS LIFE? … PHILOSOPHY OF LIFE.” Reason: It will become evident in the course of the investigation that the ‘life’ we find on planet Earth, and which at first glance appears to be a ‘part of the world and the universe,’ may not actually be only a ‘part’ … Therefore a ‘philosophy’ aiming to describe the ‘world’ would do better to focus directly on ‘life,’ which is the true ‘riddle of the universe.’
Email: info@uffmm.org
TRANSLATION: The following text is a translation from a German version into English. For the translation I am using the software @chatGPT4o with manual modifications.
In the two preceding texts, the ‘framework’ was outlined within which the subsequent texts on the topic “What is life? What roles do we have? Is there a future?” will unfold.
The exploration of the various aspects of this broad theme begins with reflections on the role of ‘philosophy’ in this context.
ANCHORING ‘PHILOSOPHY’ IN LIFE
The assumption here is that the phenomenon of ‘philosophy’ is connected to ‘actors’ who live on this ‘planet,’ who are part of the great phenomenon of ‘life’ on this planet. According to a widely held understanding, philosophy is found primarily in the life form broadly referred to as ‘Homo’ (approximately 6 million years before our present time) and, within the Homo lineage, later manifested as ‘Homo sapiens’ (approximately 300,000 years before our present time). While other manifestations of the Homo life form existed alongside Homo sapiens, it is only Homo sapiens who have survived to this day—so essentially, ‘us.’
As is well known, in the year 2025, there are many ‘continents’ on the planet Earth where ‘humans’ live almost everywhere. The ways people live on different continents often differ significantly in outward appearances, influenced by external conditions (climate, vegetation, geology, worldviews, etc.). The ‘genetic basis’ is either almost ‘identical’ or differs only in ‘details.’ The connection between these details and observable ‘behavior’ remains largely unclear. While differences in hair color, skin color, body shape, etc., may exist, these differences are found on every continent, in every population group, and are irrelevant to behavior.
Due to numerous ‘necessities of life’ (food, drink, shelter, etc.), humans never act entirely ‘planlessly.’ From the earliest ‘evidence of human life,’ we can observe that humans ‘shape,’ ‘organize,’ and develop their behavior and environment into increasingly complex ‘systems of rules’ that guide their actions. The entirety of these forms, organizations, and systems of rules is referred to here as ‘culture.’
Within this ‘human culture,’ one feature stands out in particular: communication through ‘spoken language.’ While humans can ‘communicate’ in many ways without explicit speech, for all detailed, complex matters—especially for the purpose of ‘coordinating shared actions’—spoken language proves to be indispensable and immensely powerful! It is noteworthy that there was not just ‘one language,’ but almost as many languages as there were ‘human communities.’ The ‘harmonization of languages’ or the ‘fusion’ of different languages has—if at all—only occurred over many generations. Even today (2025), we see national communities with hundreds of languages coexisting, and it seems self-evident that at multinational events, each nation participates with at least one ‘own’ language.
As a culture becomes enriched with more and more ‘elements,’ the demands on the ‘members of this culture’ to ‘familiarize themselves’ with all these elements and their ‘interplay’ increase. Today, we would say that individual members must ‘learn’ their own culture.
In the last approximately 2,000 to 3,000 years of human culture, a ‘pattern of education’ has emerged that is broadly referred to as ‘philosophy,’ or specific behaviors are labeled as ‘philosophical.’ The diversity of this phenomenon ‘philosophy’ is so vast and pronounced that it seems nearly impossible to trace this diversity back to just a few fundamental elements. Those who wish to explore this historical diversity further can do so by consulting relevant handbooks and encyclopedias, where they may—possibly—’lose themselves’ in this diversity.
Here, a different approach is taken.
This ‘diversity of the philosophical’ ultimately always leads back to specific individuals—usually referred to as ‘philosophers’ in an educational sense—who were actors in a particular, culturally shaped ‘everyday life.’ As ‘parts’ of such a ‘life process,’ they formed certain ‘opinions,’ ‘views of life.’ They used ‘specific linguistic expressions,’ interpreted, classified, and organized the experienced life through their linguistic expressions, and abstracted from individual phenomena. They ‘perceived relationships’ between phenomena, summarized many relationships into ‘networks of relationships’ (often also called ‘models’ or ‘theories’), and studied the ‘functioning of language’ (rather late), the ‘functioning of thought,’ and much more.
‘In the end,’ all these linguistic and intellectual activities led to various philosophers developing different ‘views of everyday life and the world.’ Some ‘later’ philosophers considered such ‘philosophical views’ of ‘earlier’ philosophers for their own ‘production of views,’ but to this day, one cannot claim that there is ‘one grand philosophical view of the world.’ Instead, we find a vast number of fragments and drafts, specific perspectives, some contradictory, with little overlap.
It is striking that there is still no (!) philosophical view of the world that explains philosophy ‘itself,’ its own ’emergence,’ its own ‘functioning.’ There are many reasons why this is so. Even for a philosopher willing to scrutinize all the ‘assumptions of their thinking,’ obstacles exist. One such obstacle is the language within which they philosophize. Philosophizing in a particular language while simultaneously reflecting on the ‘assumptions of that language’ is maximally difficult, and no one has truly succeeded in doing so. To a certain extent, the same applies to their own body, within which the philosopher finds themselves. The complex inner workings of one’s own body are—roughly estimated—accessible to no more than about 1% of any person. Another significant obstacle is the entirety of the culture in a society. Over a lifetime, this culture leaves deep marks on a philosopher’s ‘feelings, thinking, and behavior,’ which can only be questioned and changed to a very limited extent. Finally, not to be overlooked, is the phenomenon of ‘time,’ manifesting as ‘changes’ in the experienced everyday life and in the evolving ‘inner life’ of a philosopher: What was just ‘present’ suddenly becomes ‘past’; what was just ‘blue’ suddenly turns ‘black.’ Everything can change. And what does a philosopher then do with their ‘memories,’ shaped by ‘yesterday’?
This reflection on some of the ‘conditions of a philosopher’s cognition’ may seem ‘depressing,’ extinguishing any ‘hope for useful insight’ at the outset. However, everyday life teaches us that we humans are still here, that even in the ‘scientific field of philosophy,’ there seems to be a kind of ‘development of views (models, theories)’ which give the impression of ‘functioning,’ enabling us to make ‘predictions’ to a limited extent that can be ‘verified as accurate.’
For the further determination of what characterizes the phenomenon of ‘philosophy,’ the focus here will be less on the ‘congealed form’ of philosophy as an educational construct but more on the ‘everyday processes’ where specific people engage in concrete activities that form the ‘framework’ or ‘medium’ within which ‘philosophy for all’ takes place.
Ultimately, ‘philosophy’ is a ‘holistic phenomenon’ that becomes visible in the interplay of many people in an everyday context, is experienced, and can only take shape in this process form. ‘Truth,’ as the ‘core’ of any reality-related thinking, is always only found as a ‘part’ of a process in which the interconnected dynamics are essential to the ‘truth of a matter.’ Therefore, truth is never ‘self-evident,’ never ‘simple,’ never ‘free.’ Truth is a ‘precious substance’ that requires every effort to ‘attain’ and whose state is ‘fleeting,’ as the ‘world’ within which truth can be ‘worked out’ continuously changes as a world. A key factor in this constant change is life itself: the ‘existence of life’ is only possible within an ‘ongoing process’ through which ‘energy’ can illuminate ’emergent images’—not created for ‘resting’ but for ‘becoming,’ whose ultimate goal still appears in many ways ‘open.’ Life can indeed—partially—destroy itself or—partially—empower itself. Somewhere in the midst of all this, we find ourselves. The current year ‘2025’ is actually of little significance for this.
TRANSLATION: The following text is a translation from a German version into English. For the translation I am using the software @chatGPT4o with manual modifications.
Ultimately, the path to today’s text leads from the first entries in the Philosophy Blog of the author (initially in 2007, then from 2009 onward) through all subsequent posts to the present day. The guiding theme, “Philosophy Now: In Search of a New Image of Humanity”, aptly reflects what has transpired. The posts on Philosophy blog document a search for those “images of the world and ourselves” that best illuminate the structures characterizing our existence over time on this planet, in this universe. For a long time, it was unclear whether an answer could be found. The many disparate images of humanity and the world seemed too fragmented: in art, in religious worldviews, in economics, in the natural sciences, in the humanities, and even in philosophy itself, which considers itself the “most fundamental perspective” from which to view and analyze the world.
It should not go unmentioned that among the many other blogs the author has filled with texts over the years, at least two more are worth noting:
First, there is the blog“Integrated Engineering and the Human Factor”, which began in 2003 with the publication of the author’s lectures. Over time, it became increasingly focused on specific topics closely aligned with computer science, engineering, and the philosophy of science—especially the relationship between humans and machines, including artificial intelligence.
Second, there is the blog “Citizen Science 2.0”. Launched in 2021, it explored the transition from “traditional citizen science” to “Citizen Science 2.0” in connection with an expanded concept of “empirical theory” into a “sustainable empirical theory”. The development of this theoretical concept ran parallel to the creation of an innovative software tool called oksimo, which allows users to describe complete sustainable theories in plain text (in any language) and simulate these theories at the push of a button. This new “view of things” emerged from applying the “Integrated Engineering and the Human Factor” theory to municipal processes in which citizens seek to understand and plan their world collaboratively.
While these three blogs with their different themes always seemed to be somehow interconnected, it was only in the past two years—since spring 2023—that these topics increasingly converged. This convergence revealed a single, overarching perspective in which all themes found a new “conceptual home”, where nothing seems insignificant, and a process is emerging with a force and richness that surpasses anything previously known in human history.
This expansive new perspective will be described in more detail below.
WHAT IS LIFE? First Steps.
There is a well-known saying, “A picture is worth a thousand words.” However, as the following example will show, when dealing with a highly complex subject, a single image is not enough. Still, it may provide the reader with an initial “framework” that can serve as a reference point, allowing the unimaginably complex concept of “life” to take shape in its first outlines. Have a look to the image at the beginning of this text.
The Complete Picture Consists of Four ‘Elements,’ Each Representing a ‘Logo’ and a Corresponding ‘Theme’:
“Life@Work. It’s All Inclusive” This primarily represents biological life on planet Earth. However, as the discussion progresses will proceed, it will become clear that biological life cannot be separated from the other areas. The deeper we delve into the phenomenon of life, the more evident it becomes that everything forms a “dynamic unity” that is ultimately breathtaking.
“SW@WORK. Expand Our Thinking” This intentionally does not refer to AI but rather to Software (SW), as all AI is, at its core, an “algorithm”—a piece of software capable of controlling “standardized machines” (computers). The fact that the “behavior of such standardized machines” can appear very human or intelligent to users (such as us humans) does not change the reality that this externally observable behavior is internally based on very simple computational operations. These operations lack almost everything that characterizes biological systems. Nevertheless, living beings can use such standardized machines in various ways to “extend their own capabilities.” It may even be argued that known life forms—particularly the species Homo sapiens—will likely be unable to face emerging futures without leveraging this technology. Conversely, these standardized machines alone will not survive any future, not even remotely.
“EARTH@WORK. Cradle of Humankind” This represents planet Earth and everything we know about it. The existence of this planet was, in fact, a prerequisite for the development of biological life as we know it. Only in recent years have we begun to understand how known “biological life” (Nature 2) could “emerge” from “non-biological life” (Nature 1). On deeper analysis, one can recognize not only the commonality in the material used but also the “novel extensions” that distinguish the biological from the non-biological. Rather than turning this “novelty” into a dichotomy—as traditional human thought has often done (e.g., “matter” versus “mind”)—it can be understood as a “manifestation” of something more “fundamental,” an “emergence” of new properties that point to characteristics inherent in the “foundation of everything”—namely, energy. These characteristics only become apparent with the formation of increasingly complex structures. This new interpretation is inspired by insights from modern physics, particularly quantum physics in conjunction with astrophysics. It suggests a broader interpretation of Einstein’s classical formula e=mc² than is typically considered (summarized as Plus(e=mc²)).
“PHILOSOPHY@WORK. Everything is Object” This represents the perspective through which the author of this text attempts to bring the complexity of the experienced world (external and internal) “into language” using the expressions of a particular language—here, the English language. The seemingly simple phrase “to bring something into language” belies the inherent complexity of this task. It will therefore be necessary to more precisely describe the act of “bringing something into language” to make transparent why the following content is communicated in the way that it is.
LITERATURE NOTE
(Last change: Jan 28, 2025)
Up to the above text (including its continuations), I have read many hundreds of articles and books, and of course, I continue reading all the time. 🙂
In doing so, I came across Fritjof Capra’s book again, The Web of Life: A New Scientific Understanding of Living Systems, completed in 1996 and published in 1997 by Anchor Books, a division of Random House, New York. In 2025, this book is (29)28 years old. And when you look at today’s worldview, this book still seems “revolutionary.” While “light texts” today spread like wildfire through social media, texts that require thoughtful engagement encounter an “invisible wall” that prevents these ideas from penetrating us.
This is not new in human history; on the contrary, it seems as if we, as humans, have a “built-in inertia mechanism” for the new, at least when “mental effort” is demanded of us. This has always been the great opportunity for “populists,” and it doesn’t seem to be any different today…
The following Dialogue is an English translation from German (done with chatGPT4) and has its origin in the context of the interaction between the human species and the planet earth. During this dialogue starting with physical things the dialogue turned more and more into a true philosophical dialogue recognizing biological life as a ‘cultural system’. This was from the author not intended! It happend driven by … the ‘internal logic’ of life?
FINAL CONCLUSION
chatGPT4 commented at the end of the whole dialogue as follows: “In our dialogue, we have applied philosophical methods to gain deeper insights into the nature of human existence and interaction. This kind of reflection is a cornerstone of philosophical inquiry and helps to illuminate complex questions of human life and coexistence.”
BEGIN OF THE DIALOGUE
(Note: the BOLD TEXT indicates the contributions of the author)
Hello Chat, we had a dialogue on the ‘Earth System’ on August 18, 24 and a dialogue on ‘Collective Human Intelligence’ on August 21. Can you remember?
Hello! I don’t have access to previous conversations or information about what we discussed. Each session with me starts without knowledge of previous interactions. But I am happy to continue helping with these topics or other questions you have. How can I assist you today?
OK, good to know. Then we’ll start from scratch 🙂
Perfect! How can I help you today?
In my theory [1], I assume that the Earth system as a planet is characterized by the presence of ‘biological life’ here. For me, ‘biological life’ is synonymous with ‘life’. Do you agree?
Your approach to equate the “Earth system” with the presence of biological life is an interesting standpoint and common in many scientific disciplines. [2] Biological life, as we know it, is characterized by certain features such as the ability to reproduce, metabolic processes, and adaptation to environmental conditions.
It makes sense to consider biological life as the central aspect of life on Earth in a discussion about the Earth system. This definition excludes other forms of hypothetical or non-biological life (such as possibly silicon-based life or artificial intelligence that develops its own consciousness), which could also be considered “life” in other contexts. However, for most scientific and philosophical considerations of the Earth system, the restriction to biological life is common and appropriate.
Therefore, I agree with your view as long as we are within the framework of known biological life forms. Would you like to delve deeper into this aspect or do you have specific questions about it?
[2] This is a small mis-understanding of Chat, because I assume only, that there is ‘life’ on the planet earth. Strictly speaking can the planet earth ‘exist’ without life, but, clearly, as soon as ‘live’ appeared on the planet this changed the planet completely; it is ‘another planet’!
I would like to initially focus on the concept of ‘life’ as we encounter it on planet Earth. AI – as far as we know it today – has nothing to do with life for me. Historically, the existing forms of AI have been invented and created by life. Humans, as a life form within life, use AI as a tool. Do you agree?
Yes, your view of artificial intelligence (AI) as a tool created and used by humans is in line with the common perception in science and technology. AI is indeed an invention of human intelligence, developed to perform specific tasks that require mental processes such as learning, problem-solving, and decision-making.
AI is based on algorithms and computer-supported models and is often considered an advanced form of automation. Although AI systems are capable of performing tasks that typically require human intelligence [1], they lack essential characteristics of biological life, such as self-reproduction, metabolic processes, and natural evolution through genetic variation and natural selection. AI systems cannot reproduce or evolve outside of the parameters set by humans.
This distinction is important to understand the differences between biological life and technological products like AI. Thus, AI remains a tool used by humans for specific purposes and not an independent living being. Are you interested in further details or another aspect of this topic?
[1] Because until today the concept ‘human intelligence’ is still very badly characterized, has the expression ‘human intelligence’ no clear meaning.
I would like to delve deeper into the topic of AI and humans (or life in general) in another dialogue. Today and here, I want to continue exploring the interaction between humans and the Earth system. Are you on board?
Of course, that sounds like an exciting topic! The interaction between humans and the Earth system is complex and can be viewed from many aspects such as environmental science, ecology, geology, and even from socio-political perspectives. Would you like to explore specific aspects of these interactions, such as the impact of humans on the climate, the use of natural resources, or something else? Let me know what focus you would like to set!
Yes, the interactions between humans and the Earth system are diverse. It is important to note that humans, as part of life, interact not only with the Earth system but also with life itself. Furthermore, since humans are part of life, it follows that humans also ‘interact with themselves,’ i.e., humans with humans. What do you think?
Exactly, your observation is very apt and captures the complexity of human interactions at various levels within the Earth system. Humans are not only physically and biologically part of the Earth, but also active designers and influencers of their environment. These interactions occur on several levels:
Human and Nature: Humans influence the natural environment through agriculture, urbanization, industry, and the consumption of natural resources. These actions have direct impacts on the climate, biodiversity, and the availability of resources.
Human and Life: As part of biological life, humans also interact with other living beings, both cooperatively and conflictually. These relationships can be symbiotic, as in the domestication of animals and plants, or antagonistic, such as the destruction of habitats or the overhunting of species.
Human and Human: On a social and cultural level, humans shape societies through their interactions, which in turn develop values and norms that influence behavior towards the environment and other life forms. These social structures and the resulting decisions (such as laws and regulations) play a crucial role in how humans influence the Earth system.
Reflecting on these various interaction levels is crucial to understanding the full impact of human activities on the Earth system and developing sustainable solutions. To what extent do you think these interactions could be improved or modified to promote more sustainable coexistence on our planet?
Ah, even this brief analysis shows how difficult it is to formulate a perspective that does justice to this multitude of dimensions and possible interactions. I see the following starting point: (1) We could start directly with humans. (2) Humans are ‘individual’, ‘singular’, ‘concrete’, (3) but at the same time they are always ‘part of a community’ (a ‘population’), without which they could not exist as individuals. At least not if one demands for ‘human life’ as a ‘part of all life’ that it can ‘continue’ ‘beyond the life of an individual human’. This requires ‘offspring’, and offspring only functions over at least two generations. What do you think?
Your approach to begin the analysis of human interactions with the Earth system at the level of individuals and their communities is both pragmatic and profound. It recognizes the duality of human existence – as independent individuals and as part of a larger community. This perspective helps understand the multi-layered effects of human actions and develop possible solutions.
Here are some key aspects highlighted by your analysis:
Individual Responsibility: Every individual contributes through their actions to shaping the Earth system. This ranges from everyday decisions such as consumption habits and mobility to professional and political activities. Individual education and awareness are therefore key aspects to promote sustainable behaviors.
Social Structures and Communities: Humans exist within social structures that both enable and limit their action options. Communities form networks that distribute resources, share information, and coordinate collective actions. These networks are crucial for the implementation of sustainable practices and for collective resilience to environmental changes.
Generational Perspectives: As you rightly note, the continuation of human life requires thinking in generations. Education, cultural heritage, and traditions are mechanisms that transfer values and knowledge from one generation to the next and are crucial for the long-term stability and adaptability of human communities.
Sustainable Development: This is based on balancing the satisfaction of current human needs with the preservation of the environment for future generations. This requires innovative approaches in technology, economics, and politics that address both local and global challenges.
Your approach suggests that an integrative view, considering individual actions and collective structures, is necessary to promote sustainable solutions. This can also provide a platform for further discussions on specific measures that can be implemented at various levels of society. How do you see the implementation of these ideas in concrete policies or practices?
This is now very interesting: Your differentiation of the varied interactions in which an individual finds themselves indirectly reveals something that cannot be ‘directly’ discerned, but ‘indirectly’, through … I’m missing the right word … let’s say tentatively through ‘knowledge’ in the broadest sense. What do you think?
Your thought that certain aspects of human existence and interaction are indirectly discerned through knowledge is very profound and points to the role that knowledge and understanding play in our perception of ourselves and our environment. Knowledge – in all its forms, from scientific understanding to cultural and personal experiences – enables us to see connections that are not immediately obvious. This “indirect recognition” can be facilitated through various mechanisms:
Abstraction: Through abstraction, we can recognize general principles or patterns that are not immediately visible in specific situations. Abstraction helps us to move from the particular details of a single event or object to more general conclusions.
Model Building: Scientific and theoretical models allow us to understand complex systems and their possible behaviors by using simplifications and assumptions to represent reality. Models help us anticipate the consequences of actions and plan accordingly.
Narrative and Metaphor: Stories and metaphors enable us to communicate complicated or abstract ideas in a way that is emotionally resonant and intuitively understandable. They provide frameworks to recognize “invisible” connections between actions and their long-term impacts on people and the environment.
Collective Intelligence: The knowledge of a community or society is more than the sum of the knowledge of its individuals. By sharing ideas and experiences in a social context, people can reach a deeper, shared understanding that would not be achievable individually.
Your observation shows how important it is to promote knowledge and learning in all areas – from education to policy making – to gain deeper insight into the complex interactions within the Earth system and between people. To what extent do you see opportunities to expand or better utilize this knowledge to more effectively address the challenges we face?
OK, let’s look at a seemingly ‘simple example’. Let’s take persons who eat something because they are hungry. Their food can come directly from the rest of life (plants, animals, etc.), or from something they have somehow ‘manufactured’ from the material of the earth. However, when it comes to feeding thousands of people every day, simple measures to provide food are no longer sufficient. It then requires people, machines, agricultural methods, and much more to make this still possible. These elaborate processes assume that there are appropriate ‘experiences’ (with ‘knowledge’) that ‘tell’ the acting people what to do. However, these experiences with the corresponding knowledge do not come from ‘nothing’ but must be painstakingly ‘acquired’, ‘learned’. This requires ‘time to learn’ and – usually – other people who ‘already have experiences’ that they can ‘pass on’. From this, I deduce that the ‘biological human system’, a ‘living something’, must have complex processes inside it that make such ‘experiences’, such ‘knowledge’ possible. In other words: Only with such experiences, with such knowledge, and the ability to build such, does a biological system become a ‘human’, a ‘Homo sapiens’. What do you think?
Your example excellently highlights how the everyday need for food encompasses profound social, technological, and cultural systems that have been developed over generations. It shows that what appears at the individual level as a simple action is actually based on a complex web of knowledge and social structures.
Biological and Cognitive Foundations of Humans
The ability of humans to acquire, store, and pass on knowledge is indeed one of the core functions that define us as Homo sapiens. This ‘experiential knowledge’ is important not only on a cognitive level but also on a cultural level, as it is passed on through language, education, and social interaction.
Cultural Evolution and Human Societies
What you describe is a classic example of cultural evolution, where knowledge and technologies are developed and inherited not genetically, but through learning processes and social transmission. This enables human societies to quickly adapt to new environmental conditions without waiting for slow genetic evolution.
Knowledge as the Basis for Complex Societies
The example of food provision illustrates how important specialized knowledge and technologies are to efficiently meet the basic needs of a large number of people. Modern agricultural and production techniques are the result of accumulated knowledge developed over centuries, if not millennia. This knowledge is passed on through education systems, professional literature, and practice and is crucial for the maintenance and further development of our livelihoods.
Human Learning Ability and Adaptability
Your emphasis on ‘time to learn’ and the role of teachers and mentors underlines how crucial education and both formal and informal learning are for human development. This ability to process and pass on complex information allows us to survive and thrive not only as individuals but as a global community.
Conclusion
Overall, your approach shows how central knowledge and learning are to understanding what it means to be human. It’s not just about gathering information, but also about applying and sharing this information to master complex and dynamic challenges. This makes the biological system of humans something special: a being capable of constantly developing and adapting its understanding and technologies.
How do you see the role of modern technology and digital information in this process of knowledge acquisition and dissemination? Do you see it as an extension of our cognitive and social abilities?
As our dialogue progresses, it becomes more difficult for me to find a ‘simple formula’ to describe the interaction of humans with the Earth system and life. It starts with the fact that I need a ‘language’ for such a description, and every language does not only work with ‘dead letters’ or ‘mere sounds’, but assumes that all other people I want to talk to associate a ‘meaning’ with the ‘sounds’ or ‘letters’, which can only be present ‘inside each individual’. While I speak, however, I cannot ‘invent’ my own language; I must assume that I ‘possess’ this language without being able to ‘describe’ the language itself. Isn’t this somehow ‘bizarre’?
It is indeed a fascinating and at the same time complex consideration that you raise here. The nature of language and communication among humans reflects profound aspects of our existence and our interactions with the world.
Foundations of Language
Language is not just a system of sounds and characters but a complex web of meanings, conventions, and cultural influences. Every word and every sentence we use is embedded in a context of experiences and knowledge that we share with others who speak the same language. This makes language a powerful yet subtle tool.
Prerequisites for Communication
Your observation that in communication we must assume that others find the same meaning in words as we do is crucial. This shows how much we, as social beings, depend on each other. Without a common understanding and without assuming that our language works, effective communication would be impossible.
The Impossibility of Fully Describing Language
The fact that we use language without being able to fully explain it at all times reflects a common human experience. Many of the systems and structures that determine our lives, such as laws, social norms, or languages, are so complex and deeply rooted that no individual could fully grasp or create them. They are the product of collective human activity over generations.
The Bizarre Nature of Our Existence
What you describe as ‘bizarre’ can also be seen as a hint at the deep interwovenness and interdependence in human societies. Our ability to use and understand complex abstract systems like language, without fully controlling or creating them, is a sign of our cognitive flexibility and social nature. It shows how we can achieve and understand more together than an individual alone could.
Reflection
These considerations lead us to a deep appreciation of how human cultures and social structures function. They invite us to recognize both the limits of our individual abilities and the incredible potential of our communal endeavors.
Your thoughts open many further questions about the nature of knowledge, communication, and human cooperation. How do you see the role of modern technologies in this context, especially in terms of how they might change our communication patterns?
OK, now that we have somehow reached this ‘profound position’, a question arises that is not really important but may be of interest in a cultural context: Would you associate this kind of ‘thinking about us humans’ with the concept of ‘philosophy’? Could we describe the way we have practiced in this dialogue as ‘philosophical thinking’?
Yes, the way we have thought and reflected in this dialogue can certainly be described as philosophical thinking. Philosophy fundamentally deals with the pursuit of knowledge and understanding about the basic aspects of our existence, our experiences, and the world around us. It often involves questions about meaning, truth, values, the mind, and language.
Characteristics of Philosophical Thinking:
Critical Analysis: Philosophical thinking often questions everyday assumptions and searches for deeper meanings and connections, similar to what we have done in our conversation.
Logical Argumentation: It is based on rational considerations and uses logical arguments to examine and justify different viewpoints.
Conceptual Exploration: It explores fundamental concepts such as existence, knowledge, truth, law, ethics, and beauty.
Interdisciplinary Connections: Philosophy often overlaps with other disciplines such as science, art, and politics to gain a broader understanding of the topics discussed.
Philosophy in Everyday Life:
Philosophical thinking is not limited to academic circles but plays a vital role in everyday life. It helps us reflect on our beliefs, make decisions, and understand the world and our role in it.
Cultural Significance:
In a cultural context, philosophy contributes to shaping the values and self-understanding of a society. It influences how cultures think about important issues such as morality, justice, and human well-being.
In our dialogue, we have applied philosophical methods to gain deeper insights into the nature of human existence and interaction. This kind of reflection is a cornerstone of philosophical inquiry and helps to illuminate complex questions of human life and coexistence. Would you like to delve deeper into these considerations, or are there specific philosophical questions or topics that particularly interest you?
OK, I would like to stop here for today. Thank you for the inspiring answers.
You’re very welcome! It was an exciting conversation. If you have more questions or would like to continue the discussion, I’m here to help. Until next time!
Inquirer to chatGPT4: I will take the following short summary as bridge to the follow-up ideas : (1) Language expressions are composed of symbols wich are determined by rules and structures; (2) The inner states related to meaning are diverse and involve various cognitive, emotional, and sensory processes; (3) At the core are mental models that represent our understanding of the world. These models include abstract ideas, concrete objects, and complex scenarios. Furthermore the mind organizes concepts, emotions, sensory experiences, and language expressions into a network of associations. (4) Cognitive processes like inference and reasoning help us by connecting existing knowledge with knowledge about possible changes, to derive possible new states. Can you agree with this?
ChatGPT4: Yes, I agree with your summary. You’ve captured the essential points about how language expressions, inner states, mental models, and cognitive processes interact to create and understand meaning.
CHATGPT4 – PHILOSOPHY : Digging into the Human Meaning Space
Hi Chat, three days ago we reached the following conclusion centering around the ‘human meaning space’ : “Philosophical texts themselves are important, but they gain their true significance within the human meaning space that individuals create through their interactions with these texts and with each other. This meaning space, rooted in the experiences and interpretations of individual persons, is what ultimately forms the building blocks of a unified philosophical tradition. The tradition is not a static collection of texts, but a dynamic, evolving process of meaning-making that is constantly being enriched and redefined by those who engage with it.” Do you know something about the structure and dynamics of this meaning space?
The concept of a **human meaning space** is a fascinating and complex idea, touching on cognitive science, linguistics, philosophy, and social theory. While the idea isn’t always explicitly framed in these terms, we can explore the structure and dynamics of this meaning space by drawing on various theories and concepts from these fields.
### 1. **Structure of the Human Meaning Space**: The structure of the human meaning space can be understood as a multi-layered, interconnected web of meanings, built up through individual and collective experiences, language, and cultural practices. Here are some key elements:
– **Conceptual Frameworks**: At the core of the meaning space are conceptual frameworks—sets of basic concepts and categories that individuals and cultures use to organize and interpret the world. These include ideas about time, space, causality, identity, morality, and so on. Different cultures and individuals may have different conceptual frameworks, but they often share certain universal elements.
– **Language**: Language plays a central role in structuring the meaning space. Words, sentences, and narratives are the tools through which we express and communicate our thoughts and experiences. The structure of language, including grammar, syntax, and semantics, shapes how we perceive and describe the world (?)
– **Cultural Symbols and Norms**: Beyond language (?), cultural symbols (like religious icons, flags, or even corporate logos) and social norms (like laws or customs) contribute to the structure of the meaning space. These elements provide shared references and guide behavior, helping individuals navigate the social world.
– **Individual and Collective Memory**: The meaning space is also shaped by memory—both individual memories of personal experiences and collective memories shared by a community or society. These memories influence how we interpret new experiences and how we understand our place in the world.
### 2. **Dynamics of the Human Meaning Space**: The meaning space is not static; it is constantly evolving as individuals and communities interact with the world and each other. Here are some key dynamics:
– **Interpretation and Reinterpretation**: Individuals continuously interpret and reinterpret experiences and texts. New experiences, ideas, and cultural influences can lead to shifts in how concepts are understood, how language is used, and how meaning is constructed. This process of reinterpretation is central to the evolution of philosophical traditions.
– **Dialogue and Discourse**: Meaning is often shaped and reshaped through dialogue and discourse. When individuals engage in conversation or debate, they exchange ideas, challenge assumptions, and co-create new understandings. This dynamic exchange helps to refine and expand the meaning space.
– **Cultural Evolution and Adaptation**: As cultures evolve, so too does the meaning space. New technologies, social movements, and global interactions introduce new concepts and symbols into the cultural lexicon, which can alter or expand the collective meaning space. For example, the advent of digital technology has introduced new concepts like “virtual reality” and “cyberspace” that reshape our understanding of reality and communication.
– **Learning and Education**: The transmission of knowledge through education plays a crucial role in the dynamics of the meaning space. As individuals learn from teachers, texts, and experiences, they internalize and modify the existing meaning space, contributing to its continuity and transformation.
– **Emergence of New Concepts**: Sometimes, entirely new concepts emerge within the meaning space, often as a response to new challenges or discoveries. These emergent concepts can reshape the structure of the meaning space, leading to new ways of thinking and understanding.
### 3. **Philosophical Implications**: – **Hermeneutics**: The study of interpretation, especially of texts, is central to understanding the dynamics of the meaning space. Hermeneutics explores how meanings are constructed, how texts are understood, and how interpretations evolve over time.
– **Social Constructivism**: This theory posits that much of what we consider reality is socially constructed through language, culture, and shared practices. The meaning space, in this view, is a collective construction, shaped by social interactions and cultural norms.
– **Phenomenology**: This philosophical approach focuses on the structures of experience and consciousness. It emphasizes how individuals perceive and make sense of the world, highlighting the subjective aspect of the meaning space.
### Conclusion: The **human meaning space** is a dynamic, multi-layered structure shaped by language, culture, memory, and individual experiences. It evolves through interpretation, dialogue, cultural change, and the emergence of new ideas. Understanding this space requires considering both its structural elements and the dynamic processes that continuously shape and reshape it. This concept helps explain how philosophical traditions remain vibrant and relevant, constantly adapting to new contexts and challenges through the interplay of shared meanings and individual interpretations.
Hi Chat, it seems to me, that I have to differentiate my question a bit more: Yes, the ‘human meaning space’ includes some ‘common feature’ between different individual humans which is manifested by the shared language. But the ‘meaning’ of a languag expression is bound to the inner processes of each individual person. Therefore the usage of the samelanguage expression does not garantee that different individual persons associate automatically the ‘same meaning’ with a certain language expresseion. Would you agree?
Yes, I completely agree with your differentiation. The idea that the meaning of a language expression is tied to the internal processes of each individual person is crucial. Here’s how this distinction can be understood:
### 1. **Shared Language vs. Individual Interpretation**: – **Shared Language**: Language provides a common framework or set of symbols that allows individuals to communicate. This shared aspect of language is what enables us to exchange ideas, convey information, and engage in dialogue. – **Individual Interpretation**: However, the **meaning** that each person associates with a particular language expression is deeply influenced by their personal experiences, emotions, memories, and cognitive processes. As a result, even though two people might use the same word or phrase, they might not associate it with exactly the same meaning.
### 2. **The Gap Between Expression and Interpretation**: – **Subjectivity of Meaning**: Meaning is inherently subjective because it’s constructed within the mind of each individual. When someone hears or reads a word, their brain processes it based on their unique set of experiences and mental associations. For example, the word “home” might evoke a sense of warmth and security in one person but might bring up feelings of discomfort or displacement in another, depending on their personal history. – **Context and Nuance**: The context in which a word or phrase is used also plays a significant role in how it’s interpreted. The same word can carry different meanings in different situations, and individuals might pick up on different nuances depending on their personal context.
### 3. **Communication and Miscommunication**: – **Potential for Misunderstanding**: Because of these individual differences in interpretation, there is always the potential for misunderstanding or miscommunication. People might think they are conveying a certain meaning when using a word, but the listener or reader might interpret it differently based on their own mental framework. – **Clarification Through Dialogue**: This is why dialogue and conversation are so important. By engaging in discussion, individuals can clarify their meanings, ask questions, and work toward a shared understanding, even if their initial interpretations were different.
### 4. **Philosophical Perspectives**: – **Hermeneutics**: This branch of philosophy, particularly associated with thinkers like Hans-Georg Gadamer, emphasizes the importance of interpretation in understanding meaning. Hermeneutics suggests that every act of communication involves a process of interpretation, and this process is influenced by the interpreter’s historical and cultural context. – **Wittgenstein’s Language Games**: Ludwig Wittgenstein introduced the idea of “language games,” where the meaning of words is understood through their use in specific contexts or activities. This highlights how meaning can vary depending on the “game” being played, and how understanding is often a matter of grasping the rules of that particular game, which can differ from one person to another.
### 5. **Implications for the Human Meaning Space**: – The **human meaning space** is not a monolithic or uniform entity. It’s made up of countless individual meaning spaces that overlap and intersect in complex ways. The shared language provides a bridge between these individual spaces, but the meanings that cross this bridge are filtered through each person’s unique interpretive framework. – **Interpersonal Interaction**: The richness of human communication comes from this diversity of meaning, but it also requires effort to navigate and understand. Building a shared understanding often involves recognizing and respecting these differences, and finding ways to connect across them.
### Conclusion: While language gives us a shared set of symbols and expressions, the meanings attached to those expressions are deeply personal and subjective. The usage of the same language expression does not guarantee that different individuals will associate the same meaning with it, due to the influence of their unique internal processes and experiences. This complexity is both a challenge and a richness in human communication, requiring ongoing effort to achieve mutual understanding.
OK, let us take the following statement as starting point for the next ideas: “The human meaning space is made up of countless individual meaning spaces that overlap and intersect in complex ways. … Building a shared understanding often involves recognizing and respecting these differences, and finding ways to connect across them.” Here one follow-up question : How can a human actor A with his individual meaning space coordinate his individual meaning space with the individul meaning space of another human actor B?
Coordinating individual meaning spaces between two human actors, A and B, involves a dynamic process of communication, negotiation, and mutual understanding. This process requires both actors to engage in various strategies that allow them to bridge the differences in their interpretations and experiences. Here are some key ways in which this coordination can occur:
### 1. **Active Communication and Dialogue**: – **Expressing and Clarifying Meanings**: Actor A can express their thoughts, feelings, and interpretations clearly (?) to Actor B, and vice versa. This involves articulating not just what they think, but why they think it, including the experiences or reasoning behind their interpretations. Clarification questions, paraphrasing, and feedback loops are critical in ensuring that both parties understand each other’s intended meanings. – **Active Listening**: Effective coordination requires not just speaking but also listening. Actor A needs to actively listen to Actor B’s explanations and interpretations, and vice versa. Active listening involves paying close attention, avoiding assumptions, and being open to understanding the other’s perspective without immediately judging or dismissing it.
### 2. **Contextualization**: – **Providing Context**: Often, misunderstandings arise because different contexts or background information shape each actor’s interpretation. By providing context—explaining the background, the circumstances, or the specific meaning of terms as they understand them—Actor A can help Actor B align with their meaning space, and vice versa. – **Shared Experiences**: Drawing on shared experiences can help align meaning spaces. If Actors A and B have a common history or have shared certain experiences, referencing these can create a common ground for understanding.
### 3. **Negotiation of Meaning**: – **Negotiation and Compromise**: Sometimes, coordination requires negotiation, where both actors adjust their interpretations to reach a common understanding. This might involve redefining terms, agreeing on certain interpretations, or finding middle ground that accommodates both perspectives. – **Iterative Refinement**: Actor A might initially explain something, Actor B might respond with their interpretation, and through back-and-forth exchanges, both actors refine their understanding until they reach a shared meaning.
### 4. **Use of Metaphors and Analogies**: – **Metaphors and Analogies**: These tools can be powerful for bridging gaps in meaning spaces. By comparing a concept to something familiar to both actors, they can better align their interpretations. For example, Actor A might use an analogy that resonates with Actor B’s experiences, helping to convey a concept in a way that B can relate to more easily.
### 5. **Empathy and Perspective-Taking**: – **Empathy**: Empathy involves trying to understand the other actor’s feelings and perspective. By empathizing with Actor B, Actor A can better grasp why B interprets things in a certain way, and this understanding can help in coordinating their meaning spaces. – **Perspective-Taking**: This is the cognitive aspect of empathy, where Actor A consciously attempts to see things from Actor B’s viewpoint. By mentally putting themselves in B’s shoes, A can adjust their communication to better resonate with B’s meaning space.
### 6. **Cultural and Social Awareness**: – **Awareness of Cultural Differences**: If Actors A and B come from different cultural backgrounds, their meaning spaces may differ significantly. Being aware of these cultural differences and how they might influence interpretation can help in adjusting communication strategies to better align meaning spaces. – **Social Norms and Conventions**: Understanding and utilizing social norms that both actors share can also help in coordinating meaning spaces. These norms provide a framework for expected behaviors and interpretations, making it easier to find common ground.
### 7. **Feedback Mechanisms**: – **Seeking and Providing Feedback**: Actor A can ask Actor B whether their message was understood as intended, and B can do the same. This feedback helps identify where misalignments in meaning might exist and provides an opportunity to correct them. – **Continuous Adjustment**: Feedback allows for continuous adjustment. As Actors A and B continue to interact, they can refine their communication and interpretation strategies, leading to better alignment over time.
### 8. **Language and Conceptual Framing**: – **Shared Vocabulary**: Developing a shared vocabulary, where both actors agree on the meanings of key terms, can facilitate coordination. This might involve explicitly defining terms or agreeing on certain concepts before proceeding with a discussion. – **Conceptual Framing**: Framing discussions in terms of concepts or ideas that are familiar to both actors can help in aligning their meaning spaces. If both actors understand a concept similarly, they can use it as a reference point for further discussion.
### Conclusion: Coordinating individual meaning spaces between two human actors involves a complex interplay of communication, empathy, negotiation, and shared context. By engaging in active dialogue, providing context, using metaphors, exercising empathy, and seeking feedback, Actors A and B can bridge their differences and build a shared understanding. This process is iterative and dynamic, requiring ongoing effort and adjustment as both actors navigate their individual meaning spaces and work toward alignment.
FRAGE: OK, I like to keep the following statements as minimal requirements : (1) Effective coordination requires not just speaking but also listening. (2) If Actors A and B have a common history or have shared experiences, referencing these can create a common ground for understanding. Feedback allows for continuous adjustment. (3) (1) – (2) can support the development of a shared vocabulary. Would you agree?
Yes, I agree with your summary. The three statements you’ve outlined capture essential aspects of how effective coordination between individual meaning spaces can occur. Here’s a brief reflection on each point:
1. **Effective coordination requires not just speaking but also listening**: – This emphasizes the importance of active, two-way communication. Listening is crucial for understanding the other person’s perspective, which is necessary for aligning meaning spaces.
2. **If Actors A and B have a common history or have shared experiences, referencing these can create a common ground for understanding. Feedback allows for continuous adjustment**: – Shared experiences and history provide a foundation for mutual understanding. When actors reference these shared elements, they can more easily connect their meaning spaces. Feedback mechanisms allow both actors to continuously refine and adjust their understanding, ensuring that misalignments are addressed.
3. **(1) – (2) can support the development of a shared vocabulary**: – Through effective communication and the use of shared experiences, Actors A and B can gradually develop a shared vocabulary. This shared vocabulary helps streamline future interactions by establishing common definitions and meanings for key terms, reducing potential misunderstandings.
These statements encapsulate the core processes that enable individuals to coordinate their meaning spaces and build a deeper, more effective understanding with each other.
Hi Chat, let us take a look into the ‘inner structure’ of an individual meaning space: (i) On the one side of meaning we habe the ‘expressions of some language’ which is ‘internally represented’. (ii) On the other side we have a rich diversity of inner states of the human actor which deliver the ‘stuff’ which we call ‘meaning’ and which is ‘related’ to the ‘internally represented expressions’ of the used language. Can you describe a bit the ‘structure’ of these inner states related to language expressions?
The **inner structure** of an individual meaning space, especially how it relates to language expressions, is a complex and layered system. This system involves the interaction between **internally represented language expressions** (i.e., words, sentences, symbols) and the **inner states** of the human actor that give rise to meaning. Let’s explore this in more detail:
### 1. **Language Expressions and Internal Representations**: – **Symbols and Words**: Language expressions are composed of symbols (letters, words, sounds) that are internally represented in the brain. These representations are tied to specific neural patterns or cognitive structures that store and process linguistic information. – **Syntax and Grammar**: These internal representations are not just individual words but also the rules and structures (syntax, grammar) that determine how these words can be combined to form meaningful sentences. This layer of structure helps the mind organize language into coherent thoughts and communications.
### 2. **Inner States and Their Structure**: The **inner states** related to meaning are diverse and involve various cognitive, emotional, and sensory processes. Here are some key components:
– **Conceptual Structures**: – **Mental Models and Concepts**: At the core of the meaning-making process are **conceptual structures**—the mental models and concepts that represent our understanding of the world. These models include abstract ideas (like justice or beauty), concrete objects (like a tree or a car), and complex scenarios (like a conversation or a journey). – **Schemas and Frames**: These are cognitive structures that organize knowledge and guide interpretation. A schema might represent a typical event (like “going to a restaurant”), while a frame provides a perspective or context for understanding a situation (like seeing an argument as a debate or a conflict).
– **Emotional and Affective States**: – **Emotions**: Emotions play a significant role in the meaning space. When we process language, the meaning we derive is often colored by our emotional state. For instance, the word “home” might trigger feelings of warmth and safety for one person, while for another, it might evoke feelings of sadness or loss. – **Affective Associations**: These are the emotional responses tied to specific concepts or experiences. They contribute to how strongly or weakly certain meanings resonate with us and can influence how we interpret language.
– **Sensory and Perceptual Experiences**: – **Sensory Memories**: Sensory experiences (like sights, sounds, smells) are often tied to language expressions. For example, the word “ocean” might bring up the smell of saltwater, the sound of waves, and the feeling of sand underfoot, all of which contribute to the word’s meaning. – **Imagery**: The mind often creates mental images in response to language. These images are not just visual but can involve other senses as well. This sensory component enriches the meaning associated with language expressions.
– **Cognitive Processes**: – **Inference and Reasoning**: Cognitive processes like inference and reasoning help us make sense of language by connecting new information with existing knowledge. When we hear a sentence, we use reasoning to infer the speaker’s intent, predict outcomes, or draw connections with other ideas. – **Attention and Focus**: The focus of attention determines which aspects of a language expression we emphasize and how we interpret its meaning. What we pay attention to can shape the meaning we derive from a given expression.
### 3. **Relational and Associative Networks**: – **Associative Networks**: The mind organizes concepts, emotions, sensory experiences, and language expressions into a network of associations. For example, the word “winter” might be associated with cold weather, snow, holidays, and feelings of coziness. These associations form a web of meaning that influences how language expressions are understood. – **Relational Dynamics**: Meaning is often understood in terms of relationships between concepts. For instance, understanding the concept of “parent” is related to understanding “child,” “family,” and “care.” These relational dynamics are part of the inner structure that gives rise to meaning.
### 4. **Integration of Inner States and Language**: – **Embodied Cognition**: This theory suggests that our cognition is deeply rooted in bodily experiences. The meaning of language is not just an abstract mental process but is also tied to how we physically interact with the world. For instance, understanding the word “grasp” involves not just the mental concept but also the sensory-motor experience of physically grasping something. – **Contextual Integration**: The meaning of a language expression is often determined by the context in which it is used. This context includes both external factors (like the situation or environment) and internal states (like emotions or prior knowledge). The integration of these contextual factors is crucial in shaping meaning.
### Conclusion: The inner structure of an individual meaning space is a complex system where **language expressions** are connected to a rich diversity of **inner states**. These inner states include conceptual structures, emotional and sensory experiences, cognitive processes, and associative networks. Together, these elements create a dynamic and multi-dimensional web of meaning that allows individuals to interpret and understand language in highly personalized ways. The interaction between these inner states and language is what gives rise to the meaning that individuals derive from their linguistic experiences.
I will take the following short summary as bridge to the follow-up ideas : (1) Language expressions are composed of symbols wich are determined by rules and structures; (2) The inner states related to meaning are diverse and involve various cognitive, emotional, and sensory processes; (3) At the core are mental models that represent our understanding of the world. These models include abstract ideas, concrete objects, and complex scenarios. Furthermore the mind organizes concepts, emotions, sensory experiences, and language expressions into a network of associations. (4) Cognitive processes like inference and reasoning help us by connecting existing knowledge with knowledge about possible changes, to derive possible new states. Can you agree with this?
Yes, I agree with your summary. You’ve captured the essential points about how language expressions, inner states, mental models, and cognitive processes interact to create and understand meaning. Here’s a brief recap:
1. **Language Expressions**: These are composed of symbols (words, phrases) that are structured according to the rules of grammar and syntax, enabling coherent communication.
2. **Diverse Inner States**: Meaning arises from a complex interplay of cognitive, emotional, and sensory processes within the mind. These processes influence how we interpret and understand language.
3. **Mental Models and Associations**: At the core of meaning-making are mental models, which represent our understanding of the world. These models include abstract concepts, concrete objects, and complex scenarios. The mind organizes these elements into a network of associations, connecting various concepts, emotions, and sensory experiences.
4. **Cognitive Processes**: Inference, reasoning, and other cognitive processes allow us to connect existing knowledge with new information or hypothetical changes, enabling us to derive new states or understand potential outcomes.
This summary effectively bridges the foundational ideas we’ve discussed, setting the stage for deeper exploration into how these components work together in more complex scenarios or applications.
OK, let us stop here for today. I will come back to this issue to continue. Best regards
That sounds great! I’m glad we could delve into these ideas together. Feel free to reach out anytime you’re ready to continue. Best regards, and take care! 😊
A ‘text’ shall be written that speaks about the world, including all living beings, with ‘humans’ as the authors in the first instance. So far, we know of no cases where animals or plants write texts themselves: their view of life. We only know of humans who write from ‘their human perspective’ about life, animals, and plants. Much can be criticized about this approach. Upon further reflection, one might even realize that ‘humans writing about other humans and themselves’ is not so trivial either. Even humans writing ‘about themselves’ is prone to errors, can go completely ‘awry,’ can be entirely ‘wrong,’ which raises the question of what is ‘true’ or ‘false.’ Therefore, we should spend some thoughts on how we humans can talk about the world and ourselves in a way that gives us a chance not just to ‘fantasize,’ but to grasp something that is ‘real,’ something that describes what truly characterizes us as humans, as living beings, as inhabitants of this planet… but then the question pops up again, what is ‘real’? Are we caught in a cycle of questions with answers, where the answers themselves are again questions upon closer inspection?
First Steps
Life on Planet Earth
At the start of writing, we assume that there is a ‘Planet Earth’ and on this planet there is something we call ‘life,’ and we humans—belonging to the species Homo sapiens—are part of it.
Language
We also assume that we humans have the ability to communicate with each other using sounds. These sounds, which we use for communication, we call here ‘speech sounds’ to indicate that the totality of sounds for communication forms a ‘system’ which we ultimately call ‘language.’
Meaning
Since we humans on this planet can use completely different sounds for the ‘same objects’ in the same situation, it suggests that the ‘meaning’ of speech sounds is not firmly tied to the speech sounds themselves, but somehow has to do with what happens ‘in our minds.’ Unfortunately, we cannot look ‘into our minds.’ It seems a lot happens there, but this happening in the mind is ‘invisible.’ Nevertheless, in ‘everyday life,’ we experience that we can ‘agree’ with others whether it is currently ‘raining’ or if it smells ‘bad’ or if there is a trash bin on the sidewalk blocking the way, etc. So somehow, the ‘happenings in the mind’ seem to have certain ‘agreements’ among different people, so that not only I see something specific, but the other person does too, and we can even use the same speech sounds for it. And since a program like chatGPT can translate my German speech sounds, e.g., into English speech sounds, I can see that another person who does not speak German, instead of my word ‘Mülltonne,’ uses the word ‘trash bin’ and then nods in agreement: ‘Yes, there is a trash bin.’ Would that be a case for a ‘true statement’?
Changes and Memories
Since we experience daily how everyday life constantly ‘changes,’ we know that something that just found agreement may no longer find it the next moment because the trash bin is no longer there. We can only notice these changes because we have something called ‘memory’: we can remember that just now at a specific place there was a trash bin, but now it’s not. Or is this memory just an illusion? Can I trust my memory? If now everyone else says there was no trash bin, but I remember there was, what does that mean?
Concrete Body
Yes, and then my body: time and again I need to drink something, eat something, I’m not arbitrarily fast, I need some space, … my body is something very concrete, with all sorts of ‘sensations,’ ‘needs,’ a specific ‘shape,’ … and it changes over time: it grows, it ages, it can become sick, … is it like a ‘machine’?
Galaxies of Cells
Today we know that our human body resembles less a ‘machine’ and more a ‘galaxy of cells.’ Our body has about 37 trillion (10¹²) body cells with another 100 trillion cells in the gut that are vital for our digestive system, and these cells together form the ‘body system.’ The truly incomprehensible thing is that these approximately 140 trillion cells are each completely autonomous living beings, with everything needed for life. And if you know how difficult it is for us as humans to maintain cooperation among just five people over a long period, then you can at least begin to appreciate what it means that 140 trillion beings manage to communicate and coordinate actions every second—over many years, even decades—so that the masterpiece ‘human body’ exists and functions.
Origin as a Question
And since there is no ‘commander’ who constantly tells all the cells what to do, this ‘miracle of the human system’ expands further into the dimension of where the concept comes from that enables this ‘super-galaxy of cells’ to be as they are. How does this work? How did it arise?
Looking Behind Phenomena
In the further course, it will be important to gradually penetrate the ‘surface of everyday phenomena’ starting from everyday life, to make visible those structures that are ‘behind the phenomena,’ those structures that hold everything together and at the same time constantly move, change everything.
Fundamental Dimension of Time
All this implies the phenomenon ‘time’ as a basic category of all reality. Without time, there is also no ‘truth’…
[1] Specialists in brain research will of course raise their hand right away, and will want to say that they can indeed ‘look into the head’ by now, but let’s wait and see what this ‘looking into the head’ entails.
[2] If we assume for the number of stars in our home galaxy, the Milky Way, with an estimated 100 – 400 billion stars that there are 200 billion, then our body system would correspond to the scope of 700 galaxies in the format of the Milky Way, one cell for one star.
[3] Various disciplines of natural sciences, especially certainly evolutionary biology, have illuminated many aspects of this mega-wonder partially over the last approx. 150 years. One can marvel at the physical view of our universe, but compared to the super-galaxies of life on Planet Earth, the physical universe seems downright ‘boring’… Don’t worry: ultimately, both are interconnected: one explains the other…”
Telling Stories
Fragments of Everyday Life—Without Context
We constantly talk about something: the food, the weather, the traffic, shopping prices, daily news, politics, the boss, colleagues, sports events, music, … mostly, these are ‘fragments’ from the larger whole that we call ‘everyday life’. People in one of the many crisis regions on this planet, especially those in natural disasters or even in war…, live concretely in a completely different world, a world of survival and death.
These fragments in the midst of life are concrete, concern us, but they do not tell a story by themselves about where they come from (bombs, rain, heat,…), why they occur, how they are connected with other fragments. The rain that pours down is a single event at a specific place at a specific time. The bridge that must be closed because it is too old does not reveal from itself why this particular bridge, why now, why couldn’t this be ‘foreseen’? The people who are ‘too many’ in a country or also ‘too few’: Why is that? Could this have been foreseen? What can we do? What should we do?
The stream of individual events hits us, more or less powerfully, perhaps even simply as ‘noise’: we are so accustomed to it that we no longer even perceive certain events. But these events as such do not tell a ‘story about themselves’; they just happen, seemingly irresistibly; some say ‘It’s fate’.
Need for Meaning
It is notable that we humans still try to give the whole a ‘meaning’, to seek an ‘explanation’ for why things are the way they are. And everyday life shows that we have a lot of ‘imagination’ concerning possible ‘connections’ or ’causes’. Looking back into the past, we often smile at the various attempts at explanation by our ancestors: as long as nothing was known about the details of our bodies and about life in general, any story was possible. In our time, with science established for about 150 years, there are still many millions of people (possibly billions?) who know nothing about science and are willing to believe almost any story just because another person tells this story convincingly.
Liberation from the Moment through Words
Because of this ability, with the ‘power of imagination’ to pack things one experiences into a ‘story’ that suggests ‘possible connections’, through which events gain a ‘conceptual sense’, a person can try to ‘liberate’ themselves from the apparent ‘absoluteness of the moment’ in a certain way: an event that can be placed into a ‘context’ loses its ‘absoluteness’. Just by this kind of narrative, the experiencing person gains a bit of ‘power’: in narrating a connection, the narrator can make the experience ‘a matter’ over which they can ‘dispose’ as they see fit. This ‘power through the word’ can alleviate the ‘fear’ that an event can trigger. This has permeated the history of humanity from the beginning, as far as archaeological evidence allows.
Perhaps it is not wrong to first identify humans not as ‘hunters and gatherers’ or as ‘farmers’ but as ‘those who tell stories’.
[1] Such a magic word in Greek philosophy was the concept of ‘breath’ (Greek “pneuma”). The breath not only characterized the individually living but was also generalized to a life principle of everything that connected both body, soul, and spirit as well as permeated the entire universe. In the light of today’s knowledge, this ‘explanation’ could no longer be told, but about 2300 years ago, this belief was a certain ‘intellectual standard’ among all intellectuals, the prevailing ‘worldview’; it was ‘believed’. Anyone who thought differently was outside this ‘language game’.
Organization of an Order
Thinking Creates Relationships
As soon as one can ‘name’ individual events, things, processes, properties of things, and more through ‘language’, it is evident that humans have the ability to not only ‘name’ using language but to embed the ‘named’ through ‘arrangement of words in linguistic expression’ into ‘conceived relationships’, thereby connecting the individually named items not in isolation but in thought with others. This fundamental human ability to ‘think relationships in one’s mind’, which cannot be ‘seen’ but can indeed be ‘thought’ [1], is of course not limited to single events or a single relationship. Ultimately, we humans can make ‘everything’ a subject, and we can ‘think’ any ‘possible relationship’ in our minds; there are no fundamental restrictions here.
Stories as a Natural Force
Not only history is full of examples, but also our present day. Today, despite the incredible successes of modern science, almost universally, the wildest stories with ‘purely thought relationships’ are being told and immediately believed through all channels worldwide, which should give us pause. Our fundamental characteristic, that we can tell stories to break the absoluteness of the moment, obviously has the character of a ‘natural force’, deeply rooted within us, that we cannot ‘eradicate’; we might be able to ‘tame’ it, perhaps ‘cultivate’ it, but we cannot stop it. It is an ‘elemental characteristic’ of our thinking, that is: of our brain in the body.
Thought and Verified
The experience that we, the storytellers, can name events and arrange them into relationships—and ultimately without limit—may indeed lead to chaos if the narrated network of relationships is ultimately ‘purely thought’, without any real reference to the ‘real world around us’, but it is also our greatest asset. With it, humans can not only fundamentally free themselves from the apparent absoluteness of the present, but we can also create starting points with the telling of stories, ‘initially just thought relationships’, which we can then concretely ‘verify’ in our everyday lives.
A System of Order
When someone randomly sees another person who looks very different from what they are used to, all sorts of ‘assumptions’ automatically form in each person about what kind of person this might be. If one stops at these assumptions, these wild guesses can ‘populate the head’ and the ‘world in the head’ gets populated with ‘potentially evil people’; eventually, they might simply become ‘evil’. However, if one makes contact with the other, they might find that the person is actually nice, interesting, funny, or the like. The ‘assumptions in the head’ then transform into ‘concrete experiences’ that differ from what was initially thought. ‘Assumptions’ combined with ‘verification’ can thus lead to the formation of ‘reality-near ideas of relationships’. This gives a person the chance to transform their ‘spontaneous network of thought relationships’, which can be wrong—and usually are—into a ‘verified network of relationships’. Since ultimately the thought relationships as a network provide us with a ‘system of order’ in which everyday things are embedded, it appears desirable to work with as many ‘verified thought relationships’ as possible.
[1] The breath of the person opposite me, which for the Greeks connected my counterpart with the life force of the universe, which in turn is also connected with the spirit and the soul…
Hypotheses and Science
Challenge: Methodically Organized Guessing
The ability to think of possible relationships, and to articulate them through language, is innate [1], but the ‘use’ of this ability in everyday life, for example, to match thought relationships with the reality of everyday life, this ‘matching’/’verifying’ is not innate. We can do it, but we don’t have to. Therefore, it is interesting to realize that since the first appearance of Homo sapiens on this planet [2], 99.95% of the time has passed until the establishment of organized modern science about 150 years ago. This can be seen as an indication that the transition from ‘free guessing’ to ‘methodically organized systematic guessing’ must have been anything but easy. And if today still a large part of people—despite schooling and even higher education—[3] tend to lean towards ‘free guessing’ and struggle with organized verification, then there seems to be a not easy threshold that a person must overcome—and must continually overcome—to transition from ‘free’ to ‘methodically organized’ guessing.[4]
Starting Point for Science
The transition from everyday thinking to ‘scientific thinking’ is fluid. The generation of ‘thought relationships’ in conjunction with language, due to our ability of creativity/imagination, is ultimately also the starting point of science. While in everyday thinking we tend to spontaneously and pragmatically ‘verify’ ‘spontaneously thought relationships’, ‘science’ attempts to organize such verifications ‘systematically’ to then accept such ‘positively verified guesses’ as ’empirically verified guesses’ until proven otherwise as ‘conditionally true’. Instead of ‘guesses’, science likes to speak of ‘hypotheses’ or ‘working hypotheses’, but they remain ‘guesses’ through the power of our thinking and through the power of our imagination.[5]
[1] This means that the genetic information underlying the development of our bodies is designed so that our body with its brain is constructed during the growth phase in such a way that we have precisely this ability to ‘think of relationships’. It is interesting again to ask how it is possible that from a single cell about 13 trillion body cells (the approximately 100 trillion bacteria in the gut come ‘from outside’) can develop in such a way that they create the ‘impression of a human’ that we know.
[2] According to current knowledge, about 300,000 years ago in East Africa and North Africa, from where Homo sapiens then explored and conquered the entire world (there were still remnants of other human forms that had been there longer).
[3] I am not aware of representative empirical studies on how many people in a population tend to do this.
[4] Considering that we humans as the life form Homo sapiens only appeared on this planet after about 3.8 billion years, the 300,000 years of Homo sapiens make up roughly 0.008% of the total time since there has been life on planet Earth. Thus, not only are we as Homo sapiens a very late ‘product’ of the life process, but the ability to ‘systematically verify hypotheses’ also appears ‘very late’ in our Homo sapiens life process. Viewed across the entire life span, this ability seems to be extremely valuable, which is indeed true considering the incredible insights we as Homo sapiens have been able to gain with this form of thinking. The question is how we deal with this knowledge. This behavior of using systematically verified knowledge is not innate too.
[5] The ability of ‘imagination’ is not the opposite of ‘knowledge’, but is something completely different. ‘Imagination’ is a trait that ‘shows’ itself the moment we start to think, perhaps even in the fact ‘that’ we think at all. Since we can in principle think about ‘everything’ that is ‘accessible’ to our thinking, imagination is a factor that helps to ‘select’ what we think. In this respect, imagination is pre-posed to thinking.
TRANSLATION: The following text is a translation from a German version into English. For the translation I am using the software deepL.com as well as chatGPT 4. The English version is a slightly revised version of the German text.
This blog entry will be completed today. However, it has laid the foundations for considerations that will be pursued further in a new blog entry.
Triggered by several reasons I started some investigation in the phenomenon of ‘propaganda’ to sharpen my understanding. My strategy was first to try to characterize the phenomenon of ‘general communication’ in order to find some ‘harder criteria’ that would allow to characterize the concept of ‘propaganda’ to stand out against this general background in a somewhat comprehensible way.
The realization of this goal then actually led to an ever more fundamental examination of our normal (human) communication, so that forms of propaganda become recognizable as ‘special cases’ of our communication. The worrying thing about this is that even so-called ‘normal communication’ contains numerous elements that can make it very difficult to recognize and pass on ‘truth’ (*). ‘Massive cases of propaganda’ therefore have their ‘home’ where we communicate with each other every day. So if we want to prevent propaganda, we have to start in everyday life.
(*) The concept of ‘truth’ is examined and explained in great detail in the following long text below. Unfortunately, I have not yet found a ‘short formula’ for it. In essence, it is about establishing a connection to ‘real’ events and processes in the world – including one’s own body – in such a way that they can, in principle, be understood and verified by others.
DICTATORIAL CONTEXT
However, it becomes difficult when there is enough political power that can set the social framework conditions in such a way that for the individual in everyday life – the citizen! – general communication is more or less prescribed – ‘dictated’. Then ‘truth’ becomes less and less or even non-existent. A society is then ‘programmed’ for its own downfall through the suppression of truth. ([3], [6]).
EVERYDAY LIFE AS A DICTATOR ? The hour of narratives
But – and this is the far more dangerous form of ‘propaganda’ ! – even if there is not a nationwide apparatus of power that prescribes certain forms of ‘truth’, a mutilation or gross distortion of truth can still take place on a grand scale. Worldwide today, in the age of mass media, especially in the age of the internet, we can see that individuals, small groups, special organizations, political groups, entire religious communities, in fact all people and their social manifestations, follow a certain ‘narrative’ [*11] when they act.
Typical for acting according to a narrative is that those who do so individually believe that it is ‘their own decision’ and that their narrative is ‘true’, and that they are therefore ‘in the right’ when they act accordingly. This ‘feeling to be right’ can go as far as claiming the right to kill others because they ‘act wrongly’ in the light of their own ‘narrative’. We should therefore speak here of a ‘narrative truth’: Within the framework of the narrative, a picture of the world is drawn that ‘as a whole’ enables a perspective that ‘as such’ is ‘found to be good’ by the followers of the narrative, as ‘making sense’. Normally, the effect of a narrative, which is experienced as ‘meaningful’, is so great that the ‘truth content’ is no longer examined in detail.
RELIGIOUS NARRATIVES
This has existed at all times in the history of mankind. Narratives that appeared as ‘religious beliefs’ were particularly effective. It is therefore no coincidence that almost all governments of the last millennia have adopted religious beliefs as state doctrines; an essential component of religious beliefs is that they are ‘unprovable’, i.e. ‘incapable of truth’. This makes a religious narrative a wonderful tool in the hands of the powerful to motivate people to behave in certain ways without the threat of violence.
POPULAR NARRATIVES
In recent decades, however, we have experienced new, ‘modern forms’ of narratives that do not come across as religious narratives, but which nevertheless have a very similar effect: People perceive these narratives as ‘giving meaning’ in a world that is becoming increasingly confusing and therefore threatening for everyone today. Individual people, the citizens, also feel ‘politically helpless’, so that – even in a ‘democracy’ – they have the feeling that they cannot directly influence anything: the ‘people up there’ do what they want. In such a situation, ‘simplistic narratives’ are a blessing for the maltreated soul; you hear them and have the feeling: yes, that’s how it is; that’s exactly how I ‘feel’!
Such ‘popular narratives’, which enable ‘good feelings’, are gaining ever greater power. What they have in common with religious narratives is that the ‘followers’ of popular narratives no longer ask the ‘question of truth’; most of them are also not sufficiently ‘trained’ to be able to clarify the truth of a narrative at all. It is typical for supporters of narratives that they are generally hardly able to explain their own narrative to others. They typically send each other links to texts/videos that they find ‘good’ because these texts/videos somehow seem to support the popular narrative, and tend not to check the authors and sources because they are in the eyes of the followers such ‘decent people’, which always say exactly the ‘same thing’ as the ‘popular narrative’ dictates.
NARRATIVES ARE SEXY FOR POWER
If you now take into account that the ‘world of narratives’ is an extremely tempting offer for all those who have power over people or would like to gain power over people, then it should come as no surprise that many governments in this world, many other power groups, are doing just that today: they do not try to coerce people ‘directly’, but they ‘produce’ popular narratives or ‘monitor’ already existing popular narratives’ in order to gain power over the hearts and minds of more and more people via the detour of these narratives. Some speak here of ‘hybrid warfare’, others of ‘modern propaganda’, but ultimately, I guess, these terms miss the core of the problem.
THE NARRATIVE AS A BASIC CULTURAL PATTERN The ‘irrational’ defends itself against the ‘rational’
The core of the problem is the way in which human communities have always organized their collective action, namely through narratives; we humans have no other option. However, such narratives – as the considerations further down in the text will show – are extremely susceptible to ‘falsity’, to a ‘distortion of the picture of the world’. In the context of the development of legal systems, approaches have been developed during at least the last 7000 years to ‘improve’ the abuse of power in a society by supporting truth-preserving mechanisms. Gradually, this has certainly helped, with all the deficits that still exist today. Additionally, about 500 years ago, a real revolution took place: humanity managed to find a format with the concept of a ‘verifiable narrative (empirical theory)’ that optimized the ‘preservation of truth’ and minimized the slide into untruth. This new concept of ‘verifiable truth’ has enabled great insights that before were beyond imagination .
The ‘aura of the scientific’ has meanwhile permeated almost all of human culture, almost! But we have to realize that although scientific thinking has comprehensively shaped the world of practicality through modern technologies, the way of scientific thinking has not overridden all other narratives. On the contrary, the ‘non-truth narratives’ have become so strong again that they are pushing back the ‘scientific’ in more and more areas of our world, patronizing it, forbidding it, eradicating it. The ‘irrationality’ of religious and popular narratives is stronger than ever before. ‘Irrational narratives’ are for many so appealing because they spare the individual from having to ‘think for themselves’. Real thinking is exhausting, unpopular, annoying and hinders the dream of a simple solution.
THE CENTRAL PROBLEM OF HUMANITY
Against this backdrop, the widespread inability of people to recognize and overcome ‘irrational narratives’ appears to be the central problem facing humanity in mastering the current global challenges. Before we need more technology (we certainly do), we need more people who are able and willing to think more and better, and who are also able to solve ‘real problems’ together with others. Real problems can be recognized by the fact that they are largely ‘new’, that there are no ‘simple off-the-shelf’ solutions for them, that you really have to ‘struggle’ together for possible insights; in principle, the ‘old’ is not enough to recognize and implement the ‘true new’, and the future is precisely the space with the greatest amount of ‘unknown’, with lots of ‘genuinely new’ things.
The following text examines this view in detail.
MAIN TEXT FOR EXPLANATION
MODERN PROPAGANDA ?
As mentioned in the introduction the trigger for me to write this text was the confrontation with a popular book which appeared to me as a piece of ‘propaganda’. When I considered to describe my opinion with own words I detected that I had some difficulties: what is the difference between ‘propaganda’ and ‘everyday communication’? This forced me to think a little bit more about the ingredients of ‘everyday communication’ and where and why a ‘communication’ is ‘different’ to our ‘everyday communication’. As usual in the beginning of some discussion I took a first look to the various entries in Wikipedia (German and English). The entry in the English Wikipedia on ‘Propaganda [1b] attempts a very similar strategy to look to ‘normal communication’ and compared to this having a look to the phenomenon of ‘propaganda’, albeit with not quite sharp contours. However, it provides a broad overview of various forms of communication, including those forms that are ‘special’ (‘biased’), i.e. do not reflect the content to be communicated in the way that one would reproduce it according to ‘objective, verifiable criteria’.[*0] However, the variety of examples suggests that it is not easy to distinguish between ‘special’ and ‘normal’ communication: What then are these ‘objective verifiable criteria’? Who defines them?
Assuming for a moment that it is clear what these ‘objectively verifiable criteria’ are, one can tentatively attempt a working definition for the general (normal?) case of communication as a starting point:
Working Definition:
The general case of communication could be tentatively described as a simple attempt by one person – let’s call them the ‘author’ – to ‘bring something to the attention’ of another person – let’s call them the ‘interlocutor’. We tentatively call what is to be brought to their attention ‘the message’. We know from everyday life that an author can have numerous ‘characteristics’ that can affect the content of his message.
Here is a short list of properties that characterize the author’s situation in a communication. Then corresponding properties for the interlocutor.
The Author:
The available knowledge of the author — both conscious and unconscious — determines the kind of message the author can create.
His ability to discern truth determines whether and to what extent he can differentiate what in his message is verifiable in the real world — present or past — as ‘accurate’ or ‘true’.
His linguistic ability determines whether and how much of his available knowledge can be communicated linguistically.
The world of emotions decides whether he wants to communicate anything at all, for example, when, how, to whom, how intensely, how conspicuously, etc.
The social context can affect whether he holds a certain social role, which dictates when he can and should communicate what, how, and with whom.
The real conditions of communication determine whether a suitable ‘medium of communication’ is available (spoken sound, writing, sound, film, etc.) and whether and how it is accessible to potential interlocutors.
The author’s physical constitution decides how far and to what extent he can communicate at all.
The Interlocutor:
In general, the characteristics that apply to the author also apply to the interlocutor. However, some points can be particularly emphasized for the role of the interlocutor:
The available knowledge of the interlocutor determines which aspects of the author’s message can be understood at all.
The ability of the interlocutor to discern truth determines whether and to what extent he can also differentiate what in the conveyed message is verifiable as ‘accurate’ or ‘true’.
The linguistic ability of the interlocutor affects whether and how much of the message he can absorb purely linguistically.
Emotions decide whether the interlocutor wants to take in anything at all, for example, when, how, how much, with what inner attitude, etc.
The social context can also affect whether the interlocutor holds a certain social role, which dictates when he can and should communicate what, how, and with whom.
Furthermore, it can be important whether the communication medium is so familiar to the interlocutor that he can use it sufficiently well.
The physical constitution of the interlocutor can also determine how far and to what extent the interlocutor can communicate at all.
Even this small selection of factors shows how diverse the situations can be in which ‘normal communication’ can take on a ‘special character’ due to the ‘effect of different circumstances’. For example, an actually ‘harmless greeting’ can lead to a social problem with many different consequences in certain roles. A seemingly ‘normal report’ can become a problem because the contact person misunderstands the message purely linguistically. A ‘factual report’ can have an emotional impact on the interlocutor due to the way it is presented, which can lead to them enthusiastically accepting the message or – on the contrary – vehemently rejecting it. Or, if the author has a tangible interest in persuading the interlocutor to behave in a certain way, this can lead to a certain situation not being presented in a ‘purely factual’ way, but rather to many aspects being communicated that seem suitable to the author to persuade the interlocutor to perceive the situation in a certain way and to adopt it accordingly. These ‘additional’ aspects can refer to many real circumstances of the communication situation beyond the pure message.
Types of communication …
Given this potential ‘diversity’, the question arises as to whether it will even be possible to define something like normal communication?
In order to be able to answer this question meaningfully, one should have a kind of ‘overview’ of all possible combinations of the properties of author (1-7) and interlocutor (1-8) and one should also have to be able to evaluate each of these possible combinations with a view to ‘normality’.
It should be noted that the two lists of properties author (1-7) and interlocutor (1-8) have a certain ‘arbitrariness’ attached to them: you can build the lists as they have been constructed here, but you don’t have to.
This is related to the general way in which we humans think: on one hand, we have ‘individual events that happen’ — or that we can ‘remember’ —, and on the other hand, we can ‘set’ ‘arbitrary relationships’ between ‘any individual events’ in our thinking. In science, this is called ‘hypothesis formation’. Whether or not such formation of hypotheses is undertaken, and which ones, is not standardized anywhere. Events as such do not enforce any particular hypothesis formations. Whether they are ‘sensible’ or not is determined solely in the later course of their ‘practical use’. One could even say that such hypothesis formation is a rudimentary form of ‘ethics’: the moment one adopts a hypothesis regarding a certain relationship between events, one minimally considers it ‘important’, otherwise, one would not undertake this hypothesis formation.
In this respect, it can be said that ‘everyday life’ is the primary place for possible working hypotheses and possible ‘minimum values’.
The following diagram demonstrates a possible arrangement of the characteristics of the author and the interlocutor:
FIGURE : Overview of the possible overlaps of knowledge between the author and the interlocutor, if everyone can have any knowledge at its disposal.
What is easy to recognize is the fact that an author can naturally have a constellation of knowledge that draws on an almost ‘infinite number of possibilities’. The same applies to the interlocutor. In purely abstract terms, the number of possible combinations is ‘virtually infinite’ due to the assumptions about the properties Author 1 and Interlocutor 2, which ultimately makes the question of ‘normality’ at the abstract level undecidable.
However, since both authors and interlocutors are not spherical beings from some abstract angle of possibilities, but are usually ‘concrete people’ with a ‘concrete history’ in a ‘concrete life-world’ at a ‘specific historical time’, the quasi-infinite abstract space of possibilities is narrowed down to a finite, manageable set of concretes. Yet, even these can still be considerably large when related to two specific individuals. Which person, with their life experience from which area, should now be taken as the ‘norm’ for ‘normal communication’?
It seems more likely that individual people are somehow ‘typified’, for example, by age and learning history, although a ‘learning history’ may not provide a clear picture either. Graduates from the same school can — as we know — possess very different knowledge afterwards, even though commonalities may be ‘minimally typical’.
Overall, the approach based on the characteristics of the author and the interlocutor does not seem to provide really clear criteria for a norm, even though a specification such as ‘the humanistic high school in Hadamar (a small German town) 1960 – 1968’ would suggest rudimentary commonalities.
One could now try to include the further characteristics of Author 2-7 and Interlocutor 3-8 in the considerations, but the ‘construction of normal communication’ seems to lead more and more into an unclear space of possibilities based on the assumptions of Author 1 and Interlocutor 2.
What does this mean for the typification of communication as ‘propaganda’? Isn’t ultimately every communication also a form of propaganda, or is there a possibility to sufficiently accurately characterize the form of ‘propaganda’, although it does not seem possible to find a standard for ‘normal communication’? … or will a better characterization of ‘propaganda’ indirectly provide clues for ‘non-propaganda’?
TRUTH and MEANING: Language as Key
The spontaneous attempt to clarify the meaning of the term ‘propaganda’ to the extent that one gets a few constructive criteria for being able to characterize certain forms of communication as ‘propaganda’ or not, gets into ever ‘deeper waters’. Are there now ‘objective verifiable criteria’ that one can work with, or not? And: Who determines them?
Let us temporarily stick to working hypothesis 1, that we are dealing with an author who articulates a message for an interlocutor, and let us expand this working hypothesis by the following addition 1: such communication always takes place in a social context. This means that the perception and knowledge of the individual actors (author, interlocutor) can continuously interact with this social context or ‘automatically interacts’ with it. The latter is because we humans are built in such a way that our body with its brain just does this, without ‘us’ having to make ‘conscious decisions’ for it.[*1]
For this section, I would like to extend the previous working hypothesis 1 together with supplement 1 by a further working hypothesis 2 (localization of language) [*4]:
Every medium (language, sound, image, etc.) can contain a ‘potential meaning’.
When creating the media event, the ‘author’ may attempt to ‘connect’ possible ‘contents’ that are to be ‘conveyed’ by him with the medium (‘putting into words/sound/image’, ‘encoding’, etc.). This ‘assignment’ of meaning occurs both ‘unconsciously/automatically’ and ‘(partially) consciously’.
In perceiving the media event, the ‘interlocutor’ may try to assign a ‘possible meaning’ to this perceived event. This ‘assignment’ of meaning also happens both ‘unconsciously/automatically’ and ‘(partially) consciously’.
The assignment of meaning requires both the author and the interlocutor to have undergone ‘learning processes’ (usually years, many years) that have made it possible to link certain ‘events of the external world’ as well as ‘internal states’ with certain media events.
The ‘learning of meaning relationships’ always takes place in social contexts, as a media structure meant to ‘convey meaning’ between people belongs to everyone involved in the communication process.
Those medial elements that are actually used for the ‘exchange of meanings’ all together form what is called a ‘language’: the ‘medial elements themselves’ form the ‘surface structure’ of the language, its ‘sign dimension’, and the ‘inner states’ in each ‘actor’ involved, form the ‘individual-subjective space of possible meanings’. This inner subjective space comprises two components: (i) the internally available elements as potential meaning content and (ii) a dynamic ‘meaning relationship’ that ‘links’ perceived elements of the surface structure and the potential meaning content.
To answer the guiding question of whether one can “characterize certain forms of communication as ‘propaganda’ or not,” one needs ‘objective, verifiable criteria’ on the basis of which a statement can be formulated. This question can be used to ask back whether there are ‘objective criteria’ in ‘normal everyday dialogue’ that we can use in everyday life to collectively decide whether a ‘claimed fact’ is ‘true’ or not; in this context, the word ‘true’ is also used. Can this be defined a bit more precisely?
For this I propose an additional working hypotheses 3:
At least two actors can agree that a certain meaning, associated with the media construct, exists as a sensibly perceivable fact in such a way that they can agree that the ‘claimed fact’ is indeed present. Such a specific occurrence should be called ‘true 1’ or ‘Truth 1.’ A ‘specific occurrence’ can change at any time and quickly due to the dynamics of the real world (including the actors themselves), for example: the rain stops, the coffee cup is empty, the car from before is gone, the empty sidewalk is occupied by a group of people, etc.
At least two actors can agree that a certain meaning, associated with the media construct, is currently not present as a real fact. Referring to the current situation of ‘non-occurrence,’ one would say that the statement is ‘false 1’; the claimed fact does not actually exist contrary to the claim.
At least two actors can agree that a certain meaning, associated with the media construct, is currently not present, but based on previous experience, it is ‘quite likely’ to occur in a ‘possible future situation.’ This aspect shall be called ‘potentially true’ or ‘true 2’ or ‘Truth 2.’ Should the fact then ‘actually occur’ at some point in the future, Truth 2 would transform into Truth 1.
At least two actors can agree that a certain meaning associated with the media construct does not currently exist and that, based on previous experience, it is ‘fairly certain that it is unclear’ whether the intended fact could actually occur in a ‘possible future situation’. This aspect should be called ‘speculative true’ or ‘true 3’ or ‘truth 3’. Should the situation then ‘actually occur’ at some point, truth 3 would change into truth 1.
At least two actors can agree that a certain meaning associated with the medial construct does not currently exist, and on the basis of previous experience ‘it is fairly certain’ that the intended fact could never occur in a ‘possible future situation’. This aspect should be called ‘speculative false’ or ‘false 2’.
A closer look at these 5 assumptions of working hypothesis 3 reveals that there are two ‘poles’ in all these distinctions, which stand in certain relationships to each other: on the one hand, there are real facts as poles, which are ‘currently perceived or not perceived by all participants’ and, on the other hand, there is a ‘known meaning’ in the minds of the participants, which can or cannot be related to a current fact. This results in the following distribution of values:
REAL FACTs
Relationship to Meaning
Given
1
Fits (true 1)
Given
2
Doesn’t fit (false 1)
Not given
3
Assumed, that it will fit in the future (true 2)
Not given
4
Unclear, whether it would fit in the future (true 3)
Not given
5
Assumed, that it would not fit in the future (false 2)
In this — still somewhat rough — scheme, ‘the meaning of thoughts’ can be qualified in relation to something currently present as ‘fitting’ or ‘not fitting’, or in the absence of something real as ‘might fit’ or ‘unclear whether it can fit’ or ‘certain that it cannot fit’.
However, it is important to note that these qualifications are ‘assessments’ made by the actors based on their ‘own knowledge’. As we know, such an assessment is always prone to error! In addition to errors in perception [*5], there can be errors in one’s own knowledge [*6]. So contrary to the belief of an actor, ‘true 1’ might actually be ‘false 1’ or vice versa, ‘true 2’ could be ‘false 2’ and vice versa.
From all this, it follows that a ‘clear qualification’ of truth and falsehood is ultimately always error-prone. For a community of people who think ‘positively’, this is not a problem: they are aware of this situation and they strive to keep their ‘natural susceptibility to error’ as small as possible through conscious methodical procedures [*7]. People who — for various reasons — tend to think negatively, feel motivated in this situation to see only errors or even malice everywhere. They find it difficult to deal with their ‘natural error-proneness’ in a positive and constructive manner.
TRUTH and MEANING : Process of Processes
In the previous section, the various terms (‘true1,2’, ‘false 1,2’, ‘true 3’) are still rather disconnected and are not yet really located in a tangible context. This will be attempted here with the help of working hypothesis 4 (sketch of a process space).
FIGURE 1 Process : The process space in the real world and in thinking, including possible interactions
The basic elements of working hypothesis 4 can be characterized as follows:
There is the real world with its continuous changes, and within an actor which includes a virtual space for processes with elements such as perceptions, memories, and imagined concepts.
The link between real space and virtual space occurs through perceptual achievements that represent specific properties of the real world for the virtual space, in such a way that ‘perceived contents’ and ‘imagined contents’ are distinguishable. In this way, a ‘mental comparison’ of perceived and imagined is possible.
Changes in the real world do not show up explicitly but are manifested only indirectly through the perceivable changes they cause.
It is the task of ‘cognitive reconstruction’ to ‘identify’ changes and to describe them linguistically in such a way that it is comprehensible, based on which properties of a given state, a possible subsequent state can arise.
In addition to distinguishing between ‘states’ and ‘changes’ between states, it must also be clarified how a given description of change is ‘applied’ to a given state in such a way that a ‘subsequent state’ arises. This is called here ‘successor generation rule’ (symbolically: ⊢). An expression like Z ⊢V Z’ would then mean that using the successor generation rule ⊢ and employing the change rule V, one can generate the subsequent state Z’ from the state Z. However, more than one change rule V can be used, for example, ⊢{V1, V2, …, Vn} with the change rules V1, …, Vn.
When formulating change rules, errors can always occur. If certain change rules have proven successful in the past in derivations, one would tend to assume for the ‘thought subsequent state’ that it will probably also occur in reality. In this case, we would be dealing with the situation ‘true 2’. If a change rule is new and there are no experiences with it yet, we would be dealing with the ‘true 3’ case for the thought subsequent state. If a certain change rule has failed repeatedly in the past, then the case ‘false 2’ might apply.
The outlined process model also shows that the previous cases (1-5 in the table) only ever describe partial aspects. Suppose a group of actors manages to formulate a rudimentary process theory with many states and many change rules, including a successor generation instruction. In that case, it is naturally of interest how the ‘theory as a whole’‘proves itself’. This means that every ‘mental construction’ of a sequence of possible states according to the applied change rules under the assumption of the process theory must ‘prove itself’ in all cases of application for the theory to be said to be ‘generically true’. For example, while the case ‘true 1’ refers to only a single state, the case ‘generically true’ refers to ‘very many’ states, as many until an ‘end state’ is reached, which is supposed to count as a ‘target state’. The case ‘generically contradicted’ is supposed to occur when there is at least one sequence of generated states that keeps generating an end state that is false 1. As long as a process theory has not yet been confirmed as true 1 for an end state in all possible cases, there remains a ‘remainder of cases’ that are unclear. Then a process theory would be called ‘generically unclear’, although it may be considered ‘generically true’ for the set of cases successfully tested so far.
FIGURE 2 Process : The individual extended process space with an indication of the dimension ‘META-THINKING’ and ‘EVALUATION’.
If someone finds the first figure of the process room already quite ‘challenging’, they he will certainly ‘break into a sweat’ with this second figure of the ‘expanded process room’.
Everyone can check for himself that we humans have the ability — regardless of what we are thinking — to turn our thinking at any time back onto our own thinking shortly before, a kind of ‘thinking about thinking’. This opens up an ‘additional level of thinking’ – here called the ‘meta-level’ – on which we thinkers ‘thematize’ everything that is noticeable and important to us in the preceding thinking. [*8] In addition to ‘thinking about thinking’, we also have the ability to ‘evaluate’ what we perceive and think. These ‘evaluations’ are fueled by our ’emotions’ [*9] and ‘learned preferences’. This enables us to ‘learn’ with the help of our emotions and learned preferences: If we perform certain actions and suffer ‘pain’, we will likely avoid these actions next time. If we go to restaurant X to eat because someone ‘recommended’ it to us, and the food and/or service were really bad, then we will likely not consider this suggestion in the future. Therefore, our thinking (and our knowledge) can ‘make possibilities visible’, but it is the emotions that comment on what happens to be ‘good’ or ‘bad’ when implementing knowledge. But beware, emotions can also be mistaken, and massively so.[*10]
TRUTH AND MEANING – As a collective achievement
The previous considerations on the topic of ‘truth and meaning’ in the context of individual processes have outlined that and how ‘language’ plays a central role in enabling meaning and, based on this, truth. Furthermore, it was also outlined that and how truth and meaning must be placed in a dynamic context, in a ‘process model’, as it takes place in an individual in close interaction with the environment. This process model includes the dimension of ‘thinking’ (also ‘knowledge’) as well as the dimension of ‘evaluations’ (emotions, preferences); within thinking there are potentially many ‘levels of consideration’ that can relate to each other (of course they can also take place ‘in parallel’ without direct contact with each other (the unconnected parallelism is the less interesting case, however).
As fascinating as the dynamic emotional-cognitive structure within an individual actor can be, the ‘true power’ of explicit thinking only becomes apparent when different people begin to coordinate their actions by means of communication. When individual action is transformed into collective action in this way, a dimension of ‘society’ becomes visible, which in a way makes the ‘individual actors’ ‘forget’, because the ‘overall performance’ of the ‘collectively connected individuals’ can be dimensions more complex and sustainable than any one individual could ever realize. While a single person can make a contribution in their individual lifetime at most, collectively connected people can accomplish achievements that span many generations.
On the other hand, we know from history that collective achievements do not automatically have to bring about ‘only good’; the well-known history of oppression, bloody wars and destruction is extensive and can be found in all periods of human history.
This points to the fact that the question of ‘truth’ and ‘being good’ is not only a question for the individual process, but also a question for the collective process, and here, in the collective case, this question is even more important, since in the event of an error not only individuals have to suffer negative effects, but rather very many; in the worst case, all of them.
To be continued …
COMMENTS
[*0] The meaning of the terms ‘objective, verifiable’ will be explained in more detail below.
[*1] In a system-theoretical view of the ‘human body’ system, one can formulate the working hypothesis that far more than 99% of the events in a human body are not conscious. You can find this frightening or reassuring. I tend towards the latter, towards ‘reassurance’. Because when you see what a human body as a ‘system’ is capable of doing on its own, every second, for many years, even decades, then this seems extremely reassuring in view of the many mistakes, even gross ones, that we can make with our small ‘consciousness’. In cooperation with other people, we can indeed dramatically improve our conscious human performance, but this is only ever possible if the system performance of a human body is maintained. After all, it contains 3.5 billion years of development work of the BIOM on this planet; the building blocks of this BIOM, the cells, function like a gigantic parallel computer, compared to which today’s technical supercomputers (including the much-vaunted ‘quantum computers’) look so small and weak that it is practically impossible to express this relationship.
[*2] An ‘everyday language’ always presupposes ‘the many’ who want to communicate with each other. One person alone cannot have a language that others should be able to understand.
[*3] A meaning relation actually does what is mathematically called a ‘mapping’: Elements of one kind (elements of the surface structure of the language) are mapped to elements of another kind (the potential meaning elements). While a mathematical mapping is normally fixed, the ‘real meaning relation’ can constantly change; it is ‘flexible’, part of a higher-level ‘learning process’ that constantly ‘readjusts’ the meaning relation depending on perception and internal states.
[*4] The contents of working hypothesis 2 originate from the findings of modern cognitive sciences (neuroscience, psychology, biology, linguistics, semiotics, …) and philosophy; they refer to many thousands of articles and books. Working hypothesis 2 therefore represents a highly condensed summary of all this. Direct citation is not possible in purely practical terms.
[*5] As is known from research on witness statements and from general perception research, in addition to all kinds of direct perception errors, there are many errors in the ‘interpretation of perception’ that are largely unconscious/automated. The actors are normally powerless against such errors; they simply do not notice them. Only methodically conscious controls of perception can partially draw attention to these errors.
[*6] Human knowledge is ‘notoriously prone to error’. There are many reasons for this. One lies in the way the brain itself works. ‘Correct’ knowledge is only possible if the current knowledge processes are repeatedly ‘compared’ and ‘checked’ so that they can be corrected. Anyone who does not regularly check the correctness will inevitably confirm incomplete and often incorrect knowledge. As we know, this does not prevent people from believing that everything they carry around in their heads is ‘true’. If there is a big problem in this world, then this is one of them: ignorance about one’s own ignorance.
[*7] In the cultural history of mankind to date, it was only very late (about 500 years ago?) that a format of knowledge was discovered that enables any number of people to build up fact-based knowledge that, compared to all other known knowledge formats, enables the ‘best results’ (which of course does not completely rule out errors, but extremely minimizes them). This still revolutionary knowledge format has the name ’empirical theory’, which I have since expanded to ‘sustainable empirical theory’. On the one hand, we humans are the main source of ‘true knowledge’, but at the same time we ourselves are also the main source of ‘false knowledge’. At first glance, this seems like a ‘paradox’, but it has a ‘simple’ explanation, which at its root is ‘very profound’ (comparable to the cosmic background radiation, which is currently simple, but originates from the beginnings of the universe).
[*8] In terms of its architecture, our brain can open up any number of such meta-levels, but due to its concrete finiteness, it only offers a limited number of neurons for different tasks. For example, it is known (and has been experimentally proven several times) that our ‘working memory’ (also called ‘short-term memory’) is only limited to approx. 6-9 ‘units’ (whereby the term ‘unit’ must be defined depending on the context). So if we want to solve extensive tasks through our thinking, we need ‘external aids’ (sheet of paper and pen or a computer, …) to record the many aspects and write them down accordingly. Although today’s computers are not even remotely capable of replacing the complex thought processes of humans, they can be an almost irreplaceable tool for carrying out complex thought processes to a limited extent. But only if WE actually KNOW what we are doing!
[*9] The word ’emotion’ is a ‘collective term’ for many different phenomena and circumstances. Despite extensive research for over a hundred years, the various disciplines of psychology are still unable to offer a uniform picture, let alone a uniform ‘theory’ on the subject. This is not surprising, as much of the assumed emotions takes place largely ‘unconsciously’ or is only directly available as an ‘internal event’ in the individual. The only thing that seems to be clear is that we as humans are never ’emotion-free’ (this also applies to so-called ‘cool’ types, because the apparent ‘suppression’ or ‘repression’ of emotions is itself part of our innate emotionality).
[*10] Of course, emotions can also lead us seriously astray or even to our downfall (being wrong about other people, being wrong about ourselves, …). It is therefore not only important to ‘sort out’ the factual things in the world in a useful way through ‘learning’, but we must also actually ‘keep an eye on our own emotions’ and check when and how they occur and whether they actually help us. Primary emotions (such as hunger, sex drive, anger, addiction, ‘crushes’, …) are selective, situational, can develop great ‘psychological power’ and thus obscure our view of the possible or very probable ‘consequences’, which can be considerably damaging for us.
[*11] The term ‘narrative’ is increasingly used today to describe the fact that a group of people use a certain ‘image’, a certain ‘narrative’ in their thinking for their perception of the world in order to be able to coordinate their joint actions. Ultimately, this applies to all collective action, even for engineers who want to develop a technical solution. In this respect, the description in the German Wikipedia is a bit ‘narrow’: https://de.wikipedia.org/wiki/Narrativ_(Sozialwissenschaften)
REFERENCES
The following sources are just a tiny selection from the many hundreds, if not thousands, of articles, books, audio documents and films on the subject. Nevertheless, they may be helpful for an initial introduction. The list will be expanded from time to time.
[1a] Propaganda, in the German Wikipedia https://de.wikipedia.org/wiki/Propaganda
[1b] Propaganda in the English Wikipedia : https://en.wikipedia.org/wiki/Propaganda /*The English version appears more systematic, covers larger periods of time and more different areas of application */
Translation: This text is a translation from the German Version into English with the aid of the software deepL.com as well as with chatGPT4, moderated by the author. The style of the two translators is different. The author is not good enough to classify which translator is ‘better’.
CONTEXT
This text is the outcome of a conference held at the Technical University of Darmstadt (Germany) with the title: Discourses of disruptive digital technologies using the example of AI text generators ( https://zevedi.de/en/topics/ki-text-2/ ). A German version of this article will appear in a book from de Gruyter as open access in the beginning of 2024.
Collective human-machine intelligence and text generation. A transdisciplinary analysis.
Abstract
Based on the conference theme “AI – Text and Validity. How do AI text generators change scientific discourse?” as well as the special topic “Collective human-machine intelligence using the example of text generation”, the possible interaction relationship between text generators and a scientific discourse will be played out in a transdisciplinary analysis. For this purpose, the concept of scientific discourse will be specified on a case-by-case basis using the text types empirical theory as well as sustained empirical theory in such a way that the role of human and machine actors in these discourses can be sufficiently specified. The result shows a very clear limitation of current text generators compared to the requirements of scientific discourse. This leads to further fundamental analyses on the example of the dimension of time with the phenomenon of the qualitatively new as well as on the example of the foundations of decision-making to the problem of the inherent bias of the modern scientific disciplines. A solution to the inherent bias as well as the factual disconnectedness of the many individual disciplines is located in the form of a new service of transdisciplinary integration by re-activating the philosophy of science as a genuine part of philosophy. This leaves the question open whether a supervision of the individual sciences by philosophy could be a viable path? Finally, the borderline case of a world in which humans no longer have a human counterpart is pointed out.
AUDIO: Keyword Sound
STARTING POINT
This text takes its starting point from the conference topic “AI – Text and Validity. How do AI text generators change scientific discourses?” and adds to this topic the perspective of a Collective Human-Machine Intelligence using the example of text generation. The concepts of text and validity, AI text generators, scientific discourse, and collective human-machine intelligence that are invoked in this constellation represent different fields of meaning that cannot automatically be interpreted as elements of a common conceptual framework.
TRANSDISCIPLINARY
In order to be able to let the mentioned terms appear as elements in a common conceptual framework, a meta-level is needed from which one can talk about these terms and their possible relations to each other. This approach is usually located in the philosophy of science, which can have as its subject not only single terms or whole propositions, but even whole theories that are compared or possibly even united. The term transdisciplinary [1] , which is often used today, is understood here in this philosophy of science understanding as an approach in which the integration of different concepts is redeemed by introducing appropriate meta-levels. Such a meta-level ultimately always represents a structure in which all important elements and relations can gather.
[1] Jürgen Mittelstraß paraphrases the possible meaning of the term transdisciplinarity as a “research and knowledge principle … that becomes effective wherever a solely technical or disciplinary definition of problem situations and problem solutions is not possible…”. Article Methodological Transdisciplinarity, in LIFIS ONLINE, www.leibniz-institut.de, ISSN 1864-6972, p.1 (first published in: Technology Assessment – Theory and Practice No.2, 14.Jg., June 2005, 18-23). In his text Mittelstrass distinguishes transdisciplinarity from the disciplinary and from the interdisciplinary. However, he uses only a general characterization of transdisciplinarity as a research guiding principle and scientific form of organization. He leaves the concrete conceptual formulation of transdisciplinarity open. This is different in the present text: here the transdisciplinary theme is projected down to the concreteness of the related terms and – as is usual in philosophy of science (and meta-logic) – realized by means of the construct of meta-levels.
SETTING UP A STRUCTURE
Here the notion of scientific discourse is assumed as a basic situation in which different actors can be involved. The main types of actors considered here are humans, who represent a part of the biological systems on planet Earth as a kind of Homo sapiens, and text generators, which represent a technical product consisting of a combination of software and hardware.
It is assumed that humans perceive their environment and themselves in a species-typical way, that they can process and store what they perceive internally, that they can recall what they have stored to a limited extent in a species-typical way, and that they can change it in a species-typical way, so that internal structures can emerge that are available for action and communication. All these elements are attributed to human cognition. They are working partially consciously, but largely unconsciously. Cognition also includes the subsystem language, which represents a structure that on the one hand is largely species-typically fixed, but on the other hand can be flexibly mapped to different elements of cognition.
In the terminology of semiotics [2] the language system represents a symbolic level and those elements of cognition, on which the symbolic structures are mapped, form correlates of meaning, which, however, represent a meaning only insofar as they occur in a mapping relation – also called meaning relation. A cognitive element as such does not constitute meaning in the linguistic sense. In addition to cognition, there are a variety of emotional factors that can influence both cognitive processes and the process of decision-making. The latter in turn can influence thought processes as well as action processes, consciously as well as unconsciously. The exact meaning of these listed structural elements is revealed in a process model [3] complementary to this structure.
[2] See, for example, Winfried Nöth: Handbuch der Semiotik. 2nd, completely revised edition. Metzler, Stuttgart/Weimar, 2000
[3] Such a process model is presented here only in partial aspects.
SYMBOLIC COMMUNICATION SUB-PROCESS
What is important for human actors is that they can interact in the context of symbolic communication with the help of both spoken and written language. Here it is assumed – simplistically — that spoken language can be mapped sufficiently accurately into written language, which in the standard case is called text. It should be noted that texts only represent meaning if the text producers involved, as well as the text recipients, have a meaning function that is sufficiently similar. For texts by human text producers it is generally true that, with respect to concrete situations, statements as part of texts can be qualified under agreed conditions as now matching the situation (true) or as now not now matching the situation (false). However, a now-true can become a now-not-true again in the next moment and vice versa.
This dynamic fact refers to the fact that a punctual occurrence or non-occurrence of a statement is to be distinguished from a structural occurrence/ non-occurrence of a statement, which speaks about occurrence/ non-occurrence in context. This refers to relations which are only indirectly apparent in the context of a multitude of individual events, if one considers chains of events over many points in time. Finally, one must also consider that the correlates of meaning are primarily located within the human biological system. Meaning correlates are not automatically true as such, but only if there is an active correspondence between a remembered/thought/imagined meaning correlate and an active perceptual element, where an intersubjective fact must correspond to the perceptual element. Just because someone talks about a rabbit and the recipient understands what a rabbit is, this does not mean that there is also a real rabbit which the recipient can perceive.
TEXT-GENERATORS
When distinguishing between the two different types of actors – here biological systems of the type Homo sapiens and there technical systems of the type text-generators – a first fundamental asymmetry immediately strikes the eye: so-called text-generators are entities invented and built by humans; furthermore, it is humans who use them, and the essential material used by text-generators are furthermore texts, which are considered human cultural property, created and used by humans for a variety of discourse types, here restricted to scientific discourse.
In the case of text generators, let us first note that we are dealing with machines that have input and output, a minimal learning capability, and whose input and output can process text-like objects. Insofar as text generators can process text-like objects as input and process them again as output, an exchange of texts between humans and text generators can take place in principle.
At the current state of development (September 2023), text generators do not yet have an independent real-world perception within the scope of their input, and the entire text generator system does not yet have such processes as those that enable species-typical cognitions in humans. Furthermore, a text generator does not yet have a meaning function as it is given with humans.
From this fact it follows automatically that text generators cannot decide about selective or structural correctness/not correctness in the case of statements of a text. In general, they do not have their own assignment of meaning as with humans. Texts generated by text generators only have a meaning if a human as a recipient automatically assigns a meaning to a text due to his species-typical meaning relation, because this is the learned behavior of a human. In fact, the text generator itself has never assigned any meaning to the generated text. Salopp one could also formulate that a technical text generator works like a parasite: it collects texts that humans have generated, rearranges them combinatorially according to formal criteria for the output, and for the receiving human a meaning event is automatically triggered by the text in the human, which does not exist anywhere in the text generator. Whether this very restricted form of text generation is now in any sense detrimental or advantageous for the type of scientific discourse (with texts), that is to be examined in the further course.
SCIENTIFIC DISCOURSE
There is no clear definition for the term scientific discourse. This is not surprising, since an unambiguous definition presupposes that there is a fully specified conceptual framework within which terms such as discourse and scientific can be clearly delimited. However, in the case of a scientific enterprise with a global reach, broken down into countless individual disciplines, this does not seem to be the case at present (Sept 2023). For the further procedure, we will therefore fall back on core ideas of the discussion in philosophy of science since the 20th century [4]and we will introduce working hypotheses on the concept of empirical theory as well as sustainable empirical theory, so that a working hypothesis on the concept of scientific discourse will be possible, which has a minimal sharpness.
[4] A good place to start may be: F. Suppe, Editor. The Structure of Scientific Theories. University of Illinois Press, Urbana, 2 edition, 1979.
EMPIRICAL THEORY
The following assumptions are made for the notion of an empirical theory:
an empirical theory is basically a text, written in a language that all participants understand.
one part of the theory contains a description of an initial situation, the statements of which can be qualified by the theory users as now matching (true) or now not matching (false).
another part of the theory contains a text that lists all changes that, to the knowledge of the participants, occur in the context of the initial situation and can change parts of the initial situation.
changes in the initial situation are expressed by replacing certain statements of the initial situation with other statements. The resulting new text replaces the previous text.
through the possibility of generating new initial situations, there is the possibility of making predictions (forming expectations) by applying rules of change to an applicable initial situation several times (at least once) in succession. The texts that are generated in each case induce in the minds of the participants, on the basis of the available meaning functions, the idea of a situation that is demanded to become qualified as now matching with intersubjective reality, should it occur. In the case of occurrence, the situation must correspond to the conception in the mind via perception. Whether such a correspondence can be established, after how long time and to what extent, this is basically open in the presence of the prediction making (the formation of an expectation) (autonomy of the object!).
SCIENTIFIC DISCOURSE NEW
Even before the introduction of the notion of a sustainable empirical theory, the notion of an empirical theory just introduced allows for initial statements about what a scientific discourse could or should be. It is assumed here that the participants in a scientific discourse exchange their opinions about the world in the form of texts, all of which meet the requirements of an empirical theory.
WITH HUMANS
Insofar as the participants in the discourse are human beings, we know that they have basic species-typical abilities to generate subjective meanings by means of language, which can be decided as now true or now not true by reference to a real situation.
WITH TEXT GENERATORS
Insofar as the discourse participants would be text generators lacking these elementary skills (meaning, reality reference), they drop out as independent actors for a scientific discourse. To illustrate this, here is a self-assessment of chatGPT4, a current text generator:
ChatGPT
Yes, your summary of our previous dialogue is accurate based on the points you’ve listed:
I cannot read a book in the same way a human does, meaning I don’t interpret or comprehend in the same manner.
My knowledge is up to September 2021, which means that I might not be aware of events, advancements, or publications after that point.
My “learning” is different from human learning. I don’t learn from new experiences or information after my last update. Instead, I generate responses based on patterns in the data I was trained on.
I don’t cite individual sources in my responses. I provide information based on the patterns recognized during my training.
Responses I give can vary slightly even if the same question is posed multiple times.
I can’t directly attribute my statements to specific, individual sources.
The specifics about my training data and the processes that determine my responses are not transparently provided in each interaction.
You’ve captured the essence of our prior conversation well. If you have further questions or need clarifications on any of these points, please let me know. [5]
[5] This text is from a chat experiment conducted by the author with chatGPT4 on August 31, 2023. The citation can be found in: Gerd Doeben-Henisch, CONTINUE EXPERIMENT WITH CHATGPT4: Science, Empirical Science, Philosophy of Science, uffmm, Integrating Engineering and the Human Factor, eJournal uffmm.org ISSN 2567-6458, 8/31/2023 in [https://www.uffmm.org/2023/08/31/continue-experiment-with-chatgpt4-science-empirical-science-philosophy-of-science/ ] (accessed 9/27/2023).
The question then arises whether (current) text generators, despite their severely limited capabilities, could nevertheless contribute to scientific discourse, and what this contribution means for human participants. Since text generators fail for the hard scientific criteria (decidable reality reference, reproducible predictive behavior, separation of sources), one can only assume a possible contribution within human behavior: since humans can understand and empirically verify texts, they would in principle be able to rudimentarily classify a text from a text generator within their considerations.
For hard theory work, these texts would not be usable, but due to their literary-associative character across a very large body of texts, the texts of text generators could – in the positive case – at least introduce thoughts into the discourse through texts as stimulators via the detour of human understanding, which would stimulate the human user to examine these additional aspects to see if they might be important for the actual theory building after all. In this way, the text generators would not participate independently in the scientific discourse, but they would indirectly support the knowledge process of the human actors as aids to them.[6]
[6] A detailed illustration of this associative role of a text generator can also be found in (Doeben-Henisch, 2023) on the example of the term philosophy of science and on the question of the role of philosophy of science.
CHALLENGE DECISION
The application of an empirical theory can – in the positive case — enable an expanded picture of everyday experience, in that, related to an initial situation, possible continuations (possible futures) are brought before one’s eyes. For people who have to shape their own individual processes in their respective everyday life, however, it is usually not enough to know only what one can do.Rather, everyday life requires deciding in each case which continuation to choose, given the many possible continuations. In order to be able to assert themselves in everyday life with as little effort as possible and with – at least imagined – as little risk as possible, people have adopted well-rehearsed behavior patterns for as many everyday situations as possible, which they follow spontaneously without questioning them anew each time. These well-rehearsed behavior patterns include decisions that have been made. Nevertheless, there are always situations in which the ingrained automatisms have to be interrupted in order to consciously clarify the question for which of several possibilities one wants to decide.
The example of an individual decision-maker can also be directly applied to the behavior of larger groups. Normally, even more individual factors play a role here, all of which have to be integrated in order to reach a decision. However, the characteristic feature of a decision situation remains the same: whatever knowledge one may have at the time of decision, when alternatives are available, one has to decide for one of many alternatives without any further, additional knowledge at this point. Empirical science cannot help here [7]: it is an indisputable basic ability of humans to be able to decide.
So far, however, it remains rather hidden in the darkness of not knowing oneself, which ultimately leads to deciding for one and not for the other. Whether and to what extent the various cultural patterns of decision-making aids in the form of religious, moral, ethical or similar formats actually form or have formed a helpful role for projecting a successful future appears to be more unclear than ever.[8]
[7] No matter how much detail she can contribute about the nature of decision-making processes.
[8] This topic is taken up again in the following in a different context and embedded there in a different solution context.
SUSTAINABLE EMPIRICAL THEORY
Through the newly flared up discussion about sustainability in the context of the United Nations, the question of prioritizing action relevant to survival has received a specific global impulse. The multitude of aspects that arise in this discourse context [9] are difficult, if not impossible, to classify into an overarching, consistent conceptual framework.
[9] For an example see the 17 development goals: [https://unric.org/de/17ziele/] (Accessed: September 27, 2023)
A rough classification of development goals into resource-oriented and actor-oriented can help to make an underlying asymmetry visible: a resource problem only exists if there are biological systems on this planet that require a certain configuration of resources (an ecosystem) for their physical existence. Since the physical resources that can be found on planet Earth are quantitatively limited, it is possible, in principle, to determine through thought and science under what conditions the available physical resources — given a prevailing behavior — are insufficient. Added to this is the factor that biological systems, by their very existence, also actively alter the resources that can be found.
So, if there should be a resource problem, it is exclusively because the behavior of the biological systems has led to such a biologically caused shortage. Resources as such are neither too much, nor too little, nor good, nor bad. If one accepts that the behavior of biological systems in the case of the species Homo sapiens can be controlled by internal states, then the resource problem is primarily a cognitive and emotional problem: Do we know enough? Do we want the right thing? And these questions point to motivations beyond what is currently knowable. Is there a dark spot in the human self-image here?
On the one hand, this questioning refers to the driving forces for a current decision beyond the possibilities of the empirical sciences (trans-empirical, meta-physical, …), but on the other hand, this questioning also refers to the center/ core of human competence. This motivates to extend the notion of empirical theory to the notion of a sustainable empirical theory. This does not automatically solve the question of the inner mechanism of a value decision, but it systematically classifies the problem. The problem thus has an official place. The following formulation is suggested as a characterization for the concept of a sustainable empirical theory:
a sustainable empirical theory contains an empirical theory as its core.
besides the parts of initial situation, rules of change and application of rules of change, a sustainable theory also contains a text with a list of such situations, which are considered desirable for a possible future (goals, visions, …).
under the condition of goals, it is possible to minimally compare each current situation with the available goals and thereby indicate the degree of goal achievement.
Stating desired goals says nothing about how realistic or promising it is to pursue those goals. It only expresses that the authors of this theory know these goals and consider them optimal at the time of theory creation. [10] The irrationality of chosen goals is in this way officially included in the domain of thought of the theory creators and in this way facilitates the extension of the rational to the irrational without already having a real solution. Nobody can exclude that the phenomenon of bringing forth something new, respectively of preferring a certain point of view in comparison to others, can be understood further and better in the future.
[10] Something can only be classified as optimal if it can be placed within an overarching framework, which allows for positioning on a scale. This refers to a minimal cognitive model as an expression of rationality. However, the decision itself takes place outside of such a rational model; in this sense, the decision as an independent process is pre-rational.
EXTENDED SCIENTIFIC DISCOURSE
If one accepts the concept of a sustainable empirical theory, then one can extend the concept of a scientific discourse in such a way that not only texts that represent empirical theories can be introduced, but also those texts that represent sustainable empirical theories with their own goals. Here too, one can ask whether the current text generators (September 2023) can make a constructive contribution. Insofar as a sustainable empirical theory contains an empirical theory as a hard core, the preceding observations on the limitations of text generators apply. In the creative part of the development of an empirical theory, they can contribute text fragments through their associative-combinatorial character based on a very large number of documents, which may inspire the active human theory authors to expand their view. But what about that part that manifests itself in the selection of possible goals? At this point, one must realize that it is not about any formulations, but about those that represent possible solution formulations within a systematic framework; this implies knowledge of relevant and verifiable meaning structures that could be taken into account in the context of symbolic patterns. Text generators fundamentally do not have these abilities. But it is – again – not to be excluded that their associative-combinatorial character based on a very large number of documents can still provide one or the other suggestion.
In retrospect of humanity’s history of knowledge, research, and technology, it is suggested that the great advances were each triggered by something really new, that is, by something that had never existed before in this form. The praise for Big Data, as often heard today, represents – colloquially speaking — exactly the opposite: The burial of the new by cementing the old.[11]
[11] A prominent example of the naive fixation on the old as a standard for what is right can be seen, for example, in the book by Seth Stephens-Davidowitz, Don’t Trust Your Gut. Using Data Instead of Instinct To Make Better Choices, London – Oxford New York et al., 2022.
EXISTENTIALLY NEW THROUGH TIME
The concept of an empirical theory inherently contains the element of change, and even in the extended concept of a sustainable empirical theory, in addition to the fundamental concept of change, there is the aspect of a possible goal. A possible goal itself is not a change, but presupposes the reality of changes! The concept of change does not result from any objects but is the result of a brain performance, through which a current present is transformed into a partially memorable state (memory contents) by forming time slices in the context of perception processes – largely unconsciously. These produced memory contents have different abstract structures, are networked differently with each other, and are assessed in different ways. In addition, the brain automatically compares current perceptions with such stored contents and immediately reports when a current perception has changed compared to the last perception contents. In this way, the phenomenon of change is a fundamental cognitive achievement of the brain, which thus makes the character of a feeling of time available in the form of a fundamental process structure. The weight of this property in the context of evolution is hardly to be overestimated, as time as such is in no way perceptible.
[12] The modern invention of machines that can generate periodic signals (oscillators, clocks) has been successfully integrated into people’s everyday lives. However, the artificially (technically) producible time has nothing to do with the fundamental change found in reality. Technical time is a tool that we humans have invented to somehow structure the otherwise amorphous mass of a phenomenon stream. Since structure itself shows in the amorphous mass, which manifest obviously for all, repeating change cycles (e.g., sunrise and sunset, moonrise and moonset, seasons, …), a correlation of technical time models and natural time phenomena was offered. From the correlations resulting here, however, one should not conclude that the amorphous mass of the world phenomenon stream actually behaves according to our technical time model. Einstein’s theory of relativity at least makes us aware that there can be various — or only one? — asymmetries between technical time and world phenomenon stream.
Assuming this fundamental sense of time in humans, one can in principle recognize whether a current phenomenon, compared to all preceding phenomena, is somehow similar or markedly different, and in this sense indicates something qualitatively new.[13]
[13] Ultimately, an individual human only has its individual memory contents available for comparison, while a collective of people can in principle consult the set of all records. However, as is known, only a minimal fraction of the experiential reality is symbolically transformed.
By presupposing the concept of directed time for the designation of qualitatively new things, such a new event is assigned an information value in the Shannonian sense, as well as the phenomenon itself in terms of linguistic meaning, and possibly also in the cognitive area: relative to a spanned knowledge space, the occurrence of a qualitatively new event can significantly strengthen a theoretical assumption. In the latter case, the cognitive relevance may possibly mutate to a sustainable relevance if the assumption marks a real action option that could be important for further progress. In the latter case, this would provoke the necessity of a decision: should we adopt this action option or not? Humans can accomplish the finding of qualitatively new things. They are designed for it by evolution. But what about text generators?
Text generators so far do not have a sense of time comparable to that of humans. Their starting point would be texts that are different, in such a way that there is at least one text that is the most recent on the timeline and describes real events in the real world of phenomena. Since a text generator (as of September 2023) does not yet have the ability to classify texts regarding their applicability/non-applicability in the real world, its use would normally end here. Assuming that there are people who manually perform this classification for a text generator [14] (which would greatly limit the number of possible texts), then a text generator could search the surface of these texts for similar patterns and, relative to them, for those that cannot be compared. Assuming that the text generator would find a set of non-comparable patterns in acceptable time despite a massive combinatorial explosion, the problem of semantic qualification would arise again: which of these patterns can be classified as an indication of something qualitatively new? Again, humans would have to become active.
[14] Such support of machines by humans in the field of so-called intelligent algorithms has often been applied (and is still being applied today, see: [https://www.mturk.com/] (Accessed: September 27, 2023)), and is known to be very prone to errors.
As before, the verdict is mixed: left to itself, a text generator will not be able to solve this task, but in cooperation with humans, it may possibly provide important auxiliary services, which could ultimately be of existential importance to humans in search of something qualitatively new despite all limitations.
THE IMMANENT PREJUDICE OF THE SCIENCES
A prejudice is known to be the assessment of a situation as an instance of a certain pattern, which the judge assumes applies, even though there are numerous indications that the assumed applicability is empirically false. Due to the permanent requirement of everyday life that we have to make decisions, humans, through their evolutionary development, have the fundamental ability to make many of their everyday decisions largely automatically. This offers many advantages, but can also lead to conflicts.
Daniel Kahneman introduced in this context in his book [15] the two terms System 1 and System 2 for a human actor. These terms describe in his concept of a human actor two behavioral complexes that can be distinguished based on some properties.[16] System 1 is set by the overall system of human actor and is characterized by the fact that the actor can respond largely automatically to requirements by everyday life. The human actor has automatic answers to certain stimuli from his environment, without having to think much about it. In case of conflicts within System 1 or from the perspective of System 2, which exercises some control over the appropriateness of System 1 reactions in a certain situation in conscious mode, System 2 becomes active. This does not have automatic answers ready, but has to laboriously work out an answer to a given situation step by step. However, there is also the phenomenon that complex processes, which must be carried out frequently, can be automated to a certain extent (bicycling, swimming, playing a musical instrument, learning language, doing mental arithmetic, …). All these processes are based on preceding decisions that encompass different forms of preferences. As long as these automated processes are appropriate in the light of a certain rational model, everything seems to be OK. But if the corresponding model is distorted in any sense, then it would be said that these models carry a prejudice.
[15] Daniel Kahnemann, Thinking Fast and Slow, Pinguin Boooks Random House, UK, 2012 (zuerst 2011)
[16] See the following Chapter 1 in Part 1 of (Kahnemann, 2012, pages 19-30).
In addition to the countless examples that Kahneman himself cites in his book to show the susceptibility of System 1 to such prejudices, it should be pointed out here that the model of Kahneman himself (and many similar models) can carry a prejudice that is of a considerably more fundamental nature. The division of the behavioral space of a human actor into a System 1 and 2, as Kahneman does, obviously has great potential to classify many everyday events. But what about all the everyday phenomena that fit neither the scheme of System 1 nor the scheme of System 2?
In the case of making a decision, System 1 comments that people – if available – automatically call up and execute an available answer. Only in the case of conflict under the control of System 2 can there be lengthy operations that lead to other, new answers.
In the case of decisions, however, it is not just about reacting at all, but there is also the problem of choosing between known possibilities or even finding something new because the known old is unsatisfactory.
Established scientific disciplines have their specific perspectives and methods that define areas of everyday life as a subject area. Phenomena that do not fit into this predefined space do not occur for the relevant discipline – methodically conditioned. In the area of decision-making and thus the typical human structures, there are not a few areas that have so far not found official entry into a scientific discipline. At a certain point in time, there are ultimately many, large phenomenon areas that really exist, but methodically are not present in the view of individual sciences. For a scientific investigation of the real world, this means that the sciences, due to their immanent exclusions, are burdened with a massive reservation against the empirical world. For the task of selecting suitable sustainable goals within the framework of sustainable science, this structurally conditioned fact can be fatal. Loosely formulated: under the banner of actual science, a central principle of science – the openness to all phenomena – is simply excluded, so as not to have to change the existing structure.
For this question of a meta-reflection on science itself, text generators are again only reduced to possible abstract text delivery services under the direction of humans.
SUPERVISION BY PHILOSOPHY
The just-described fatal dilemma of all modern sciences is to be taken seriously, as without an efficient science, sustainable reflection on the present and future cannot be realized in the long term. If one agrees that the fatal bias of science is caused by the fact that each discipline works intensively within its discipline boundaries, but does not systematically organize communication and reflection beyond its own boundaries with a view to other disciplines as meta-reflection, the question must be answered whether and how this deficit can be overcome.
There is only one known answer to this question: one must search for that conceptual framework within which these guiding concepts can meaningfully interact both in their own right and in their interaction with other guiding concepts, starting from those guiding concepts that are constitutive for the individual disciplines.
This is genuinely the task of philosophy, concretized by the example of the philosophy of science. However, this would mean that each individual science would have to use a sufficiently large part of its capacities to make the idea of the one science in maximum diversity available in a real process.
For the hard conceptual work hinted at here, text generators will hardly be able to play a central role.
COLLECTIVE INTELLIGENCE
Since so far there is no concept of intelligence in any individual science that goes beyond a single discipline, it makes little sense at first glance to apply the term intelligence to collectives. However, looking at the cultural achievements of humanity as a whole, and here not least with a view to the used language, it is undeniable that a description of the performance of an individual person, its individual performance, is incomplete without reference to the whole.
So, if one tries to assign an overarching meaning to the letter combination intelligence, one will not be able to avoid deciphering this phenomenon of the human collective in the form of complex everyday processes in a no less complex dynamic world, at least to the extent that one can identify a somewhat corresponding empirical something for the letter combination intelligence, with which one could constitute a comprehensible meaning.
Of course, this term should be scalable for all biological systems, and one would have to have a comprehensible procedure that allows the various technical systems to be related to this collective intelligence term in such a way that direct performance comparisons between biological and technical systems would be possible.[17]
[17] The often quoted and popular Turing Test (See: Alan M. Turing: Computing Machinery and Intelligence. In: Mind. Volume LIX, No. 236, 1950, 433–460, [doi:10.1093/mind/LIX.236.433] (Accessed: Sept 29, 2023) in no way meets the methodological requirements that one would have to adhere to if one actually wanted to come to a qualified performance comparison between humans and machines. Nevertheless, the basic idea of Turing in his meta-logical text from 1936, published in 1937 (see: A. M. Turing: On Computable Numbers, with an Application to the Entscheidungsproblem. In: Proceedings of the London Mathematical Society. s2-42. Volume, No. 1, 1937, 230–265 [doi:10.1112/plms/s2-42.1.230] (Accessed: Sept 29, 2023) seems to be a promising starting point, since he, in trying to present an alternative formulation to Kurt Gödel’s (1931) proof on the undecidability of arithmetic, leads a meta-logical proof, and in this context Turing introduces the concept of a machine that was later called Universal Turing Machine.
Already in this proof approach, it can be seen how Turing transforms the phenomenon of a human bookkeeper at a meta-level into a theoretical concept, by means of which he can then meta-logically examine the behavior of this bookkeeper in a specific behavioral space. His meta-logical proof not only confirmed Gödel’s meta-logical proof, but also indirectly indicates how ultimately any phenomenal complexes can be formalized on a meta-level in such a way that one can then argue formally demanding with it.
CONCLUSION STRUCTURALLY
The idea of philosophical supervision of the individual sciences with the goal of a concrete integration of all disciplines into an overall conceptual structure seems to be fundamentally possible from a philosophy of science perspective based on the previous considerations. From today’s point of view, specific phenomena claimed by individual disciplines should no longer be a fundamental obstacle for a modern theory concept. This would clarify the basics of the concept of Collective Intelligence and it would surely be possible to more clearly identify interactions between human collective intelligence and interactive machines. Subsequently, the probability would increase that the supporting machines could be further optimized, so that they could also help in more demanding tasks.
CONCLUSION SUBJECTIVELY
Attempting to characterize the interactive role of text generators in a human-driven scientific discourse, assuming a certain scientific model, appears to be somewhat clear from a transdisciplinary (and thus structural) perspective. However, such scientific discourse represents only a sub-space of the general human discourse space. In the latter, the reception of texts from the perspective of humans inevitably also has a subjective view [18]: People are used to suspecting a human author behind a text. With the appearance of technical aids, texts have increasingly become products, which increasingly gaining formulations that are not written down by a human author alone, but by the technical aids themselves, mediated by a human author. With the appearance of text generators, the proportion of technically generated formulations increases extremely, up to the case that ultimately the entire text is the direct output of a technical aid. It becomes difficult to impossible to recognize to what extent a controlling human share can still be spoken of here. The human author thus disappears behind a text; the sign reality which does not prevent an existential projection of the inner world of the human reader into a potential human author, but threatens to lose itself or actually loses itself in the real absence of a human author in the face of a chimeric human counterpart. What happens in a world where people no longer have human counterparts?
[18] There is an excellent analysis on this topic by Hannes Bajohr titled “Artifizielle und postartifizielle Texte. Über Literatur und Künstliche Intelligenz” (Artificial and Post-Artificial Texts: On Literature and Artificial Intelligence). It was the Walter-Höllerer-Lecture 2022, delivered on December 8, 2022, at the Technical University of Berlin. The lecture can be accessed here [ https://hannesbajohr.de/wp-content/uploads/2022/12/Hoellerer-Vorlesung-2022.pdf ] (Accessed: September 29, 2023). The reference to this lecture was provided to me by Jennifer Becker.
Attention: This text has been translated from a German source by using the software deepL for nearly 97 – 99% of the text! The diagrams of the German version have been left out.
CONTEXT
This text represents the outline of a talk given at the conference “AI – Text and Validity. How do AI text generators change scientific discourse?” (August 25/26, 2023, TU Darmstadt). [1] A publication of all lectures is planned by the publisher Walter de Gruyter by the end of 2023/beginning of 2024. This publication will be announced here then.
Start of the Lecture
Dear Auditorium,
This conference entitled “AI – Text and Validity. How do AI text generators change scientific discourses?” is centrally devoted to scientific discourses and the possible influence of AI text generators on these. However, the hot core ultimately remains the phenomenon of text itself, its validity.
In this conference many different views are presented that are possible on this topic.
TRANSDISCIPLINARY
My contribution to the topic tries to define the role of the so-called AI text generators by embedding the properties of ‘AI text generators’ in a ‘structural conceptual framework’ within a ‘transdisciplinary view’. This helps the specifics of scientific discourses to be highlighted. This can then result further in better ‘criteria for an extended assessment’ of AI text generators in their role for scientific discourses.
An additional aspect is the question of the structure of ‘collective intelligence’ using humans as an example, and how this can possibly unite with an ‘artificial intelligence’ in the context of scientific discourses.
‘Transdisciplinary’ in this context means to span a ‘meta-level’ from which it should be possible to describe today’s ‘diversity of text productions’ in a way that is expressive enough to distinguish ‘AI-based’ text production from ‘human’ text production.
HUMAN TEXT GENERATION
The formulation ‘scientific discourse’ is a special case of the more general concept ‘human text generation’.
This change of perspective is meta-theoretically necessary, since at first sight it is not the ‘text as such’ that decides about ‘validity and non-validity’, but the ‘actors’ who ‘produce and understand texts’. And with the occurrence of ‘different kinds of actors’ – here ‘humans’, there ‘machines’ – one cannot avoid addressing exactly those differences – if there are any – that play a weighty role in the ‘validity of texts’.
TEXT CAPABLE MACHINES
With the distinction in two different kinds of actors – here ‘humans’, there ‘machines’ – a first ‘fundamental asymmetry’ immediately strikes the eye: so-called ‘AI text generators’ are entities that have been ‘invented’ and ‘built’ by humans, it are furthermore humans who ‘use’ them, and the essential material used by so-called AI generators are again ‘texts’ that are considered a ‘human cultural property’.
In the case of so-called ‘AI-text-generators’, we shall first state only this much, that we are dealing with ‘machines’, which have ‘input’ and ‘output’, plus a minimal ‘learning ability’, and whose input and output can process ‘text-like objects’.
BIOLOGICAL — NON-BIOLOGICAL
On the meta-level, then, we are assumed to have, on the one hand, such actors which are minimally ‘text-capable machines’ – completely human products – and, on the other hand, actors we call ‘humans’. Humans, as a ‘homo-sapiens population’, belong to the set of ‘biological systems’, while ‘text-capable machines’ belong to the set of ‘non-biological systems’.
BLANK INTELLIGENCE TERM
The transformation of the term ‘AI text generator’ into the term ‘text capable machine’ undertaken here is intended to additionally illustrate that the widespread use of the term ‘AI’ for ‘artificial intelligence’ is rather misleading. So far, there exists today no general concept of ‘intelligence’ in any scientific discipline that can be applied and accepted beyond individual disciplines. There is no real justification for the almost inflationary use of the term AI today other than that the term has been so drained of meaning that it can be used anytime, anywhere, without saying anything wrong. Something that has no meaning can be neither true’ nor ‘false’.
PREREQUISITES FOR TEXT GENERATION
If now the homo-sapiens population is identified as the original actor for ‘text generation’ and ‘text comprehension’, it shall now first be examined which are ‘those special characteristics’ that enable a homo-sapiens population to generate and comprehend texts and to ‘use them successfully in the everyday life process’.
VALIDITY
A connecting point for the investigation of the special characteristics of a homo-sapiens text generation and a text understanding is the term ‘validity’, which occurs in the conference topic.
In the primary arena of biological life, in everyday processes, in everyday life, the ‘validity’ of a text has to do with ‘being correct’, being ‘appicable’. If a text is not planned from the beginning with a ‘fictional character’, but with a ‘reference to everyday events’, which everyone can ‘check’ in the context of his ‘perception of the world’, then ‘validity in everyday life’ has to do with the fact that the ‘correctness of a text’ can be checked. If the ‘statement of a text’ is ‘applicable’ in everyday life, if it is ‘correct’, then one also says that this statement is ‘valid’, one grants it ‘validity’, one also calls it ‘true’. Against this background, one might be inclined to continue and say: ‘If’ the statement of a text ‘does not apply’, then it has ‘no validity’; simplified to the formulation that the statement is ‘not true’ or simply ‘false’.
In ‘real everyday life’, however, the world is rarely ‘black’ and ‘white’: it is not uncommon that we are confronted with texts to which we are inclined to ascribe ‘a possible validity’ because of their ‘learned meaning’, although it may not be at all clear whether there is – or will be – a situation in everyday life in which the statement of the text actually applies. In such a case, the validity would then be ‘indeterminate’; the statement would be ‘neither true nor false’.
ASYMMETRY: APPLICABLE- NOT APPLICABLE
One can recognize a certain asymmetry here: The ‘applicability’ of a statement, its actual validity, is comparatively clear. The ‘not being applicable’, i.e. a ‘merely possible’ validity, on the other hand, is difficult to decide.
With this phenomenon of the ‘current non-decidability’ of a statement we touch both the problem of the ‘meaning’ of a statement — how far is at all clear what is meant? — as well as the problem of the ‘unfinishedness of our everyday life’, better known as ‘future’: whether a ‘current present’ continues as such, whether exactly like this, or whether completely different, depends on how we understand and estimate ‘future’ in general; what some take for granted as a possible future, can be simply ‘nonsense’ for others.
MEANING
This tension between ‘currently decidable’ and ‘currently not yet decidable’ additionally clarifies an ‘autonomous’ aspect of the phenomenon of meaning: if a certain knowledge has been formed in the brain and has been made usable as ‘meaning’ for a ‘language system’, then this ‘associated’ meaning gains its own ‘reality’ for the scope of knowledge: it is not the ‘reality beyond the brain’, but the ‘reality of one’s own thinking’, whereby this reality of thinking ‘seen from outside’ has something like ‘being virtual’.
If one wants to talk about this ‘special reality of meaning’ in the context of the ‘whole system’, then one has to resort to far-reaching assumptions in order to be able to install a ‘conceptual framework’ on the meta-level which is able to sufficiently describe the structure and function of meaning. For this, the following components are minimally assumed (‘knowledge’, ‘language’ as well as ‘meaning relation’):
KNOWLEDGE: There is the totality of ‘knowledge’ that ‘builds up’ in the homo-sapiens actor in the course of time in the brain: both due to continuous interactions of the ‘brain’ with the ‘environment of the body’, as well as due to interactions ‘with the body itself’, as well as due to interactions ‘of the brain with itself’.
LANGUAGE: To be distinguished from knowledge is the dynamic system of ‘potential means of expression’, here simplistically called ‘language’, which can unfold over time in interaction with ‘knowledge’.
MEANING RELATIONSHIP: Finally, there is the dynamic ‘meaning relation’, an interaction mechanism that can link any knowledge elements to any language means of expression at any time.
Each of these mentioned components ‘knowledge’, ‘language’ as well as ‘meaning relation’ is extremely complex; no less complex is their interaction.
FUTURE AND EMOTIONS
In addition to the phenomenon of meaning, it also became apparent in the phenomenon of being applicable that the decision of being applicable also depends on an ‘available everyday situation’ in which a current correspondence can be ‘concretely shown’ or not.
If, in addition to a ‘conceivable meaning’ in the mind, we do not currently have any everyday situation that sufficiently corresponds to this meaning in the mind, then there are always two possibilities: We can give the ‘status of a possible future’ to this imagined construct despite the lack of reality reference, or not.
If we would decide to assign the status of a possible future to a ‘meaning in the head’, then there arise usually two requirements: (i) Can it be made sufficiently plausible in the light of the available knowledge that the ‘imagined possible situation’ can be ‘transformed into a new real situation’ in the ‘foreseeable future’ starting from the current real situation? And (ii) Are there ‘sustainable reasons’ why one should ‘want and affirm’ this possible future?
The first requirement calls for a powerful ‘science’ that sheds light on whether it can work at all. The second demand goes beyond this and brings the seemingly ‘irrational’ aspect of ’emotionality’ into play under the garb of ‘sustainability’: it is not simply about ‘knowledge as such’, it is also not only about a ‘so-called sustainable knowledge’ that is supposed to contribute to supporting the survival of life on planet Earth — and beyond –, it is rather also about ‘finding something good, affirming something, and then also wanting to decide it’. These last aspects are so far rather located beyond ‘rationality’; they are assigned to the diffuse area of ’emotions’; which is strange, since any form of ‘usual rationality’ is exactly based on these ’emotions’.[2]
SCIENTIFIC DISCOURSE AND EVERYDAY SITUATIONS
In the context of ‘rationality’ and ’emotionality’ just indicated, it is not uninteresting that in the conference topic ‘scientific discourse’ is thematized as a point of reference to clarify the status of text-capable machines.
The question is to what extent a ‘scientific discourse’ can serve as a reference point for a successful text at all?
For this purpose it can help to be aware of the fact that life on this planet earth takes place at every moment in an inconceivably large amount of ‘everyday situations’, which all take place simultaneously. Each ‘everyday situation’ represents a ‘present’ for the actors. And in the heads of the actors there is an individually different knowledge about how a present ‘can change’ or will change in a possible future.
This ‘knowledge in the heads’ of the actors involved can generally be ‘transformed into texts’ which in different ways ‘linguistically represent’ some of the aspects of everyday life.
The crucial point is that it is not enough for everyone to produce a text ‘for himself’ alone, quite ‘individually’, but that everyone must produce a ‘common text’ together ‘with everyone else’ who is also affected by the everyday situation. A ‘collective’ performance is required.
Nor is it a question of ‘any’ text, but one that is such that it allows for the ‘generation of possible continuations in the future’, that is, what is traditionally expected of a ‘scientific text’.
From the extensive discussion — since the times of Aristotle — of what ‘scientific’ should mean, what a ‘theory’ is, what an ’empirical theory’ should be, I sketch what I call here the ‘minimal concept of an empirical theory’.
The starting point is a ‘group of people’ (the ‘authors’) who want to create a ‘common text’.
This text is supposed to have the property that it allows ‘justifiable predictions’ for possible ‘future situations’, to which then ‘sometime’ in the future a ‘validity can be assigned’.
The authors are able to agree on a ‘starting situation’ which they transform by means of a ‘common language’ into a ‘source text’ [A].
It is agreed that this initial text may contain only ‘such linguistic expressions’ which can be shown to be ‘true’ ‘in the initial situation’.
In another text, the authors compile a set of ‘rules of change’ [V] that put into words ‘forms of change’ for a given situation.
Also in this case it is considered as agreed that only ‘such rules of change’ may be written down, of which all authors know that they have proved to be ‘true’ in ‘preceding everyday situations’.
The text with the rules of change V is on a ‘meta-level’ compared to the text A about the initial situation, which is on an ‘object-level’ relative to the text V.
The ‘interaction’ between the text V with the change rules and the text A with the initial situation is described in a separate ‘application text’ [F]: Here it is described when and how one may apply a change rule (in V) to a source text A and how this changes the ‘source text A’ to a ‘subsequent text A*’.
The application text F is thus on a next higher meta-level to the two texts A and V and can cause the application text to change the source text A.
The moment a new subsequent text A* exists, the subsequent text A* becomes the new initial text A.
If the new initial text A is such that a change rule from V can be applied again, then the generation of a new subsequent text A* is repeated.
This ‘repeatability’ of the application can lead to the generation of many subsequent texts <A*1, …, A*n>.
A series of many subsequent texts <A*1, …, A*n> is usually called a ‘simulation’.
Depending on the nature of the source text A and the nature of the change rules in V, it may be that possible simulations ‘can go quite differently’. The set of possible scientific simulations thus represents ‘future’ not as a single, definite course, but as an ‘arbitrarily large set of possible courses’.
The factors on which different courses depend are manifold. One factor are the authors themselves. Every author is, after all, with his corporeality completely himself part of that very empirical world which is to be described in a scientific theory. And, as is well known, any human actor can change his mind at any moment. He can literally in the next moment do exactly the opposite of what he thought before. And thus the world is already no longer the same as previously assumed in the scientific description.
Even this simple example shows that the emotionality of ‘finding good, wanting, and deciding’ lies ahead of the rationality of scientific theories. This continues in the so-called ‘sustainability discussion’.
SUSTAINABLE EMPIRICAL THEORY
With the ‘minimal concept of an empirical theory (ET)’ just introduced, a ‘minimal concept of a sustainable empirical theory (NET)’ can also be introduced directly.
While an empirical theory can span an arbitrarily large space of grounded simulations that make visible the space of many possible futures, everyday actors are left with the question of what they want to have as ‘their future’ out of all this? In the present we experience the situation that mankind gives the impression that it agrees to destroy the life beyond the human population more and more sustainably with the expected effect of ‘self-destruction’.
However, this self-destruction effect, which can be predicted in outline, is only one variant in the space of possible futures. Empirical science can indicate it in outline. To distinguish this variant before others, to accept it as ‘good’, to ‘want’ it, to ‘decide’ for this variant, lies in that so far hardly explored area of emotionality as root of all rationality.[2]
If everyday actors have decided in favor of a certain rationally lightened variant of possible future, then they can evaluate at any time with a suitable ‘evaluation procedure (EVAL)’ how much ‘percent (%) of the properties of the target state Z’ have been achieved so far, provided that the favored target state is transformed into a suitable text Z.
In other words, the moment we have transformed everyday scenarios into a rationally tangible state via suitable texts, things take on a certain clarity and thereby become — in a sense — simple. That we make such transformations and on which aspects of a real or possible state we then focus is, however, antecedent to text-based rationality as an emotional dimension.[2]
MAN-MACHINE
After these preliminary considerations, the final question is whether and how the main question of this conference, “How do AI text generators change scientific discourse?” can be answered in any way?
My previous remarks have attempted to show what it means for humans to collectively generate texts that meet the criteria for scientific discourse that also meets the requirements for empirical or even sustained empirical theories.
In doing so, it becomes apparent that both in the generation of a collective scientific text and in its application in everyday life, a close interrelation with both the shared experiential world and the dynamic knowledge and meaning components in each actor play a role.
The aspect of ‘validity’ is part of a dynamic world reference whose assessment as ‘true’ is constantly in flux; while one actor may tend to say “Yes, can be true”, another actor may just tend to the opposite. While some may tend to favor possible future option X, others may prefer future option Y. Rational arguments are absent; emotions speak. While one group has just decided to ‘believe’ and ‘implement’ plan Z, the others turn away, reject plan Z, and do something completely different.
This unsteady, uncertain character of future-interpretation and future-action accompanies the Homo Sapiens population from the very beginning. The not understood emotional complex constantly accompanies everyday life like a shadow.
Where and how can ‘text-enabled machines’ make a constructive contribution in this situation?
Assuming that there is a source text A, a change text V and an instruction F, today’s algorithms could calculate all possible simulations faster than humans could.
Assuming that there is also a target text Z, today’s algorithms could also compute an evaluation of the relationship between a current situation as A and the target text Z.
In other words: if an empirical or a sustainable-empirical theory would be formulated with its necessary texts, then a present algorithm could automatically compute all possible simulations and the degree of target fulfillment faster than any human alone.
But what about the (i) elaboration of a theory or (ii) the pre-rational decision for a certain empirical or even sustainable-empirical theory ?
A clear answer to both questions seems hardly possible to me at the present time, since we humans still understand too little how we ourselves collectively form, select, check, compare and also reject theories in everyday life.
My working hypothesis on the subject is: that we will very well need machines capable of learning in order to be able to fulfill the task of developing useful sustainable empirical theories for our common everyday life in the future. But when this will happen in reality and to what extent seems largely unclear to me at this point in time.[2]
COMMENTS
[1] https://zevedi.de/en/topics/ki-text-2/
[2] Talking about ’emotions’ in the sense of ‘factors in us’ that move us to go from the state ‘before the text’ to the state ‘written text’, that hints at very many aspects. In a small exploratory text “State Change from Non-Writing to Writing. Working with chatGPT4 in parallel” ( https://www.uffmm.org/2023/08/28/state-change-from-non-writing-to-writing-working-with-chatgpt4-in-parallel/ ) the author has tried to address some of these aspects. While writing it becomes clear that very many ‘individually subjective’ aspects play a role here, which of course do not appear ‘isolated’, but always flash up a reference to concrete contexts, which are linked to the topic. Nevertheless, it is not the ‘objective context’ that forms the core statement, but the ‘individually subjective’ component that appears in the process of ‘putting into words’. This individual subjective component is tentatively used here as a criterion for ‘authentic texts’ in comparison to ‘automated texts’ like those that can be generated by all kinds of bots. In order to make this difference more tangible, the author decided to create an ‘automated text’ with the same topic at the same time as the quoted authentic text. For this purpose he used chatGBT4 from openAI. This is the beginning of a philosophical-literary experiment, perhaps to make the possible difference more visible in this way. For purely theoretical reasons, it is clear that a text generated by chatGBT4 can never generate ‘authentic texts’ in origin, unless it uses as a template an authentic text that it can modify. But then this is a clear ‘fake document’. To prevent such an abuse, the author writes the authentic text first and then asks chatGBT4 to write something about the given topic without chatGBT4 knowing the authentic text, because it has not yet found its way into the database of chatGBT4 via the Internet.
At first sight, the previously described galactic cell association of a human body does not provide a natural clue for a ‘center’ of some kind. Which cell should be more important than others? Each one is active, each one does its ‘job’. Many ‘talk’ to many. Chemical substances are exchanged or by means of chemical substance exchange ‘electrical potentials’ are generated which can travel ‘faster’ and which can generate ‘impulse-like events’ which in turn activate chemical substances again. If one would make this ‘talking with chemical substances and electric potentials’ artificially audible, we would have a symphony of 127 trillion (127 x 10^12) single voices …
And yet, when we experience our human bodies in everyday life, we don’t see a huge cloud of galactic proportions of individual cells, we see a ‘delineated object’ with a surface that is ‘visible’; an object that can make ‘sounds’, that ‘smells’, that is ‘touchable’, that can ‘change’ and ‘move’. Moreover, it can ‘stuff things into itself’, and ‘gases’, ‘liquids’, and ‘more solid components’ also come out of it. Further it is obvious with longer observation that there are areas at the body which react to ‘light’ (eyes), to ‘sounds’ (ears), to ‘smells’ (nose), to ‘touch’ (skin), to ‘body positions’ (among other things sense of balance), to ‘temperature’ (skin), to ‘chemical compositions of substances in the mouth’ (taste organs in the mouth) and some more.
This everyday ‘experience’ suggests the assumption that the cells of our human body have spatially arranged themselves into ‘special networks’ [1], which show a high ‘degree of organization’, so pronounced that these networks appear like ‘one unit’, like a ‘single system’ with ‘input’ and ‘output’, and where complex processes take place between input and output. This opens up the possibility of viewing the galactic space of autonomous cells in a human body as a ‘collective of organized systems’ that appear to be in active exchange with each other.”[2], [4],[5]
In modern technical systems such as a car, an airplane, a computer, there is a ‘meta-level’ from which the whole system can be ‘controlled’. In the car the steering wheel, the brake, the gear shift etc., similarly in the airplane the cockpit with a multiplicity of instruments, or with the computer the input and output devices. However, for years an increasing ‘autonomy’ of these technical devices has been emerging, insofar as many control decisions of humans are shifted to ‘subsystems’, which thereby ‘self-perform’ more and more classical control performance of humans.[6].
In a human body there exists ‘parallel’ to the different body systems among other things the ‘nervous system’ with the ‘brain’ as central area, in which many ‘signals from the body systems’ run together and from which again ‘signals to the body systems’ are sent out. The brain with the nervous system seems to be a system of its own, which processes the incoming signals in different ‘neuronal processes’ and also sends out signals, which can cause ‘effects in the body systems’.[7] From the point of view of ‘functioning’ the brain with the nervous system can be understood as a kind of ‘meta-system’, in which properties of all other ‘body systems’ are ‘mapped’, find a ‘process-like interpretation’, and can be influenced (= ‘controlled’) to a certain degree with the help of these mappings and interpretations.
As the modern empirical sciences make visible more and more by their investigations and subsequent ‘interpretations’ (e.g. [4],[5]), the distinguishable body systems themselves have a very high complexity with their own ‘autonomy’ (stomach, liver, kidney, heart, …), which can be influenced only conditionally by the brain, but which conversely can also influence the brain. In addition, there is a hardly manageable amount of mutual influences via the immense ‘material flows’ in the blood circulation and in the body fluids.
For the context of this book, of particular interest here are those structures that are important for the ‘coordination of the different brains’ by means of ‘language’ and closely related to this are the ‘cognitive’ and ’emotional’ processes in the brain that are responsible for what ‘cognitive images are created in the mind’ with which a brain ‘interprets’ ‘itself’ and ‘everything else’.
How to describe the Human Being?
The description of the human cell galaxy as ‘subsystems’ with their own ‘input’ and ‘output’ and and including ‘inner processes’ – here simply called the ‘system function’ – can appear ‘simple’ at first sight, ‘normal’, or something else. We enter with this question the fundamental question, how we can describe the human cell galaxy – i.e. ‘ourselves’! – at all and furthermore maybe how we ‘should’ describe it: are there any criteria on the basis of which we should prefer a ‘certain way of description’?
In the case of the description of ‘nature’, of the ‘real world’, we may still be able to distinguish between ‘us’ and ‘nature’ (which, however, will later come out as a fallacy)), it becomes somewhat more difficult with the ‘description of ourselves’. If one wants to describe something, one needs certain conditions to be able to make a description. But what are these conditions if we want to describe ourselves? Doesn’t here the famous ‘cat bite into its own tail’?
In ‘normal everyday life’ [8] typical forms with which we describe are e.g. ‘pictures’, ‘photographs’, ‘videos’, ‘music’, ‘body movements’ and others, but above all linguistic expressions (spoken, written; everyday language, technical language; …).
Let’s stay for a moment with ‘everyday language (German, English, Italian, …).
As children we are born into a certain, already existing world with a respective ‘everyday life’ distinctive for each human person. At least one language is spoken in such an environment. If the parents are bilingual even two languages in parallel. If the environment is different from the language of the parents, then perhaps even three languages. And today, where also the environment becomes more and more ‘multi-cultural’, maybe even more than three languages are practiced.
No matter how many languages occur simultaneously for a person, each language has its own ‘rules’, its own ‘pronunciation’, its own ‘contextual reference’, its own ‘meanings’. These contexts can change; the language itself can change. And if someone grows up with not just one language, but more than one, then ‘in the person’, in the ‘speaker-listener’, there can naturally be multiple interactions between the different languages. Since this happens today in many places at the same time with more and more people, there are still hardly sufficient research results available that adequately describe this diversity in its specifics.
So, if we want to describe ‘ourselves’ as ‘part of the real world’, we should first of all accept and ‘consciously assume’ that we do not start at ‘point zero’ at the moment of describing, not as a ‘blank sheet’, but as a biological system which has a more or less long ‘learning process’ behind it. Thereby, the word ‘learning process’ as part of the language the author uses, is not a ‘neutral set of letters’, but likewise a ‘word’ of his language, which he shares with many other speakers of ‘German’. One must assume that each ‘speaker of German’ associates his own ‘individual conceptions’ with the word ‘learning process’. And also this word ‘conception’ is such a word, which as part of the spoken (and written) language normally does not come along ‘meaning-free’. In short, as soon as we speak, as soon as we link words in larger units to statements, we activate a set of ‘knowledge and skills’ that are somehow ‘present in us’, that we use ‘automatically’, and whose use is normally largely ‘unconscious’.”[9],[10]
When I, as the author of this text, now write down statements in the German language, I let myself be carried by a ‘wave of language usage’, so to speak, whose exact nature and effectiveness I cannot fully grasp at the moment of use (and this is the case for every language user). I can, however, when I have expressed myself, look more consciously at what has been expressed, and then — perhaps — see clearer whether and how I can place it in contexts known to me. Since also the ‘known to me’ is largely ‘unconscious’ and passes from ‘unconscious knowledge’ into ‘conscious’ knowledge, the task of a ‘clarification of speaking’ and the ‘meaning’ connected with it is always only fragmentarily, partially possible. The ‘conscious eye of knowledge’ is therefore perhaps comparable to a ‘shining knowledge bubble’ in the black sea of ‘unconscious knowledge’, which seems to be close to ‘not-knowing’ but it isn’t ‘not-knowing’: ‘unconscious knowledge’ is ‘inside the brain ‘real knowledge’, which ‘works’.
… to be continued …
COMMENTS
wkp := Wikipedia
[1] In microbiology as a part of evolutionary biology, one has recognized rudimentarily how the individual cells during the ‘growth process’ ‘communicate’ possible cooperations with other cells via chemical substances, which are ‘controlled’ by their respective individual ‘genetic program’. These processes can very well be described as ‘exchange of signals’, where these ‘signals’ do not occur in isolation, but are ‘related’ by the genetic program to other chemical substances and process steps. Through this ‘relating’, the chemical signal carriers, isolated in themselves, are embedded in a ‘space of meanings’ from which they find an ‘assignment’. This overall process fulfills all requirements of a ‘communication’. In this respect, it seems justified to speak of an ‘agreement’ between the individual cells, an ‘understanding’ about whether and how they want to ‘cooperate’ with each other.
[2] When thinking of complex connections between cells, one may first think of the cells in the brain (‘neurons’), certain types of which may have as many as 1000 dendrites (:= these are projections on an ‘axon’ and an axon is the ‘output’ on a neuron), each dendrite housing multiple synapses.[3] Since each synapse can be the endpoint of a connection to another synapse, it suggests that a complex network of the order of trillions (10^12) connections may exist here in a brain. In addition, there is also the system of blood vessels that run through the entire body and supply the approximately 36 trillion (10^12) body cells with various chemical substances.
[3] wkp [EN], Neuron, URL: https://en.wikipedia.org/wiki/Neuron, section ‚Connectivity‘, citation: „The human brain has some 8.6 x 1010 (eighty six billion neurons. Each neuron has on average 7,000 synaptic connections to other neurons. It has been estimated that the brain of a three-year-old child has about 1015 synapses (quadrillion). This number declines with age, stabilizing by adulthood. Estimates vary for an adult, ranging from 1014 to 5 x 1014 synapses (100 to 500 trillion).”
[4] Robert F.Schmidt, Gerhard Thews (Eds.), 1995, Physiologie des Menschen, 25th edition, Springer
[6] Famously, the example of the ‘auto-pilot’ on an airplane, software that can ‘steer’ the entire plane without human intervention.
[7] Thus, the position of the joints is continuously sent to the brain and, in the case of a ‘directed movement’, the set of current joint positions is used to trigger an ‘appropriate movement’ by sending appropriate signals ‘from the brain to the muscles’.
[8] Of course, also a certain fiction, because everyone ultimately experiences ‘his everyday life’ to a certain degree, which only partially overlaps with the ‘everyday life of another’.
[9] When children in school are confronted for the first time with the concept of a ‘grammar’, with ‘grammatical rules’, they will not understand what that is. Using concrete examples of language, they will be able to ‘link’ one or another ‘grammatical expression’ with linguistic phenomena, but they will not really understand the concept of grammar. This is due to the fact that the entire processes that take place in the ‘inside of a human being’ have been researched only in a very rudimentary way until today. It is in no way sufficient for the formulation of a grammar close to everyday life.
[10] Karl Erich Heidoplh, Walter Flämig, Wolfgang Motsch (ed.), (1980), Grundzüge einer Deutschen Grammatik, Akademie-Verlag, Berlin. Note: Probably the most systematized grammar of German to date, compiled by a German authors’ collective (at that time still the eastern part of Germany called ‘German Democratic Republic’ (GDR)). Precisely because the approach was very systematic, the authors could clearly see that grammar as a description of ‘regular forms’ reaches its limits where the ‘meaning’ of expressions comes into play. Since ‘meaning’ describes a state of affairs that takes place in the ‘inside of the human being’ (of course in intensive interaction with interactions of the body with the environment), a comprehensive objective description of the factor ‘meaning’ in interaction with the forms is always only partially possible.
The whole text shows a dynamic, which induces many changes. Difficult to plan ‘in advance’.
Perhaps, some time, it will look like a ‘book’, at least ‘for a moment’.
I have started a ‘book project’ in parallel. This was motivated by the need to provide potential users of our new oksimo.R software with a coherent explanation of how the oksimo.R software, when used, generates an empirical theory in the format of a screenplay. The primary source of the book is in German and will be translated step by step here in the uffmm.blog.
INTRODUCTION
In a rather foundational paper about an idea, how one can generalize ‘systems engineering’ [*1] to the art of ‘theory engineering’ [1] a new conceptual framework has been outlined for a ‘sustainable applied empirical theory (SAET)’. Part of this new framework has been the idea that the classical recourse to groups of special experts (mostly ‘engineers’ in engineering) is too restrictive in the light of the new requirement of being sustainable: sustainability is primarily based on ‘diversity’ combined with the ‘ability to predict’ from this diversity probable future states which keep life alive. The aspect of diversity induces the challenge to see every citizen as a ‘natural expert’, because nobody can know in advance and from some non-existing absolut point of truth, which knowledge is really important. History shows that the ‘mainstream’ is usually to a large degree ‘biased’ [*1b].
With this assumption, that every citizen is a ‘natural expert’, science turns into a ‘general science’ where all citizens are ‘natural members’ of science. I will call this more general concept of science ‘sustainable citizen science (SCS)’ or ‘Citizen Science 2.0 (CS2)’. The important point here is that a sustainable citizen science is not necessarily an ‘arbitrary’ process. While the requirement of ‘diversity’ relates to possible contents, to possible ideas, to possible experiments, and the like, it follows from the other requirement of ‘predictability’/ of being able to make some useful ‘forecasts’, that the given knowledge has to be in a format, which allows in a transparent way the construction of some consequences, which ‘derive’ from the ‘given’ knowledge and enable some ‘new’ knowledge. This ability of forecasting has often been understood as the business of ‘logic’ providing an ‘inference concept’ given by ‘rules of deduction’ and a ‘practical pattern (on the meta level)’, which defines how these rules have to be applied to satisfy the inference concept. But, looking to real life, to everyday life or to modern engineering and economy, one can learn that ‘forecasting’ is a complex process including much more than only cognitive structures nicely fitting into some formulas. For this more realistic forecasting concept we will use here the wording ‘common logic’ and for the cognitive adventure where common logic is applied we will use the wording ‘common science’. ‘Common science’ is structurally not different from ‘usual science’, but it has a substantial wider scope and is using the whole of mankind as ‘experts’.
The following chapters/ sections try to illustrate this common science view by visiting different special views which all are only ‘parts of a whole’, a whole which we can ‘feel’ in every moment, but which we can not yet completely grasp with our theoretical concepts.
CONTENT
Language (Main message: “The ordinary language is the ‘meta language’ to every special language. This can be used as a ‘hint’ to something really great: the mystery of the ‘self-creating’ power of the ordinary language which for most people is unknown although it happens every moment.”)
Concrete Abstract Statements (Main message: “… you will probably detect, that nearly all words of a language are ‘abstract words’ activating ‘abstract meanings’. …If you cannot provide … ‘concrete situations’ the intended meaning of your abstract words will stay ‘unclear’: they can mean ‘nothing or all’, depending from the decoding of the hearer.”)
True False Undefined (Main message: “… it reveals that ’empirical (observational) evidence’ is not necessarily an automatism: it presupposes appropriate meaning spaces embedded in sets of preferences, which are ‘observation friendly’.“
Beyond Now (Main message: “With the aid of … sequences revealing possible changes the NOW is turned into a ‘moment’ embedded in a ‘process’, which is becoming the more important reality. The NOW is something, but the PROCESS is more.“)
Playing with the Future (Main message: “In this sense seems ‘language’ to be the master tool for every brain to mediate its dynamic meaning structures with symbolic fix points (= words, expressions) which as such do not change, but the meaning is ‘free to change’ in any direction. And this ‘built in ‘dynamics’ represents an ‘internal potential’ for uncountable many possible states, which could perhaps become ‘true’ in some ‘future state’. Thus ‘future’ can begin in these potentials, and thinking is the ‘playground’ for possible futures.(but see [18])”)
Forecasting – Prediction: What? (This chapter explains the cognitive machinery behind forecasting/ predictions, how groups of human actors can elaborate shared descriptions, and how it is possible to start with sequences of singularities to built up a growing picture of the empirical world which appears as a radical infinite and indeterministic space. )
!!! From here all the following chapters have to be re-written !!!
Boolean Logic (Explains what boolean logic is, how it enables the working of programmable machines, but that it is of nearly no help for the ‘heart’ of forecasting.)
/* Often people argue against the usage of the wikipedia encyclopedia as not ‘scientific’ because the ‘content’ of an entry in this encyclopedia can ‘change’. This presupposes the ‘classical view’ of scientific texts to be ‘stable’, which presupposes further, that such a ‘stable text’ describes some ‘stable subject matter’. But this view of ‘steadiness’ as the major property of ‘true descriptions’ is in no correspondence with real scientific texts! The reality of empirical science — even as in some special disciplines like ‘physics’ — is ‘change’. Looking to Aristotle’s view of nature, to Galileo Galilei, to Newton, to Einstein and many others, you will not find a ‘single steady picture’ of nature and science, and physics is only a very simple strand of science compared to the live-sciences and many others. Thus wikipedia is a real scientific encyclopedia give you the breath of world knowledge with all its strengths and limits at once. For another, more general argument, see In Favour for Wikipedia */
[*1] Meaning operator ‘…’ : In this text (and in nearly all other texts of this author) the ‘inverted comma’ is used quite heavily. In everyday language this is not common. In some special languages (theory of formal languages or in programming languages or in meta-logic) the inverted comma is used in some special way. In this text, which is primarily a philosophical text, the inverted comma sign is used as a ‘meta-language operator’ to raise the intention of the reader to be aware, that the ‘meaning’ of the word enclosed in the inverted commas is ‘text specific’: in everyday language usage the speaker uses a word and assumes tacitly that his ‘intended meaning’ will be understood by the hearer of his utterance as ‘it is’. And the speaker will adhere to his assumption until some hearer signals, that her understanding is different. That such a difference is signaled is quite normal, because the ‘meaning’ which is associated with a language expression can be diverse, and a decision, which one of these multiple possible meanings is the ‘intended one’ in a certain context is often a bit ‘arbitrary’. Thus, it can be — but must not — a meta-language strategy, to comment to the hearer (or here: the reader), that a certain expression in a communication is ‘intended’ with a special meaning which perhaps is not the commonly assumed one. Nevertheless, because the ‘common meaning’ is no ‘clear and sharp subject’, a ‘meaning operator’ with the inverted commas has also not a very sharp meaning. But in the ‘game of language’ it is more than nothing 🙂
[*1b] That the main stream ‘is biased’ is not an accident, not a ‘strange state’, not a ‘failure’, it is the ‘normal state’ based on the deeper structure how human actors are ‘built’ and ‘genetically’ and ‘cultural’ ‘programmed’. Thus the challenge to ‘survive’ as part of the ‘whole biosphere’ is not a ‘partial task’ to solve a single problem, but to solve in some sense the problem how to ‘shape the whole biosphere’ in a way, which enables a live in the universe for the time beyond that point where the sun is turning into a ‘red giant’ whereby life will be impossible on the planet earth (some billion years ahead)[22]. A remarkable text supporting this ‘complex view of sustainability’ can be found in Clark and Harvey, summarized at the end of the text. [23]
[*2] The meaning of the expression ‘normal’ is comparable to a wicked problem. In a certain sense we act in our everyday world ‘as if there exists some standard’ for what is assumed to be ‘normal’. Look for instance to houses, buildings: to a certain degree parts of a house have a ‘standard format’ assuming ‘normal people’. The whole traffic system, most parts of our ‘daily life’ are following certain ‘standards’ making ‘planning’ possible. But there exists a certain percentage of human persons which are ‘different’ compared to these introduced standards. We say that they have a ‘handicap’ compared to this assumed ‘standard’, but this so-called ‘standard’ is neither 100% true nor is the ‘given real world’ in its properties a ‘100% subject’. We have learned that ‘properties of the real world’ are distributed in a rather ‘statistical manner’ with different probabilities of occurrences. To ‘find our way’ in these varying occurrences we try to ‘mark’ the main occurrences as ‘normal’ to enable a basic structure for expectations and planning. Thus, if in this text the expression ‘normal’ is used it refers to the ‘most common occurrences’.
[*3] Thus we have here a ‘threefold structure’ embracing ‘perception events, memory events, and expression events’. Perception events represent ‘concrete events’; memory events represent all kinds of abstract events but they all have a ‘handle’ which maps to subsets of concrete events; expression events are parts of an abstract language system, which as such is dynamically mapped onto the abstract events. The main source for our knowledge about perceptions, memory and expressions is experimental psychology enhanced by many other disciplines.
[*4] Characterizing language expressions by meaning – the fate of any grammar: the sentence ” … ‘words’ (= expressions) of a language which can activate such abstract meanings are understood as ‘abstract words’, ‘general words’, ‘category words’ or the like.” is pointing to a deep property of every ordinary language, which represents the real power of language but at the same time the great weakness too: expressions as such have no meaning. Hundreds, thousands, millions of words arranged in ‘texts’, ‘documents’ can show some statistical patterns’ and as such these patterns can give some hint which expressions occur ‘how often’ and in ‘which combinations’, but they never can give a clue to the associated meaning(s). During more than three-thousand years humans have tried to describe ordinary language in a more systematic way called ‘grammar’. Due to this radically gap between ‘expressions’ as ‘observable empirical facts’ and ‘meaning constructs’ hidden inside the brain it was all the time a difficult job to ‘classify’ expressions as representing a certain ‘type’ of expression like ‘nouns’, ‘predicates’, ‘adjectives’, ‘defining article’ and the like. Without regressing to the assumed associated meaning such a classification is not possible. On account of the fuzziness of every meaning ‘sharp definitions’ of such ‘word classes’ was never and is not yet possible. One of the last big — perhaps the biggest ever — project of a complete systematic grammar of a language was the grammar project of the ‘Akademie der Wissenschaften der DDR’ (‘Academy of Sciences of the GDR’) from 1981 with the title “Grundzüge einer Deutschen Grammatik” (“Basic features of a German grammar”). A huge team of scientists worked together using many modern methods. But in the preface you can read, that many important properties of the language are still not sufficiently well describable and explainable. See: Karl Erich Heidolph, Walter Flämig, Wolfgang Motsch et al.: Grundzüge einer deutschen Grammatik. Akademie, Berlin 1981, 1028 Seiten.
[*5] Differing opinions about a given situation manifested in uttered expressions are a very common phenomenon in everyday communication. In some sense this is ‘natural’, can happen, and it should be no substantial problem to ‘solve the riddle of being different’. But as you can experience, the ability of people to solve the occurrence of different opinions is often quite weak. Culture is suffering by this as a whole.
[1] Gerd Doeben-Henisch, 2022, From SYSTEMS Engineering to THEORYEngineering, see: https://www.uffmm.org/2022/05/26/from-systems-engineering-to-theory-engineering/(Remark: At the time of citation this post was not yet finished, because there are other posts ‘corresponding’ with that post, which are too not finished. Knowledge is a dynamic network of interwoven views …).
[1d] ‘usual science’ is the game of science without having a sustainable format like in citizen science 2.0.
[2] Science, see e.g. wkp-en: https://en.wikipedia.org/wiki/Science
Citation = “In modern science, the term “theory” refers to scientific theories, a well-confirmed type of explanation of nature, made in a way consistent with the scientific method, and fulfilling the criteria required by modern science. Such theories are described in such a way that scientific tests should be able to provide empirical support for it, or empirical contradiction (“falsify“) of it. Scientific theories are the most reliable, rigorous, and comprehensive form of scientific knowledge,[1] in contrast to more common uses of the word “theory” that imply that something is unproven or speculative (which in formal terms is better characterized by the word hypothesis).[2] Scientific theories are distinguished from hypotheses, which are individual empirically testableconjectures, and from scientific laws, which are descriptive accounts of the way nature behaves under certain conditions.”
[2b] History of science in wkp-en: https://en.wikipedia.org/wiki/History_of_science#Scientific_Revolution_and_birth_of_New_Science
[3] Theory, see wkp-en: https://en.wikipedia.org/wiki/Theory#:~:text=A%20theory%20is%20a%20rational,or%20no%20discipline%20at%20all.
Citation = “A theory is a rational type of abstract thinking about a phenomenon, or the results of such thinking. The process of contemplative and rational thinking is often associated with such processes as observational study or research. Theories may be scientific, belong to a non-scientific discipline, or no discipline at all. Depending on the context, a theory’s assertions might, for example, include generalized explanations of how nature works. The word has its roots in ancient Greek, but in modern use it has taken on several related meanings.”
Citation = “In modern science, the term “theory” refers to scientific theories, a well-confirmed type of explanation of nature, made in a way consistent with the scientific method, and fulfilling the criteria required by modern science. Such theories are described in such a way that scientific tests should be able to provide empirical support for it, or empirical contradiction (“falsify“) of it. Scientific theories are the most reliable, rigorous, and comprehensive form of scientific knowledge,[1] in contrast to more common uses of the word “theory” that imply that something is unproven or speculative (which in formal terms is better characterized by the word hypothesis).[2] Scientific theories are distinguished from hypotheses, which are individual empirically testableconjectures, and from scientific laws, which are descriptive accounts of the way nature behaves under certain conditions.”
[4b] Empiricism in wkp-en: https://en.wikipedia.org/wiki/Empiricism
[4c] Scientific method in wkp-en: https://en.wikipedia.org/wiki/Scientific_method
Citation =”The scientific method is an empirical method of acquiring knowledge that has characterized the development of science since at least the 17th century (with notable practitioners in previous centuries). It involves careful observation, applying rigorous skepticism about what is observed, given that cognitive assumptions can distort how one interprets the observation. It involves formulating hypotheses, via induction, based on such observations; experimental and measurement-based statistical testing of deductions drawn from the hypotheses; and refinement (or elimination) of the hypotheses based on the experimental findings. These are principles of the scientific method, as distinguished from a definitive series of steps applicable to all scientific enterprises.[1][2][3] [4c]
and
Citation = “The purpose of an experiment is to determine whether observations[A][a][b] agree with or conflict with the expectations deduced from a hypothesis.[6]: Book I, [6.54] pp.372, 408 [b] Experiments can take place anywhere from a garage to a remote mountaintop to CERN’s Large Hadron Collider. There are difficulties in a formulaic statement of method, however. Though the scientific method is often presented as a fixed sequence of steps, it represents rather a set of general principles.[7] Not all steps take place in every scientific inquiry (nor to the same degree), and they are not always in the same order.[8][9]”
[5] Gerd Doeben-Henisch, “Is Mathematics a Fake? No! Discussing N.Bourbaki, Theory of Sets (1968) – Introduction”, 2022, https://www.uffmm.org/2022/06/06/n-bourbaki-theory-of-sets-1968-introduction/
[6] Logic, see wkp-en: https://en.wikipedia.org/wiki/Logic
[7] W. C. Kneale, The Development of Logic, Oxford University Press (1962)
[8] Set theory, in wkp-en: https://en.wikipedia.org/wiki/Set_theory
[9] N.Bourbaki, Theory of Sets , 1968, with a chapter about structures, see: https://en.wikipedia.org/wiki/%C3%89l%C3%A9ments_de_math%C3%A9matique
[10] = [5]
[11] Ludwig Josef Johann Wittgenstein ( 1889 – 1951): https://en.wikipedia.org/wiki/Ludwig_Wittgenstein
[12] Ludwig Wittgenstein, 1953: Philosophische Untersuchungen [PU], 1953: Philosophical Investigations [PI], translated by G. E. M. Anscombe /* For more details see: https://en.wikipedia.org/wiki/Philosophical_Investigations */
[13] Wikipedia EN, Speech acts: https://en.wikipedia.org/wiki/Speech_act
[14] While the world view constructed in a brain is ‘virtual’ compared to the ‘real word’ outside the brain (where the body outside the brain is also functioning as ‘real world’ in relation to the brain), does the ‘virtual world’ in the brain function for the brain mostly ‘as if it is the real world’. Only under certain conditions can the brain realize a ‘difference’ between the triggering outside real world and the ‘virtual substitute for the real world’: You want to use your bicycle ‘as usual’ and then suddenly you have to notice that it is not at that place where is ‘should be’. …
[15] Propositional Calculus, see wkp-en: https://en.wikipedia.org/wiki/Propositional_calculus#:~:text=Propositional%20calculus%20is%20a%20branch,of%20arguments%20based%20on%20them.
[16] Boolean algebra, see wkp-en: https://en.wikipedia.org/wiki/Boolean_algebra
[17] Boolean (or propositional) Logic: As one can see in the mentioned articles of the English wikipedia, the term ‘boolean logic’ is not common. The more logic-oriented authors prefer the term ‘boolean calculus’ [15] and the more math-oriented authors prefer the term ‘boolean algebra’ [16]. In the view of this author the general view is that of ‘language use’ with ‘logic inference’ as leading idea. Therefore the main topic is ‘logic’, in the case of propositional logic reduced to a simple calculus whose similarity with ‘normal language’ is widely ‘reduced’ to a play with abstract names and operators. Recommended: the historical comments in [15].
[18] Clearly, thinking alone can not necessarily induce a possible state which along the time line will become a ‘real state’. There are numerous factors ‘outside’ the individual thinking which are ‘driving forces’ to push real states to change. But thinking can in principle synchronize with other individual thinking and — in some cases — can get a ‘grip’ on real factors causing real changes.
[19] This kind of knowledge is not delivered by brain science alone but primarily from experimental (cognitive) psychology which examines observable behavior and ‘interprets’ this behavior with functional models within an empirical theory.
[20] Predicate Logic or First-Order Logic or … see: wkp-en: https://en.wikipedia.org/wiki/First-order_logic#:~:text=First%2Dorder%20logic%E2%80%94also%20known,%2C%20linguistics%2C%20and%20computer%20science.
[21] Gerd Doeben-Henisch, In Favour of Wikipedia, https://www.uffmm.org/2022/07/31/in-favour-of-wikipedia/, 31 July 2022
[22] The sun, see wkp-ed https://en.wikipedia.org/wiki/Sun (accessed 8 Aug 2022)
[23] By Clark, William C., and Alicia G. Harley – https://doi.org/10.1146/annurev-environ-012420-043621, Clark, William C., and Alicia G. Harley. 2020. “Sustainability Science: Toward a Synthesis.” Annual Review of Environment and Resources 45 (1): 331–86, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=109026069
[24] Sustainability in wkp-en: https://en.wikipedia.org/wiki/Sustainability#Dimensions_of_sustainability
[27] SDG 4 in wkp-en: https://en.wikipedia.org/wiki/Sustainable_Development_Goal_4
[28] Thomas Rid, Rise of the Machines. A Cybernetic History, W.W.Norton & Company, 2016, New York – London
[29] Doeben-Henisch, G., 2006, Reducing Negative Complexity by a Semiotic System In: Gudwin, R., & Queiroz, J., (Eds). Semiotics and Intelligent Systems Development. Hershey et al: Idea Group Publishing, 2006, pp.330-342
[30] Döben-Henisch, G., Reinforcing the global heartbeat: Introducing the planet earth simulator project, In M. Faßler & C. Terkowsky (Eds.), URBAN FICTIONS. Die Zukunft des Städtischen. München, Germany: Wilhelm Fink Verlag, 2006, pp.251-263
[29] The idea that individual disciplines are not good enough for the ‘whole of knowledge’ is expressed in a clear way in a video of the theoretical physicist and philosopher Carlo Rovell: Carlo Rovelli on physics and philosophy, June 1, 2022, Video from the Perimeter Institute for Theoretical Physics. Theoretical physicist, philosopher, and international bestselling author Carlo Rovelli joins Lauren and Colin for a conversation about the quest for quantum gravity, the importance of unlearning outdated ideas, and a very unique way to get out of a speeding ticket.
[] By Azote for Stockholm Resilience Centre, Stockholm University – https://www.stockholmresilience.org/research/research-news/2016-06-14-how-food-connects-all-the-sdgs.html, CC BY 4.0, https://commons.wikimedia.org/w/index.php?curid=112497386
[] Sierra Club in wkp-en: https://en.wikipedia.org/wiki/Sierra_Club
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/* Comment: Gro Harlem Brundtland (Norway) has been the main coordinator of this document */
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[] V. Singh, G. Singh, and S. Pande (2013), Emergence, self-organization and collective intelligence—Modeling the dynamics of complex collectives in social and organizational settings. In 2013 UKSim 15th International Conference on Computer Modelling and Simulation. 182–189. DOI:https://doi.org/10.1109/UKSim.2013.77
[] A. Kornrumpf and U. Baumöl (2014), A design science approach to collective intelligence systems. In 2014 47th Hawaii International Conference on System Sciences. 361–370. DOI:https://doi.org/10.1109/HICSS.2014.53
[] Michael A. Peters and Richard Heraud. 2015. Toward a political theory of social innovation: Collective intelligence and the co-creation of social goods. 3, 3 (2015), 7–23. https://researchcommons.waikato.ac.nz/handle/10289/9569
[] Juho Salminen. 2015. The Role of Collective Intelligence in Crowdsourcing Innovation. PhD dissertation. Lappeenranta University of Technology
[] Aelita Skarzauskiene and Monika Maciuliene (2015), Modelling the index of collective intelligence in online community projects. In International Conference on Cyber Warfare and Security. Academic Conferences International Limited, 313
[] AYA H. KIMURA and ABBY KINCHY (2016), Citizen Science: Probing the Virtues and Contexts of Participatory Research, Engaging Science, Technology, and Society 2 (2016), 331-361, DOI:10.17351/ests2016.099
[] Philip Tetlow, Dinesh Garg, Leigh Chase, Mark Mattingley-Scott, Nicholas Bronn, Kugendran Naidoo†, Emil Reinert (2022), Towards a Semantic Information Theory (Introducing Quantum Corollas), arXiv:2201.05478v1 [cs.IT] 14 Jan 2022, 28 pages
[] Melanie Mitchell, What Does It Mean to Align AI With Human Values?, quanta magazin, Quantized Columns, 19.Devember 2022, https://www.quantamagazine.org/what-does-it-mean-to-align-ai-with-human-values-20221213#
Comment by Gerd Doeben-Henisch:
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[] Scott Aaronson, Reform AI Alignment, Update: 22.November 2022, https://scottaaronson.blog/?p=6821
[] Andrew Y. Ng, Stuart J. Russell, Algorithms for Inverse Reinforcement Learning, ICML 2000: Proceedings of the Seventeenth International Conference on Machine LearningJune 2000 Pages 663–670
[] Pat Langley (ed.), ICML ’00: Proceedings of the Seventeenth International Conference on Machine Learning, Morgan Kaufmann Publishers Inc., 340 Pine Street, Sixth Floor, San Francisco, CA, United States, Conference 29 June 2000- 2 July 2000, 29.June 2000
Abstract: Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations Daniel S. Brown * 1 Wonjoon Goo * 1 Prabhat Nagarajan 2 Scott Niekum 1 You can read in the abstract: “A critical flaw of existing inverse reinforcement learning (IRL) methods is their inability to significantly outperform the demonstrator. This is because IRL typically seeks a reward function that makes the demonstrator appear near-optimal, rather than inferring the underlying intentions of the demonstrator that may have been poorly executed in practice. In this paper, we introduce a novel reward-learning-from-observation algorithm, Trajectory-ranked Reward EXtrapolation (T-REX), that extrapolates beyond a set of (ap- proximately) ranked demonstrations in order to infer high-quality reward functions from a set of potentially poor demonstrations. When combined with deep reinforcement learning, T-REX outperforms state-of-the-art imitation learning and IRL methods on multiple Atari and MuJoCo bench- mark tasks and achieves performance that is often more than twice the performance of the best demonstration. We also demonstrate that T-REX is robust to ranking noise and can accurately extrapolate intention by simply watching a learner noisily improve at a task over time.”
In the abstract you can read: “For sophisticated reinforcement learning (RL) systems to interact usefully with real-world environments, we need to communicate complex goals to these systems. In this work, we explore goals defined in terms of (non-expert) human preferences between pairs of trajectory segments. We show that this approach can effectively solve complex RL tasks without access to the reward function, including Atari games and simulated robot locomotion, while providing feedback on less than one percent of our agent’s interactions with the environment. This reduces the cost of human oversight far enough that it can be practically applied to state-of-the-art RL systems. To demonstrate the flexibility of our approach, we show that we can successfully train complex novel behaviors with about an hour of human time. These behaviors and environments are considerably more complex than any that have been previously learned from human feedback.
In the abstract you can read: “Conceptual abstraction and analogy-making are key abilities underlying humans’ abilities to learn, reason, and robustly adapt their knowledge to new domains. Despite of a long history of research on constructing AI systems with these abilities, no current AI system is anywhere close to a capability of forming humanlike abstractions or analogies. This paper reviews the advantages and limitations of several approaches toward this goal, including symbolic methods, deep learning, and probabilistic program induction. The paper concludes with several proposals for designing challenge tasks and evaluation measures in order to make quantifiable and generalizable progress
In the abstract you can read: “Since its beginning in the 1950s, the field of artificial intelligence has cycled several times between periods of optimistic predictions and massive investment (“AI spring”) and periods of disappointment, loss of confidence, and reduced funding (“AI winter”). Even with today’s seemingly fast pace of AI breakthroughs, the development of long-promised technologies such as self-driving cars, housekeeping robots, and conversational companions has turned out to be much harder than many people expected. One reason for these repeating cycles is our limited understanding of the nature and complexity of intelligence itself. In this paper I describe four fallacies in common assumptions made by AI researchers, which can lead to overconfident predictions about the field. I conclude by discussing the open questions spurred by these fallacies, including the age-old challenge of imbuing machines with humanlike common sense.”
[] Stuart Russell, (2019), Human Compatible: AI and the Problem of Control, Penguin books, Allen Lane; 1. Edition (8. Oktober 2019)
In the preface you can read: “This book is about the past , present , and future of our attempt to understand and create intelligence . This matters , not because AI is rapidly becoming a pervasive aspect of the present but because it is the dominant technology of the future . The world’s great powers are waking up to this fact , and the world’s largest corporations have known it for some time . We cannot predict exactly how the technology will develop or on what timeline . Nevertheless , we must plan for the possibility that machines will far exceed the human capacity for decision making in the real world . What then ? Everything civilization has to offer is the product of our intelligence ; gaining access to considerably greater intelligence would be the biggest event in human history . The purpose of the book is to explain why it might be the last event in human history and how to make sure that it is not .”
[] David Adkins, Bilal Alsallakh, Adeel Cheema, Narine Kokhlikyan, Emily McReynolds, Pushkar Mishra, Chavez Procope, Jeremy Sawruk, Erin Wang, Polina Zvyagina, (2022), Method Cards for Prescriptive Machine-Learning Transparency, 2022 IEEE/ACM 1st International Conference on AI Engineering – Software Engineering for AI (CAIN), CAIN’22, May 16–24, 2022, Pittsburgh, PA, USA, pp. 90 – 100, Association for Computing Machinery, ACM ISBN 978-1-4503-9275-4/22/05, New York, NY, USA, https://doi.org/10.1145/3522664.3528600
In the abstract you can read: “Specialized documentation techniques have been developed to communicate key facts about machine-learning (ML) systems and the datasets and models they rely on. Techniques such as Datasheets, AI FactSheets, and Model Cards have taken a mainly descriptive approach, providing various details about the system components. While the above information is essential for product developers and external experts to assess whether the ML system meets their requirements, other stakeholders might find it less actionable. In particular, ML engineers need guidance on how to mitigate po- tential shortcomings in order to fix bugs or improve the system’s performance. We propose a documentation artifact that aims to provide such guidance in a prescriptive way. Our proposal, called Method Cards, aims to increase the transparency and reproducibil- ity of ML systems by allowing stakeholders to reproduce the models, understand the rationale behind their designs, and introduce adap- tations in an informed way. We showcase our proposal with an example in small object detection, and demonstrate how Method Cards can communicate key considerations that help increase the transparency and reproducibility of the detection model. We fur- ther highlight avenues for improving the user experience of ML engineers based on Method Cards.”
[] John H. Miller, (2022), Ex Machina: Coevolving Machines and the Origins of the Social Universe, The SFI Press Scholars Series, 410 pages Paperback ISBN: 978-1947864429 , DOI: 10.37911/9781947864429
In the announcement of the book you can read: “If we could rewind the tape of the Earth’s deep history back to the beginning and start the world anew—would social behavior arise yet again? While the study of origins is foundational to many scientific fields, such as physics and biology, it has rarely been pursued in the social sciences. Yet knowledge of something’s origins often gives us new insights into the present. In Ex Machina, John H. Miller introduces a methodology for exploring systems of adaptive, interacting, choice-making agents, and uses this approach to identify conditions sufficient for the emergence of social behavior. Miller combines ideas from biology, computation, game theory, and the social sciences to evolve a set of interacting automata from asocial to social behavior. Readers will learn how systems of simple adaptive agents—seemingly locked into an asocial morass—can be rapidly transformed into a bountiful social world driven only by a series of small evolutionary changes. Such unexpected revolutions by evolution may provide an important clue to the emergence of social life.”
In the abstract you can read: “Analyzing the spatial and temporal properties of information flow with a multi-century perspective could illuminate the sustainability of human resource-use strategies. This paper uses historical and archaeological datasets to assess how spatial, temporal, cognitive, and cultural limitations impact the generation and flow of information about ecosystems within past societies, and thus lead to tradeoffs in sustainable practices. While it is well understood that conflicting priorities can inhibit successful outcomes, case studies from Eastern Polynesia, the North Atlantic, and the American Southwest suggest that imperfect information can also be a major impediment to sustainability. We formally develop a conceptual model of Environmental Information Flow and Perception (EnIFPe) to examine the scale of information flow to a society and the quality of the information needed to promote sustainable coupled natural-human systems. In our case studies, we assess key aspects of information flow by focusing on food web relationships and nutrient flows in socio-ecological systems, as well as the life cycles, population dynamics, and seasonal rhythms of organisms, the patterns and timing of species’ migration, and the trajectories of human-induced environmental change. We argue that the spatial and temporal dimensions of human environments shape society’s ability to wield information, while acknowledging that varied cultural factors also focus a society’s ability to act on such information. Our analyses demonstrate the analytical importance of completed experiments from the past, and their utility for contemporary debates concerning managing imperfect information and addressing conflicting priorities in modern environmental management and resource use.”
In the uffmm review section the different papers and books are discussed from the point of view of the oksimo paradigm, which is embedded in the general view of a generalized ‘citizen science’ as a ‘computer aided sustainable applied empirical theory’ (CSAET). In the following text the author discusses the introduction of the book “Theory of Sets” from the series “Elements of Mathematics” by N.Bourbaki (1968) [1b]
CONTEXT
In the foundational post with the title “From SYSTEMS Engineering to THEORY Engineering” [3] the assumptions of the whole formalization approach in logic, mathematics and science are questioned as to narrow to allow a modern sustainable theory of science dealing explicitly with the future. To sharpen some of the arguments in that post it seems to be helpful to discuss one of the cornerstones of modern (formalized) mathematics substantiated in the book ‘Theory of sets’ from the Bourbaki group.[1a] It has to be mentioned that the question of the insufficiency of formalization has been discussed in the uffmm blog in several posts before. (cf. e.g. [2])
Formalization
preface
In the introduction to the ‘Set Theory Book’ the bourbaki group reveals a little bit of their meta-mathematical point of view, which finally belongs to the perspective of philosophy. At the one hand they try to be ‘radically formal’, but doing this they notice themselves that this is — by several reasons — only a ‘regulative idea’, somehow important for our thinking, but not completely feasible. This ‘practical impossibility’ is not necessarily a problem as long as one is conscious about this. The Bourbaki group is conscious about this problem, but different to their ‘rigor’ with the specialized formalization of mathematical ideas, they leave it widely ‘undefined’ what follows from the practical impossibility of being ‘completely rigorous’. In the following text it will be tried to describe the Bourbaki position with both dimensions: the idea of ‘formalization’ and the reality of ‘non-formalized realities’ which give the ‘ground’ for everything, even for the formalization. Doing this it will — hopefully — become clear that the idea of formalization was a great achievement in the philosophical and scientific thinking but it did not really solve our problems of understanding the world. The most important aspects of knowledge are ‘outside’ of this formalization approach, and many ‘problems’ which seem to bother our actual thinking are perhaps only ‘artifacts’ of this simplified formalization approach (somehow similar to the problems which have been induced by the metaphysical thinking of the older philosophy). To say it flatly: to introduce new names for old problems does not necessarily solve problems. It enables new ways of speaking and perhaps some new kinds of knowledge, but it does not really solve the big problems of knowledge. And the biggest problem of knowledge is — perhaps — the primary ‘knowledge machine’ itself: the biological actors which have brains to transform ‘reality’ in ‘virtual models’ in their brains and communication tools to ‘communicate’ these virtual models to enable a ‘collective intelligence’ as well as a ‘collective cooperation’. As long as we do not understand this we do not really understand the ‘process of knowing’.
before formalization
With the advent of the homo sapiens population on the planet earth about 300.000 years ago [4] it became possible that biological systems could transform their perceptions of the reality around their brains into ‘internal’, ‘virtual’ models, which enabled ‘reference points’ for ‘acting’ and a ‘cooperation’ which was synchronized by a ‘symbolic communication’. Those properties of the internal virtual models which have no clear ‘correspondence’ to the ‘reality between the brains’ are difficult to communicate.
Everyday symbolic communication refers to parts of the reality by certain types of expressions, which are ‘combined’ in manners which encode different types of ‘relations’ or even ‘changes’. Expressions which ‘refer’ to ‘concrete’ properties can be ‘overloaded’ by expressions which refer to other expressions, which in turn refer either again to expressions or to ‘concrete meanings’. Those objects which are the targets of a referring relation — concrete objects or other expressions — are here called ‘the meaning’ of the expressions. Thus the ‘meaning space’ is populated by either expressions related to ‘concrete’ properties or by ‘expressions pointing forward’ to other expressions and these ‘pointing-forward’ expressions are here called ‘abstract meaning’. While concrete meanings are usually ‘decidable’ in the everyday world situations as being ‘given’ (being ‘true’) or as ‘not being given’ (‘being false’), abstract meanings are as expressions ‘undefined’: they can lead to some concrete property which in turn perhaps can be decided or not.
The availability of ‘abstract expressions’ in ordinary language can be seen as a ‘problem’ or as a ‘blessing’. Being able to generate and use abstract terms manifests a great flexibility in talking — and thinking! — about possible realities which allow to overcome the dictatorship of the ‘now’ and the ‘individual single’. Without abstraction thinking would indeed be impossible. Thus if one understands that ‘thinking’ is a real process with sequences of different states which reveal eventually more abstract classes, structures, and changes, then abstraction is the ‘opener’ for more reality, the ‘enabler’ for a more broader and flexible knowledge. Only by ‘transcending’ the eternal ‘Now’ we get an access to phenomena like time, changes, all kinds of dynamics, and only thereby are ‘pictures of some possible future’ feasible!
Clearly, the potential of abstraction can also be a source of ‘non-real’ ideas, of ‘fantastic’ pictures, of ‘fake news’ and the like.
But these possible ‘failures’ — if they will be ‘recognized’ as failures! — are inevitable if one wants to dig out some ‘truth’ in the nearly infinite space of the unknown. Before the ‘knowledge that something is true’ one has to master a ‘path of trial and error’ consuming ‘time’ and ‘resources’.
This process of creating new abstract ideas to guide a search in the space of the unknown is the only key to find besides ‘errors’ sometimes some ‘truth’.
Thus the ‘problem’ with abstract ideas is an unavoidable condition to find necessary ‘truths’. Stepping back in the face of possible problems is no option to survive in the unknown future.
the formal view of the world according to bourbaki
Figure 1: Graphical interpretation of N.Bourbaki, Set Theory (1968), Introduction, ‘liberal version’
Language, object language, meta language
Talking about mathematical objects with their properties within an ordinary language is not simple because the expressions of an ordinary language are as such usually part of a network of meanings, which can overlap, which can be fuzzy, which are giving space for many interpretations. Additionally, that which is called a ‘mathematical object’ is not a kind of an object wich is given in the everyday world experience. What can be done in such a situation?
Bourbaki proposes to introduce a ‘specialized language’ constructed out of a finite set of elements constituting the ‘alphabet’ of a new language, together with ‘syntactical rules’, which describe how to construct with the elements of the alphabet chains of elements called ‘(well formed) expressions’, which constitute the ‘language’ LO, which shall be used to talk about mathematical objects.
But because mathematics is not restricted to ‘static objects’ but deals also with ‘transformations’ (‘changes’) of objects, one needs ‘successions of objects’ (‘sequences’), which are related by ‘operations with mathematical objects’. In this case the operations are also represented by ‘expressions’ but these expressions are expressions of a ‘higher order’ which have as referenced subject those expressions which are representing objects . Thus, Bourbaki needs right from the beginning two languages: an ‘object language’ (expressions of a language LO representing mathematical objects) and a ‘meta language’ LL (expressions referring to expressions of the object language LO including certain ‘types of changes’ occurring with the object language expressions). Thus a mathematical language Lm consists in the combination of an object language LO with a meta language LL (Lm = (LO,LL)).
And, what becomes clear by this procedure, to introduce such a kind of mathematical language Lm one needs another language talking about the mathematical language Lm, and this is either the everyday (normal) language L, which is assumed to be a language which everybody can ‘understand’ and ‘apply correctly’, or it is a third specialized language LLL, which can talk with special expressions about the mathematical language Lm. Independent of the decision which solution one prefers, finally the ordinary language L will become the meta language for all other thinkable meta languages.
Translating(?) math objects into formal expressions
If the formalized expressions of the mathematical language (Lm = (LO,LL)) would be the mathematical objects themselves, then mathematics would consist only of those expressions. And, because there would be no other criteria available, whatever expressions one would introduce, every expression would claim to be a relevant mathematical expression. This situation would be a ‘maximum of non-sense’ construct: nothing could be ‘false’.
Thus, the introduction of formal expressions of some language alone seems to be not enough to establish a language which is called a ‘mathematical’ language Lm different from other languages which talk about other kinds of objects. But what could it be which relates to ‘specific math objects’ which are not yet the expressions used to ‘refer’ to these specific math objects?
Everybody knows that the main reason for to ‘speak’ (or ‘write’) about math specific objects are humans which are claiming to be ‘mathematicians’ and which are claiming to have some ‘knowledge’ about specific objects called ‘math objects’ which are the ‘content’ which they ‘translate’ into the expressions of a certain language call ‘mathematical language’.[5] Thus, if the ‘math objects’ are not the used expressions themselves then these ‘math objects’ have to be located ‘inside of these talking humans’. According to modern science one would specify this ‘inside’ as ‘brain’, which is connected in complex ways to a body which in turn is connected to the ‘outside world of the body’. Until today it is not possible to ‘observe’ directly math objects assumed to be in the brain of the body of someone which claims to be a mathematician. Thus one mathematician A can not decide what another mathematician B has ‘available in his brain’ at some point of time.
Bourbaki is using some formulations in his introduction which gives some ‘flavor’ of this ‘being not able to translate it into a formalized mathematical language’. Thus at one position in the text Bourbaki is recurring to the “common sense” of the mathematicians [6] or to the “reader’s intuition”. [7] Other phrases refer to the “modes of reasoning” which cannot be formalized [8], or simply to the “experience” on which “the opinion rests”. [9] Expressions like ‘common sense’, ‘intuition’, ‘modes of reasoning’, and ‘experience’ are difficult to interpret. All these expressions describe something ‘inside’ the brains which cannot be observed directly. Thus, how can mathematician A know what mathematician B ‘means’ if he is uttering some statement or writes it down? Does it make a difference whether a mathematician is a man or a woman or is belonging to some other kind of a ‘gender’? Does it make a difference which ‘age’ the mathematician has? How ‘big’ he is? Which ‘weight’ he has?
Thus, from a philosophical point of view the question to the specific criteria which classify a language as a ‘mathematical language’ and not some other language leads us into a completely unsatisfying situation: there are no ‘hard facts’ which can give us a hint what ‘mathematical objects’ could be. What did we ‘overlook’ here? What is the key to the specific mathematical objects which inspired the brains of many many thousand people through centuries and centuries? Is mathematics a ‘big fake’ or is there more than this?
A mathematician as an ‘actor’?
Figure 2: Graphical interpretation of N.Bourbaki, Set Theory (1968), Introduction, ‘Actor view’
This last question “Is mathematics a ‘big fake’ or is there more than this?” can lead o the assumption, that it is not enough to talk about ‘mathematics’ by not including the mathematician itself. Only the mathematician is that ‘mysterious source’ of knowledge, which seems to trigger the production of ‘mathematical expressions’ in speaking or writing (or drawing). Thus a meta-mathematical — and thereby philosophical’ — ‘description’ of mathematics should have at least the ‘components’ (MA, LO,LL,L) with ‘MA’ as abbreviation for the set of actors where each element of the set MA is a mathematician, and — this is decisive ! — it is this math actor MA which is in possession of those ‘criteria’ which decide whether an expression E belongs the ‘mathematical language Lm‘ or not.
The phrase of the ‘mathematician’ as a ‘mysterious source of knowledge’ is justified by an ’empirical observational point of view’: nobody can directly look into the brain of a mathematician. Thus the question of what an expression called ‘mathematical expression’ can ‘mean’ is in such an empirical view not decidable and appears to be a ‘mystery’.
But in the reality of everyday life we can observe, that every human actor — not only mathematicians — seems to be able to use expressions of the everyday language with referring to ‘internal states’ of the brain in a way which seems to ‘work’. If we are talking about ‘pain with my teeth’ or about ‘being hungry or thirsty’ or ‘having an idea’ etc. then usually other human actors seem to ‘understand’ what one is uttering. The ‘evidence’ of a ‘working understanding’ is growing up by the ‘confirmation of expectations’: if oneself is hungry, then one has a certain kind of ‘feeling’ and usually this feeling leads — depending from the cultural patterns one is living in — to a certain kind of ‘behavior’, which has — usually — the ‘felt effect’ of being again ‘not hungry’. This functional relation of ‘feeling to be hungry’, ‘behavior of consuming something’, ‘feeling of being not hungry again’ is an association between ‘bodily functions’ common to all human actors and additionally it is a certain kind of observable behavior, which is common to all human actors too. And it seems to work that human actors are able to associate ‘common internal states’ with ‘common observable behavior’ and associate this observable behavior with the ‘presupposed internal states’ with certain kinds of ‘expressions’. Thus although the internal states are directly not observable, they can become ‘communicated by expressions’ because these internal states are — usually — ‘common to the internal experience of every human actor’.
From this follows the ‘assumption’ that we should extend the necessary elements for ‘inter-actor communication’ with the factor of ‘common human actor HA experience’ abbreviated as ‘HAX‘ (HA, HAX, MA, LO,LL,L), which is usually accompanied by certain kinds of observable behavior ‘BX‘, which can be used as point of reference for certain expressions ‘LX‘, which ‘point to’ the associated intern al states HAX, which are not directly observable. This yields the structure (HA, HAX, MA, BX, LO,LL,LX,L).
Having reached this state of assumptions, there arises an other assumption regarding the relationship between ‘expressions of a language’ — like (LO,LL,LX,L) — and those properties which are constituting the ‘meaning’ of these expressions. In this context ‘meaning’ is not a kind of an ‘object’ but a ‘relation’ between two different things, the expressions at one side and the properties ‘referred to’ on the other side. Moreover this ‘meaning relation’ seems not to be a ‘static’ relation but a ‘dynamic’ one, associating two different kinds of properties one to another. This reminds to that what mathematicians call a ‘mapping, a function’, and the engineers a ‘process, an operation’. If we abbreviate this ‘dynamic meaning relation’ with the sign ‘μ’, then we could agree to the convention ‘μX : LX <—> (BX,HAX)’ saying that there exists a meaning function μX which maps the special expressions of LX to the special internal experience HAX, which in turn is associated with the special behavior BX. Thus, we extend our hypothetical structure to the format (HA, HAX, MA, BX, LO,LL,LX,L,μX).
With these assumptions we are getting a first idea how human actors in general can communicate about internal, directly not observable states, with other human actors by using external language expressions. We have to notice that the assumed dynamic meaning relation μX itself has to be located ‘inside’ the body, inside’ the brain. This triggers the further assumption to have ‘internal counterparts’ of the external observable behavior as well as external expressions. From this follows the further assumption that there must exists some ‘translation/ transformation’ ‘τ’ which ‘maps’ the internal ‘counterparts’ of the observable behavior and the observable expressions into the external behavior.(cf. figure 2) Thus, we are reaching the further extended format: (HA, HAX, MA, BX, LO,LL,LX,L,μX,τ).
Mathematical objects
Accepting the basic assumptions about an internal meaning function μX as well an internal translation function τ narrows the space of possible answers about the nature of ‘math objects’ a little bit, but as such this is possibly not yet a satisfying answer. Or, have we nevertheless yet to assume that ‘math objects’ and related ‘modes of reasoning’ are also rooted in internal properties and dynamics of the brain which are ‘common to all humans’?
If one sees that every aspect of the human world view is encoded in some internal states of the brain, and that what we call ‘world’ is only given as a constructed virtual structure in the brains of bodies including all the different kinds of ‘memories’, then there is no real alternative to the assumption that ‘math objects’ and related ‘modes of reasoning’ have to be located in these — yet not completely decoded — inner structures and dynamics of the brain.
From the everyday experience — additionally enlightened by different scientific disciplines, e.g. experimental (neuro) psychology — we know that the brain is — completely automatic — producing all kinds of ‘abstractions’ from concrete ‘perceptions’, can produce any kinds of ‘abstractions of abstractions’, can ‘associate’ abstractions with other abstractions, can arrange many different kinds of memories to ‘arrangements’ representing ‘states’/ ‘situations’, ‘transformations of states’, ‘sequences of states’ and the like. Thus everything which a ‘mathematical reasoning’ HAm needs seems to be available as concrete brain state or brain activity, and this is not only ‘special’ for an individual person alone, it is the common structure of all brains.
Therefore one has to assume that the set of mathematicians MA is a ‘subset’ of the set of human actors HA in general. From this one can further assume that the ‘mathematical reasoning’ HAm is a subset of the general human everyday experience HAX. And, saying this, the meaning function μX as well as the translation function τ should be applicable also to the mathematical reasoning and the mathematical objects as well: (HA, MA, HAX, HAm, BX, LO,LL,LX,L,μX,τ).
These assumptions would explain why it is not only possible but ‘inevitable’ to use the everyday language L to introduce and to use a mathematical language Lm with different kinds of sub-languages (LO,LL, LLL, …). Thus in analogy to the ‘feeling’ ‘to be hungry’ with a cultural encoded kind of accompanying behavior BX we have to assume that the different kinds of internal states and transformations in the case of mathematical reasoning can be associated with an observable kind of ‘behavior’ by using ‘expressions’ embedded (encoded) in certain kinds of ‘behavior’ accepted as ‘typical mathematical’. Introducing expressions like ‘0’, ‘1’, ‘2’, …, ’10’, … (belonging to a language Lo) for certain kinds of ‘objects’ and expressions like ‘+’, ‘-‘ … for certain kinds of operations with these before introduced objects (belonging to a language LL) one can construct combined expressions like ‘1+2=3’ (belonging to a mathematical language Lm). To introduce ‘more abstract objects’ like ‘sets’, ‘relations’, ‘functions’ etc. which have no direct counterpart in the everyday world does not break the assumptions. The everyday language L operates already only with abstract objects like ‘cup’, ‘dog’, ‘house’ etc. The expression ‘cup’ is an abstract concept, which can easily be associated with any kind of concrete phenomena provided by perceptions introducing ‘sets of different properties’, which allow the construction of ‘subsets of properties’ constituting a kind of ‘signature’ for a certain abstract ‘class’ which only exists in the dynamics of the brain. Thus having a set C named ‘cup’ introduces ‘possible elements’, whose ‘interpretation’ can be realized by associating different kinds of sets of properties provided by ‘sensory perception’. But the ‘memory’ as well as the ‘thinking’ can also provide other kinds of properties which can be used too to construct other ‘classes’.
In this outlined perspective of brain dynamics mathematics appears to be a science which is using these brain dynamics in a most direct way without to recur to the the huge amount of everyday experiences. Thus, mathematical languages (today summarized in that language, which enables the so called ‘set theory’) and mathematical thinking in general seems to reflect the basic machinery of the brain processing directly across all different cultures. Engineers worldwide speaking hundreds of different ‘everyday languages’ can work together by using mathematics as their ‘common language’ because this is their ‘common thinking’ underlying all those different everyday languages.
Being a human means being able to think mathematically … besides many other things which characterizes a human actor.
Epiloge
Basically every ordinary language offers all elements which are necessary for mathematics (mathematics is the kernel of every language). But history illustrates that it can be helpful to ‘extend’ an ordinary language with additional expressions (Lo, LL, LLL, …). But the development of modern mathematics and especially computer science shows increasing difficulties by ‘cutting away’ everyday experience in case of elaborating structures, models, theories in a purely formal manner, and to use these formal structures afterwards to interpret the everyday world. This separates the formal productions from the main part of users, of citizens, leading into a situation where only a few specialist have some ‘understanding’ (usually only partially because the formalization goes beyond the individual capacity of understanding), but all others have no more an understanding at all. This has he flavor of a ‘cultural self-destruction’.
In the mentioned oksimo software as part of a new paradigm of a more advanced citizen science this problem of ‘cultural self-destruction’ is avoided because in the format of a ‘computer aided sustainable applied empirical theory (CSAET) the basic language for investigating possible futures is the ordinary language which can be extend as needed with quantifying properties. The computer is not any more needed for ‘understanding’ but only for ‘supporting’ the ‘usage’ of everyday language expressions. This enables the best of both worlds: human thinking as well as machine operations.
[4] Humans, How many years ago?, see: wkp (en): https://en.wikipedia.org/wiki/Human#:~:text=Homo%20sapiens,-Linnaeus%2C%201758&text=Anatomically%20modern%20humans%20emerged%20around,local%20populations%20of%20archaic%20humans.
[5] The difference between ‘talking’ about math objects and ‘writing’ is usually not thematised in the philosophy of mathematics. Because the ordinary language is the most general ‘meta language’ for all kinds of specialized languages and the primary source of the ordinary language then ‘speaking’ is perhaps not really a ‘trivial’ aspect in understanding the ‘meaning’ of any kind of language.
[6] “But formalized mathematics cannot in practice be written down in full, and therefore we must have confidence in what might be called the common sense of the mathematician …”. (p.11)
[7] “Sometimes we shall use ordinary language more loosely … and by indications which cannot be translated into formalized language and which are designed to help the reader to reconstruct the whole text. Other passages, equally untranslatable into formalized language, are introduced in order to clarify the ideas involved, if necessary by appealing to the reader’s intuition …”(p.11)
[8] “It may happen at some future date that mathematicians will agree to use modes of reasoning which cannot be formalized in the language described here : it would then be necessary, if not to change the language completely, at least to enlarge its rules of syntax.”(p.9)
[9] “To sum up, we believe that mathematics is destined to survive … but we cannot pretend that this opinion rests on anything more than experience.”(p.13)
In a preceding post I have outline the concept of an empirical theory based on a text from Popper 1971. In his article Popper points to a minimal structure of what he is calling an empirical theory. A closer investigation of his texts reveals many questions which should be clarified for a more concrete application of his concept of an empirical theory.
In this post it will be attempted to elaborate the concept of an empirical theory more concretely from a theoretical point of view as well as from an application point of view.
A Minimal Concept of an Empirical Theory
The figure shows the process of (i) observing phenomena, (ii) representing these in expressions of some language L, (iii) elaborating conjectures as hypothetical relations between different observations, (iv) using an inference concept to deduce some forecasts, and (v) compare these forecasts with those observations, which are possible in an assumed situation.
Empirical Basis
As starting point as well as a reference for testing does Popper assume an ’empirical basis’. The question arises what this means.
In the texts examined so far from Popper this is not well described. Thus in this text some ‘assumptions/ hypotheses’ will be formulated to describe some framework which should be able to ‘explain’ what an empirical basis is and how it works.
Experts
Those, who usually are building theories, are scientists, are experts. For a general concept of an ’empirical theory’ it is assumed here that every citizen is a ‘natural expert’.
Environment
Natural experts are living in ‘natural environments’ as part of the planet earth, as part of the solar system, as part of the whole universe.
Language
Experts ‘cooperate’ by using some ‘common language’. Here the ‘English language’ is used; many hundreds of other languages are possible.
Shared Goal (Changes, Time, Measuring, Successive States)
For cooperation it is necessary to have a ‘shared goal’. A ‘goal’ is an ‘idea’ about a possible state in the ‘future’ which is ‘somehow different’ to the given actual situation. Such a future state can be approached by some ‘process’, a series of possible ‘states’, which usually are characterized by ‘changes’ manifested by ‘differences’ between successive states. The concept of a ‘process’, a ‘sequence of states’, implies some concept of ‘time’. And time needs a concept of ‘measuring time’. ‘Measuring’ means basically to ‘compare something to be measured’ (the target) with ‘some given standard’ (the measuring unit). Thus to measure the height of a body one can compare it with some object called a ‘meter’ and then one states that the target (the height of the body) is 1,8 times as large as the given standard (the meter object). In case of time it was during many thousand years customary to use the ‘cycles of the sun’ to define the concept (‘unit’) of a ‘day’ and a ‘night’. Based on this one could ‘count’ the days as one day, two days, etc. and one could introduce further units like a ‘week’ by defining ‘One week compares to seven days’, or ‘one month compares to 30 days’, etc. This reveals that one needs some more concepts like ‘counting’, and associated with this implicitly then the concept of a ‘number’ (like ‘1’, ‘2’, …, ’12’, …) . Later the measuring of time has been delegated to ‘time machines’ (called ‘clocks’) producing mechanically ‘time units’ and then one could be ‘more precise’. But having more than one clock generates the need for ‘synchronizing’ different clocks at different locations. This challenge continues until today. Having a time machine called ‘clock’ one can define a ‘state’ only by relating the state to an ‘agreed time window’ = (t1,t2), which allows the description of states in a successive timely order: the state in the time-window (t1,t2) is ‘before’ the time-window (t2,t3). Then one can try to describe the properties of a given natural environment correlated with a certain time-window, e.g. saying that the ‘observed’ height of a body in time-window w1 was 1.8 m, in a later time window w6 the height was still 1.8 m. In this case no changes could be observed. If one would have observed at w6 1.9 m, then a difference is occurring by comparing two successive states.
Example: A County
Here we will assume as an example for a natural environment a ‘county’ in Germany called ‘Main-Kinzig Kreis’ (‘Kreis’ = ‘county’), abbreviated ‘MKK’. We are interested in the ‘number of citizens’ which are living in this county during a certain time-window, here the year 2018 = (1.January 2018, 31.December 2018). According to the statistical office of the state of Hessen, to which the MKK county belongs, the number of citizens in the MKK during 2018 was ‘418.950’.(cf. [2])
Observing the Number of Citizens
One can ask in which sense the number ‘418.950’ can be understood as an ‘observation statement’? If we understand ‘observation’ as the everyday expression for ‘measuring’, then we are looking for a ‘procedure’ which allows us to ‘produce’ this number ‘418.950’ associated with the unit ‘number of citizens during a year’. As everybody can immediately realize no single person can simply observe all citizens of that county. To ‘count’ all citizens in the county one had to ‘travel’ to all places in the county where citizens are living and count every person. Such a travelling would need some time. This can easily need more than 40 years working 24 hours a day. Thus, this procedure would not work. A different approach could be to find citizens in every of the 24 cities in the MKK [1] to help in this counting-procedure. To manage this and enable some ‘quality’ for the counting, this could perhaps work. An interesting experiment. Here we ‘believe’ in the number of citizens delivered by the statistical office of the state of Hessen [2], but keeping some reservation for the question how ‘good’ this number really is. Thus our ‘observation statement’ would be: “In the year 2018 418.950 citizens have been counted in the MKK (according to the information of the statistical office of the state of Hessen)” This observation statement lacks a complete account of the procedure, how this counting really happened.
Concrete and Abstract Words
There are interesting details in this observation statement. In this observation statement we notice words like ‘citizen’ and ‘MKK’. To talk about ‘citizens’ is not a talk about some objects in the direct environment. What we can directly observe are concrete bodies which we have learned to ‘classify’ as ‘humans’, enriched for example with ‘properties’ like ‘man’, ‘woman’, ‘child’, ‘elderly person’, neighbor’ and the like. Bu to classify someone as a ‘citizen’ deserves knowledge about some official procedure of ‘registering as a citizen’ at a municipal administration recorded in some certified document. Thus the word ‘citizen’ has a ‘meaning’ which needs some ‘concrete procedure to get the needed information’. Thus ‘citizen’ is not a ‘simple word’ but a ‘more abstract word’ with regard to the associated meaning. The same holds for the word ‘MKK’ short for ‘Main-Kinzig Kreis’. At a first glance ‘MKK’ appears as a ‘name’ for some entity. But this entity cannot directly be observed too. One component of the ‘meaning’ of the name ‘MKK’ is a ‘real geographical region’, whose exact geographic extensions have been ‘measured’ by official institutions marked in an ‘official map’ of the state of Hessen. This region is associated with an official document of the state of Hessen telling, that this geographical region has to be understood s a ‘county’ with the name MKK. There exist more official documents defining what is meant with the word ‘county’. Thus the word ‘MKK’ has a rather complex meaning which to understand and to check, whether everything is ‘true’, isn’t easy. The author of this post is living in the MKK and he would not be able to tell all the details of the complete meaning of the name ‘MKK’.
First Lessons Learned
Thus one can learn from these first considerations, that we as citizens are living in a natural environment where we are using observation statements which are using words with potentially rather complex meanings, which to ‘check’ deserves some serious amount of clarification.
Conjectures – Hypotheses
Changes
The above text shows that ‘observations as such’ show nothing of interest. Different numbers of citizens in different years have no ‘message’. But as soon as one arranges the years in a ‘time line’ according to some ‘time model’ the scene is changing: if the numbers of two consecutive years are ‘different’ then this ‘difference in numbers’ can be interpreted as a ‘change’ in the environment, but only if one ‘assumes’ that the observed phenomena (the number of counted citizens) are associated with some real entities (the citizens) whose ‘quantity’ is ‘represented’ in these numbers.[5]
And again, the ‘difference between consecutive numbers’ in a time line cannot be observed or measured directly. It is a ‘second order property’ derived from given measurements in time. Such a 2nd order property presupposes a relationship between different observations: they ‘show up’ in the expressions (here numbers), but they are connected back in the light of the agreed ‘meaning’ to some ‘real entities’ with the property ‘overall quantity’ which can change in the ‘real setting’ of these real entities called ‘citizens’.
In the example of the MKK the statistical office of the state of Hessen computed a difference between two consecutive years which has been represented as a ‘growth factor’ of 0,4%. This means that the number of citizens in the year 2018 will increase until the year 2019 as follows: number-citizens(2019) = number-citizens(2018) + (number of citizens(2018) * growth-factor). This means number-citizens(2019) =418.950 + (418.950 * 0.004) = 418.950 + 1.675,8 = 420.625,8
Applying change repeatedly
If one could assume that the ‘growth rate’ would stay constant through the time then one could apply the growth rate again and again onto the actual number of citizens in the MKK every year. This would yield the following simple table:
Year
Number
Growth Rate
2018
418.950,00
,0040
2019
420.625,80
2020
422.308,30
2021
423.997,54
2022
425.693,53
2023
427.396,30
Table: Simplified description of the increase of the number of citizens in the Main-Kinzig county in Germany with an assumed growth rate of 0,4% per year.
As we know from reality an assumption of a fixed growth rate for complex dynamic systems is not very probable.
Theory
Continuing the previous considerations one has to ask the question, how the layout of a ‘complete empirical theory’ would look like?
As I commented in the preceding post about Popper’s 1971 article about ‘objective knowledge’ there exists today no one single accepted framework for a formalized empirical theory. Therefore I will stay here with a ‘bottom-up’ approach using elements taken from everyday reasoning.
What we have until now is the following:
Before the beginning of a theory building process one needs a group of experts being part of a natural environment using the samelanguage which share a common goal which they want to enable.
The assumed natural environment is assumed from the experts as being a ‘process’ of consecutive states in time. The ‘granularity’ of the process depends from the used ‘time model’.
As a starting point they collect a set of statements talking about those aspects of a ‘selected state’ at some time t which they are interested in.
This set of statements describes a set of ‘observable properties’ of the selected state which is understood as a ‘subset’ of the properties of the natural environment.
Every statement is understood by the experts as being ‘true’ in the sense, that the ‘known meaning’ of a statement has an ‘observable counterpart’ in the situation, which can be ‘confirmed’ by each expert.
For each pair of consecutive states it holds that the set of statements of each state can be ‘equal’ or ‘can show ‘differences’.
A ‘difference’ between sets of statements can be interpreted as pointing to a ‘change in the real environment’.[5]
Observed differences can be described by special statements called ‘change statements’ or simply ‘rules’.
A change statement has the format ‘IF a set of statements ST* is a subset of the statements ST of a given state S, THEN with probability p, a set of statements ST+ will be added to the actual state S and a set of statements ST- will be removed from the statements ST of a given state S. This will result in a new succeeding state S* with the representing statements ST – (ST-) + (ST+) depending from the assumed probability p.
The list of change statements is an ‘open set’ according to the assumption, that an actual state is only a ‘subset’ of the real environment.
Until now we have an assumed state S, an assumed goal V, and an open set of change statements X.
Applying change statements to a given state S will generate a new state S*. Thus the application of a subset X’ of the open set of change statements X onto a given state S will here be called ‘generating a new state by a procedure’. Such a state-generating-procedure can be understood as an ‘inference’ (like in logic) oder as a ‘simulation’ (like in engineering).[6]
To write this in a more condensed format we can introduce some signs —– S,V ⊩ ∑ X S‘ —– saying: If I have some state S and a goal V then the simulator ∑ will according to the change statements X generate a new state S’. In such a setting the newly generated state S’ can be understood as a ‘theorem’ which has been derived from the set of statements in the state S which are assumed to be ‘true’. And because the derived new state is assumed to happen in some ‘future’ ‘after’ the ‘actual state S’ this derived state can also be understood as a ‘forecast’.
Because the experts can change all the time all parts ‘at will’ such a ‘natural empirical theory’ is an ‘open entity’ living in an ongoing ‘communication process’.
Second Lessons Learned
It is interestingly to know that from the set of statements in state S, which are assumed to be empirically true, together with some change statements X, whose proposed changes are also assumed to be ‘true’, and which have some probability P in the domain [0,1], one can forecast a set of statements in the state S* which shall be true, with a certainty being dependent from the preceding probability P and the overall uncertainty of the whole natural environment.
Confirmation – Non-Confirmation
A Theory with Forecasts
Having reached the formulation of an ordinary empirical theory T with the ingredients <S,V,X,⊩ ∑> and the derivation conceptS,V ⊩ ∑ X S‘ it is possible to generate theorems as forecasts. A forecast here is not a single statement st* but a whole state S* consisting of a finite set of statements ST* which ‘designate’ according to the ‘agreed meaning’ a set of ‘intended properties’ which need a set of ‘occurring empirical properties’ which can be observed by the experts. These observations are usually associated with ‘agreed procedures of measurement’, which generate as results ‘observation statements’/ ‘measurement statements’.
Within Time
Experts which are cooperating by ‘building’ an ordinary empirical theory are themselves part of a process in time. Thus making observations in the time-window (t1,t2) they have a state S describing some aspects of the world at ‘that time’ (t1,t2). When they then derive a forecast S* with their theory this forecast describes — with some probability P — a ‘possible state of the natural environment’ which is assumed to happen in the ‘future’. The precision of the predicted time when the forecasted statements in S* should happen depends from the assumptions in S.
To ‘check’ the ‘validity’ of such a forecast it is necessary that the overall natural process reaches a ‘point in time’ — or a time window — indicated by the used ‘time model’, where the ‘actual point in time’ is measured by an agreed time machine (mechanical clock). Because there is no observable time without a time machine the classification of a certain situation S* being ‘now’ at the predicted point of time depends completely from the used time machine.[7]
Given this the following can happen: According to the used theory a certain set of statements ST* is predicted to be ‘true’ — with some probability — either ‘at some time in the future’ or in the time-window (t1,t2) or at a certain point in time t*.
Validating Forecasts
If one of these cases would ‘happen’ then the experts would have the statements ST* of their forecast and a real situation in their natural environment which enables observations ‘Obs’ which are ‘translated’ into appropriate ‘observation statements’ STObs. The experts with their predicted statements ST* know a learned agreed meaning M* of their predicted statements ST* as intended-properties M* of ST*. The experts have also learned how they relate the intended meaning M* to the meaning MObs from the observation statements STobs. If the observed meaning MObs ‘agrees sufficiently well’ with the intended meaning M* then the experts would agree in a statement, that the intended meaning M* is ‘fulfilled’/ ‘satisfied’/ ‘confirmed’ by the observed meaning MObs. If not then it would stated that it is ‘not fulfilled’/ ‘not satisfied’/ ‘not confirmed’.
The ‘sufficient fulfillment’ of the intended meaning M* of a set of statements ST* is usually translated in a statement like “The statements ST* are ‘true'”. In the case of ‘no fulfillment’ it is unclear: this can be interpreted as ‘being false’ or as ‘being unclear’: No clear case of ‘being true’ and no clear case of ‘being false’.
Forecasting the Number of Citizens
In the used simple example we have the MKK county with an observed number of citizens in 2018 with 418950. The simple theory used a change statement with a growth factor of 0.4% per year. This resulted in the forecast with the number 420.625 citizens for the year 2019.
If the newly counting of the number of citizens in the years 2019 would yield 420.625, then there would be a perfect match, which could be interpreted as a ‘confirmation’ saying that the forecasted statement and the observed statement are ‘equal’ and therefore the theory seems to match the natural environment through the time. One could even say that the theory is ‘true for the observed time’. Nothing would follow from this for the unknown future. Thus the ‘truth’ of the theory is not an ‘absolute’ truth but a truth ‘within defined limits’.
We know from experience that in the case of forecasting numbers of citizens for some region — here a county — it is usually not so clear as it has been shown in this example.
This begins with the process of counting. Because it is very expensive to count the citizens of all cities of a county this happens only about every 20 years. In between the statistical office is applying the method of ‘forecasting projection’.[9] The state statistical office collects every year ‘electronically’ the numbers of ‘birth’, ‘death’, ‘outflow’, and ‘inflow’ from the individual cities and modifies with these numbers the last real census. In the case of the state of Hessen this was the year 2011. The next census in Germany will happen May 2022.[10] For such a census the data will be collected directly from the registration offices from the cities supported by a control survey of 10% of the population.
Because there are data from the statistical office of the state of Hessen for June 2021 [8:p.9] with saying that the MKK county had 421 936 citizens at 30. June 2021 we can compare this number with the theory forecast for the year 2021 with 423 997. This shows a difference in the numbers. The theory forecast is ‘higher’ than the observed forecast. What does this mean?
Purely arithmetically the forecast is ‘wrong’. The responsible growth factor is too large. If one would ‘adjust’ it in a simplified linear way to ‘0.24%’ then the theory could get a forecast for 2021 with 421 973 (observed: 421 936), but then the forecast for 2019 would be 419 955 (instead of 420 625).
This shows at least the following aspects:
The empirical observations as such can vary ‘a little bit’. One had to clarify which degree of ‘variance’ is due to the method of measurement and therefore this variance should be taken into account for the evaluation of a theoretical forecast.
As mentioned by the statistical office [9] there are four ‘factors’ which influence the final number of citizens in a region: ‘birth’, ‘death’, ‘outflow’, and ‘inflow’. These factors can change in time. Under ‘normal conditions’ the birth-rate and the death-rate are rather ‘stable’, but in case of an epidemic situation or even war this can change a lot. Outflow and inflow are very dynamic depending from many factors. Thus this can influence the growth factor a lot and these factors are difficult to forecast.
Third lessons Learned
Evaluating the ‘relatedness’ of some forecast F of an empirical theory T to the observations O in a given real natural environment is not a ‘clear-cut’ case. The ‘precision’ of such a relatedness depends from many factors where each of these factors has some ‘fuzziness’. Nevertheless as experience shows it can work in a limited way. And, this ‘limited way’ is the maximum we can get. The most helpful contribution of an ‘ordinary empirical theory’ seems to be the forecast of ‘What will happen if we have a certain set of assumptions’. Using such a forecast in the process of the experts this can help to improve to get some ‘informed guesses’ for planning.
Forecast
The next post will show, how this concept of an ordinary empirical theory can be used by applying the oksimo paradigm to a concrete case. See HERE.
Comments
[1] Cities of the MKK-county: 24, see: https://www.wegweiser-kommune.de/kommunen/main-kinzig-kreis-lk
[3] Karl Popper, „A World of Propensities“,(1988) and „Towards an Evolutionary Theory of Knowledge“, (1989) in: Karl Popper, „A World of Propensities“, Thoemmes Press, Bristol, (1990, repr. 1995)
[4] Karl Popper, „All Life is Problem Solving“, original a lecture 1991 in German, the first tome published (in German) „Alles Leben ist Problemlösen“ (1994), then in the book „All Life is Problem Solving“, 1999, Routledge, Taylor & Francis Group, London – New York
[5] This points to the concept of ‘propensity’ which the late Popper has discussed in the papers [3] and [4].
[6] This concept of a ‘generator’ or an ‘inference’ reminds to the general concept of Popper and the main stream philosophy of a logical derivation concept where a ‘set of logical rules’ defines a ‘derivation concept’ which allows the ‘derivation/ inference’ of a statement s* as a ‘theorem’ from an assumed set of statements S assumed to be true.
[7] The clock-based time is in the real world correlated with certain constellations of the real universe, but this — as a whole — is ‘changing’!
[8] Hessisches Statistisches Landesamt, “Die Bevölkerung der hessischen Gemeinden am 30. Juni 2021. Fortschreibungsergebnisse Basis Zensus 09. Mai 2011″, Okt. 2021, Wiesbaden, URL: https://statistik.hessen.de/sites/statistik.hessen.de/files/AI2_AII_AIII_AV_21-1hj.pdf
[9] Method of the forward projection of the statistical office of the State of Hessen: “Bevölkerung: Die Bevölkerungszahlen sind Fortschreibungsergebnisse, die auf den bei der Zensuszählung 2011 ermittelten Bevölkerungszahlen basieren. Durch Auswertung von elektronisch übermittelten Daten für Geburten und Sterbefälle durch die Standesämter, sowie der Zu- und Fortzüge der Meldebehörden, werden diese nach einer bundeseinheitlichen Fortschreibungsmethode festgestellt. Die Zuordnung der Personen zur Bevölkerung einer Gemeinde erfolgt nach dem Hauptwohnungsprinzip (Bevölkerung am Ort der alleinigen oder der Hauptwohnung).”([8:p.2]
[10] Statistical Office state of Hessen, Next census 2022: https://statistik.hessen.de/zahlen-fakten/zensus/zensus-2022/zensus-2022-kurz-erklaert
This text is part of a philosophy of science analysis of the case of the oksimo software (oksimo.com). A specification of the oksimo software from an engineering point of view can be found in four consecutive posts dedicated to the HMI-Analysis for this software.
POPPERs POSITION IN THE CHAPTERS 1-17
In my reading of the chapters 1-17 of Popper’s The Logic of Scientific Discovery [1] I see the following three main concepts which are interrelated: (i) the concept of a scientific theory, (ii) the point of view of a meta-theory about scientific theories, and (iii) possible empirical interpretations of scientific theories.
Scientific Theory
A scientific theory is according to Popper a collection of universal statements AX, accompanied by a concept of logical inference ⊢, which allows the deduction of a certain theorem t if one makes some additional concrete assumptions H.
Example: Theory T1 = <AX1,⊢>
AX1= {Birds can fly}
H1= {Peter is a bird}
⊢: Peter can fly
Because there exists a concrete object which is classified as a bird and this concrete bird with the name ‘Peter’ can fly one can infer that the universal statement could be verified by this concrete bird. But the question remains open whether all observable concrete objects classifiable as birds can fly.
One could continue with observations of several hundreds of concrete birds but according to Popper this would not prove the theory T1 completelytrue. Such a procedure can only support a numerical universality understood as a conjunction of finitely many observations about concrete birds like ‘Peter can fly’ & ‘Mary can fly’ & …. &’AH2 can fly’.(cf. p.62)
The only procedure which is applicable to a universal theory according to Popper is to falsify a theory by only one observation like ‘Doxy is a bird’ and ‘Doxy cannot fly’. Then one could construct the following inference:
AX1= {Birds can fly}
H2= {Doxy is a bird, Doxy cannot fly}
⊢: ‘Doxy can fly’ & ~’Doxy can fly’
If a statement A can be inferred and simultaneously the negation ~A then this is called a logical contradiction:
{AX1, H2} ⊢‘Doxy can fly’ & ~’Doxy can fly’
In this case the set {AX1, H2} is called inconsistent.
If a set of statements is classified as inconsistent then you can derive from this set everything. In this case you cannot any more distinguish between true or false statements.
Thus while the increase of the number of confirmed observations can only increase the trust in the axioms of a scientific theory T without enabling an absolute proof a falsification of a theory T can destroy the ability of this theory to distinguish between true and false statements.
Another idea associated with this structure of a scientific theory is that the universal statements using universal concepts are strictly speaking speculative ideas which deserve some faith that these concepts will be provable every time one will try it.(cf. p.33, 63)
Meta Theory, Logic of Scientific Discovery, Philosophy of Science
Talking about scientific theories has at least two aspects: scientific theories as objects and those who talk about these objects.
Those who talk about are usually Philosophers of Science which are only a special kind of Philosophers, e.g. a person like Popper.
Reading the text of Popper one can identify the following elements which seem to be important to describe scientific theories in a more broader framework:
A scientific theory from a point of view of Philosophy of Science represents a structure like the following one (minimal version):
MT=<S, A[μ], E, L, AX, ⊢, ET, E+, E-, true, false, contradiction, inconsistent>
In a shared empirical situation S there are some human actors A as experts producing expressions E of some language L. Based on their built-in adaptive meaning function μ the human actors A can relate properties of the situation S with expressions E of L. Those expressions E which are considered to be observable and classified to be true are called true expressions E+, others are called false expressions E-. Both sets of expressions are true subsets of E: E+ ⊂ E and E- ⊂ E. Additionally the experts can define some special set of expressions called axioms AX which are universal statements which allow the logical derivation of expressions called theorems of the theory T ET which are called logically true. If one combines the set of axioms AX with some set of empirically true expressions E+ as {AX, E+} then one can logically derive either only expressions which are logically true and as well empirically true, or one can derive logically true expressions which are empirically true and empirically false at the same time, see the example from the paragraph before:
{AX1, H2} ⊢‘Doxy can fly’ & ~’Doxy can fly’
Such a case of a logically derived contradiction A and ~A tells about the set of axioms AX unified with the empirical true expressions that this unified set confronted with the known true empirical expressions is becoming inconsistent: the axioms AX unified with true empirical expressions can not distinguish between true and false expressions.
Popper gives some general requirements for the axioms of a theory (cf. p.71):
Axioms must be free from contradiction.
The axioms must be independent , i.e . they must not contain any axiom deducible from the remaining axioms.
The axioms should be sufficient for the deduction of all statements belonging to the theory which is to be axiomatized.
While the requirements (1) and (2) are purely logical and can be proved directly is the requirement (3) different: to know whether the theory covers all statements which are intended by the experts as the subject area is presupposing that all aspects of an empirical environment are already know. In the case of true empirical theories this seems not to be plausible. Rather we have to assume an open process which generates some hypothetical universal expressions which ideally will not be falsified but if so, then the theory has to be adapted to the new insights.
Empirical Interpretation(s)
Popper assumes that the universal statements of scientific theories are linguistic representations, and this means they are systems of signs or symbols. (cf. p.60) Expressions as such have no meaning. Meaning comes into play only if the human actors are using their built-in meaning function and set up a coordinated meaning function which allows all participating experts to map properties of the empirical situation S into the used expressions as E+ (expressions classified as being actually true), or E- (expressions classified as being actually false) or AX (expressions having an abstract meaning space which can become true or false depending from the activated meaning function).
Examples:
Two human actors in a situation S agree about the fact, that there is ‘something’ which they classify as a ‘bird’. Thus someone could say ‘There is something which is a bird’ or ‘There is some bird’ or ‘There is a bird’. If there are two somethings which are ‘understood’ as being a bird then they could say ‘There are two birds’ or ‘There is a blue bird’ (If the one has the color ‘blue’) and ‘There is a red bird’ or ‘There are two birds. The one is blue and the other is red’. This shows that human actors can relate their ‘concrete perceptions’ with more abstract concepts and can map these concepts into expressions. According to Popper in this way ‘bottom-up’ only numerical universal concepts can be constructed. But logically there are only two cases: concrete (one) or abstract (more than one). To say that there is a ‘something’ or to say there is a ‘bird’ establishes a general concept which is independent from the number of its possible instances.
These concrete somethings each classified as a ‘bird’ can ‘move’ from one position to another by ‘walking’ or by ‘flying’. While ‘walking’ they are changing the position connected to the ‘ground’ while during ‘flying’ they ‘go up in the air’. If a human actor throws a stone up in the air the stone will come back to the ground. A bird which is going up in the air can stay there and move around in the air for a long while. Thus ‘flying’ is different to ‘throwing something’ up in the air.
The expression ‘A bird can fly’ understood as an expression which can be connected to the daily experience of bird-objects moving around in the air can be empirically interpreted, but only if there exists such a mapping called meaning function. Without a meaning function the expression ‘A bird can fly’ has no meaning as such.
To use other expressions like ‘X can fly’ or ‘A bird can Y’ or ‘Y(X)’ they have the same fate: without a meaning function they have no meaning, but associated with a meaning function they can be interpreted. For instance saying the the form of the expression ‘Y(X)’ shall be interpreted as ‘Predicate(Object)’ and that a possible ‘instance’ for a predicate could be ‘Can Fly’ and for an object ‘a bird’ then we could get ‘Can Fly(a Bird)’ translated as ‘The object ‘a Bird’ has the property ‘can fly” or shortly ‘A Bird can fly’. This usually would be used as a possible candidate for the daily meaning function which relates this expression to those somethings which can move up in the air.
Axioms and Empirical Interpretations
The basic idea with a system of axioms AX is — according to Popper — that the axioms as universal expressions represent a system of equations where the general terms should be able to be substituted by certain values. The set of admissible values is different from the set of inadmissible values. The relation between those values which can be substituted for the terms is called satisfaction: the values satisfy the terms with regard to the relations! And Popper introduces the term ‘model‘ for that set of admissible terms which can satisfy the equations.(cf. p.72f)
But Popper has difficulties with an axiomatic system interpreted as a system of equations since it cannot be refuted by the falsification of its consequences ; for these too must be analytic.(cf. p.73) His main problem with axioms is, that “the concepts which are to be used in the axiomatic system should be universal names, which cannot be defined by empirical indications, pointing, etc . They can be defined if at all only explicitly, with the help of other universal names; otherwise they can only be left undefined. That some universal names should remain undefined is therefore quite unavoidable; and herein lies the difficulty…” (p.74)
On the other hand Popper knows that “…it is usually possible for the primitive concepts of an axiomatic system such as geometry to be correlated with, or interpreted by, the concepts of another system , e.g . physics …. In such cases it may be possible to define the fundamental concepts of the new system with the help of concepts which were originally used in some of the old systems .”(p.75)
But the translation of the expressions of one system (geometry) in the expressions of another system (physics) does not necessarily solve his problem of the non-empirical character of universal terms. Especially physics is using also universal or abstract terms which as such have no meaning. To verify or falsify physical theories one has to show how the abstract terms of physics can be related to observable matters which can be decided to be true or not.
Thus the argument goes back to the primary problem of Popper that universal names cannot not be directly be interpreted in an empirically decidable way.
As the preceding examples (1) – (4) do show for human actors it is no principal problem to relate any kind of abstract expressions to some concrete real matters. The solution to the problem is given by the fact that expressions E of some language L never will be used in isolation! The usage of expressions is always connected to human actors using expressions as part of a language L which consists together with the set of possible expressions E also with the built-in meaning function μ which can map expressions into internal structures IS which are related to perceptions of the surrounding empirical situation S. Although these internal structures are processed internally in highly complex manners and are — as we know today — no 1-to-1 mappings of the surrounding empirical situation S, they are related to S and therefore every kind of expressions — even those with so-called abstract or universal concepts — can be mapped into something real if the human actors agree about such mappings!
Example:
Lets us have a look to another example.
If we take the system of axioms AX as the following schema: AX= {a+b=c}. This schema as such has no clear meaning. But if the experts interpret it as an operation ‘+’ with some arguments as part of a math theory then one can construct a simple (partial) model m as follows: m={<1,2,3>, <2,3,5>}. The values are again given as a set of symbols which as such must not ave a meaning but in common usage they will be interpreted as sets of numbers which can satisfy the general concept of the equation. In this secondary interpretation m is becoming a logically true (partial) model for the axiom Ax, whose empirical meaning is still unclear.
It is conceivable that one is using this formalism to describe empirical facts like the description of a group of humans collecting some objects. Different people are bringing objects; the individual contributions will be reported on a sheet of paper and at the same time they put their objects in some box. Sometimes someone is looking to the box and he will count the objects of the box. If it has been noted that A brought 1 egg and B brought 2 eggs then there should according to the theory be 3 eggs in the box. But perhaps only 2 could be found. Then there would be a difference between the logically derivedforecast of the theory 1+2 = 3 and the empirically measured value 1+2 = 2. If one would define all examples of measurement a+b=c’ as contradiction in that case where we assume a+b=c as theoretically given and c’ ≠ c, then we would have with ‘1+2 = 3′ & ~’1+2 = 3’ a logically derived contradiction which leads to the inconsistency of the assumed system. But in reality the usual reaction of the counting person would not be to declare the system inconsistent but rather to suggest that some unknown actor has taken against the agreed rules one egg from the box. To prove his suggestion he had to find this unknown actor and to show that he has taken the egg … perhaps not a simple task … But what will the next authority do: will the authority belief the suggestion of the counting person or will the authority blame the counter that eventually he himself has taken the missing egg? But would this make sense? Why should the counter write the notes how many eggs have been delivered to make a difference visible? …
Thus to interpret some abstract expression with regard to some observable reality is not a principal problem, but it can eventually be unsolvable by purely practical reasons, leaving questions of empirical soundness open.
SOURCES
[1] Karl Popper, The Logic of Scientific Discovery, First published 1935 in German as Logik der Forschung, then 1959 in English by Basic Books, New York (more editions have been published later; I am using the eBook version of Routledge (2002))
This text is part of a philosophy of science analysis of the case of the oksimo software (oksimo.com). A specification of the oksimo software from an engineering point of view can be found in four consecutive posts dedicated to the HMI-Analysis for this software.
THE OKSIMO EVENT SPACE
The characterization of the oksimo software paradigm starts with an informal characterization of the oksimo software event space.
EVENT SPACE
An event space is a space which can be filled up by observable events fitting to the species-specific internal processed environment representations [1], [2] here called internal environments [ENVint]. Thus the same externalenvironment [ENV] can be represented in the presence of 10 different species in 10 different internal formats. Thus the expression ‘environment’ [ENV] is an abstract concept assuming an objective reality which is common to all living species but indeed it is processed by every species in a species-specific way.
In a human culture the usual point of view [ENVhum] is simultaneous with all the other points of views [ENVa] of all the other other species a.
In the ideal case it would be possible to translate all species-specific views ENVa into a symbolic representation which in turn could then be translated into the human point of view ENVhum. Then — in the ideal case — we could define the term environment [ENV] as the sum of all the different species-specific views translated in a human specific language: ∑ENVa = ENV.
But, because such a generalized view of the environment is until today not really possible by practical reasons we will use here for the beginning only expressions related to the human specific point of view [ENVhum] using as language an ordinary language [L], here the English language [LEN]. Every scientific language — e.g. the language of physics — is understood here as a sub language of the ordinary language.
EVENTS
An event [EV] within an event space [ENVa] is a change[X] which can be observed at least from the members of that species [SP] a which is part of that environment ENV which enables a species-specific event space [ENVa]. Possibly there can be other actors around in the environment ENV from different species with their specific event space [ENVa] where the content of the different event spaces can possible overlap with regard to certain events.
A behavior is some observable movement of the body of some actor.
Changes X can be associated with certain behavior of certain actors or with non-actor conditions.
Thus when there are some human or non-human actors in an environment which are moving than they show a behavior which can eventually be associated with some observable changes.
CHANGE
Besides being associated with observable events in the (species specific) environment the expression change is understood here as a kind of inner state in an actor which can comparepast (stored) states Spast with an actual state Snow. If the past and actual state differ in some observable aspect Diff(Spast, Snow) ≠ 0, then there exists some change X, or Diff(Spast, Snow) = X. Usually the actor perceiving a change X will assume that this internal structure represents something external to the brain, but this must not necessarily be the case. It is of help if there are other human actors which confirm such a change perception although even this does not guarantee that there really is a change occurring. In the real world it is possible that a whole group of human actors can have a wrong interpretation.
SYMBOLIC COMMUNICATION AND MEANING
It is a specialty of human actors — to some degree shared by other non-human biological actors — that they not only can built up internal representations ENVint of the reality external to the brain (the body itself or the world beyond the body) which are mostly unconscious, partially conscious, but also they can built up structures of expressions of an internal language Lint which can be mimicked to a high degree by expressions in the body-external environment ENV called expressions of an ordinary language L.
For this to work one has to assume that there exists an internal mapping from internal representations ENVint into the expressions of the internal language Lint as
meaning : ENVint <—> Lint.
and
speaking: Lint —> L
hearing: Lint <— L
Thus human actors can use their ordinary language L to activate internal encodings/ decodings with regard to the internal representations ENVint gained so far. This is called here symbolic communication.
NO SPEECH ACTS
To classify the occurrences of symbolic expressions during a symbolic communication is a nearly infinite undertaking. First impressions of the unsolvability of such a classification task can be gained if one reads the Philosophical Investigations of Ludwig Wittgenstein. [5] Later trials from different philosophers and scientists — e.g. under the heading of speech acts [4] — can not fully convince until today.
Instead of assuming here a complete scientific framework to classify occurrences of symbolic expressions of an ordinary language L we will only look to some examples and discuss these.
KINDS OF EXPRESSIONS
In what follows we will look to some selected examples of symbolic expressions and discuss these.
(Decidable) Concrete Expressions [(D)CE]
It is assumed here that two human actors A and B speaking the same ordinary language L are capable in a concrete situation S to describeobjects OBJ and properties PROP of this situation in a way, that the hearer of a concrete expression E can decide whether the encoded meaning of that expression produced by the speakeris part of the observable situation S or not.
Thus, if A and B are together in a room with a wooden white table and there is a enough light for an observation then B can understand what A is saying if he states ‘There is a white wooden table.‘
To understand means here that both human actors are able to perceive the wooden white table as an object with properties, their brains will transform these external signals into internal neural signals forming an inner — not 1-to-1 — representationENVint which can further be mapped by the learned meaning function into expressions of the inner language Lint and mapped further — by the speaker — into the external expressions of the learned ordinary language L and if the hearer can hear these spoken expressions he can translate the external expressions into the internal expressions which can be mapped onto the learned internal representations ENVint. In everyday situations there exists a high probability that the hearer then can respond with a spoken ‘Yes, that’s true’.
If this happens that some human actor is uttering a symbolic expression with regard to some observable property of the external environment and the other human actor does respond with a confirmation then such an utterance is called here a decidable symbolic expression of the ordinary language L. In this case one can classify such an expression as being true. Otherwise the expression is classified as being not true.
The case of being not true is not a simple case. Being not true can mean: (i) it is actually simply not given; (ii) it is conceivable that the meaning could become true if the external situation would be different; (iii) it is — in the light of the accessible knowledge — not conceivable that the meaning could become true in any situation; (iv) the meaning is to fuzzy to decided which case (i) – (iii) fits.
Cognitive Abstraction Processes
Before we talk about (Undecidable) Universal Expressions [(U)UE] it has to clarified that the internal mappings in a human actor are not only non-1-to-1 mappings but they are additionally automatic transformation processes of the kind that concrete perceptions of concrete environmental matters are automatically transformed by the brain into different kinds of states which are abstracted states using the concrete incoming signals as a trigger either to start a new abstracted state or to modify an existing abstracted state. Given such abstracted states there exist a multitude of other neural processes to process these abstracted states further embedded in numerous different relationships.
Thus the assumed internal language Lint does not map the neural processes which are processing the concrete events as such but the processed abstracted states! Language expressions as such can never be related directly to concrete material because this concrete material has no direct neural basis. What works — completely unconsciously — is that the brain can detect that an actual neural pattern nn has some similarity with a given abstracted structure NN and that then this concrete pattern nn is internally classified as an instance of NN. That means we can recognize that a perceived concrete matter nn is in ‘the light of’ our available (unconscious) knowledge an NN, but we cannot argue explicitly why. The decision has been processed automatically (unconsciously), but we can become aware of the result of this unconscious process.
Universal (Undecidable) Expressions [U(U)E]
Let us repeat the expression ‘There is a white wooden table‘ which has been used before as an example of a concrete decidable expression.
If one looks to the different parts of this expression then the partial expressions ‘white’, ‘wooden’, ‘table’ can be mapped by a learned meaning function φ into abstracted structures which are the result of internal processing. This means there can be countable infinite many concrete instances in the external environment ENV which can be understood as being white. The same holds for the expressions ‘wooden’ and ‘table’. Thus the expressions ‘white’, ‘wooden’, ‘table’ are all related to abstracted structures and therefor they have to be classified as universal expressions which as such are — strictly speaking — not decidable because they can be true in many concrete situations with different concrete matters. Or take it otherwise: an expression with a meaning function φ pointing to an abstracted structure is asymmetric: one expression can be related to many different perceivable concrete matters but certain members of a set of different perceived concrete matters can be related to one and the same abstracted structure on account of similarities based on properties embedded in the perceived concrete matter and being part of the abstracted structure.
In a cognitive point of view one can describe these matters such that the expression — like ‘table’ — which is pointing to a cognitive abstracted structure ‘T’ includes a set of properties Π and every concrete perceived structure ‘t’ (caused e.g. by some concrete matter in our environment which we would classify as a ‘table’) must have a ‘certain amount’ of properties Π* that one can say that the properties Π* are entailed in the set of properties Π of the abstracted structure T, thus Π* ⊆ Π. In what circumstances some speaker-hearer will say that something perceived concrete ‘is’ a table or ‘is not’ a table will depend from the learning history of this speaker-hearer. A child in the beginning of learning a language L can perhaps call something a ‘chair’ and the parents will correct the child and will perhaps say ‘no, this is table’.
Thus the expression ‘There is a white wooden table‘ as such is not true or false because it is not clear which set of concrete perceptions shall be derived from the possible internal meaning mappings, but if a concrete situation S is given with a concrete object with concrete properties then a speaker can ‘translate’ his/ her concrete perceptions with his learned meaning function φ into a composed expression using universal expressions. In such a situation where the speaker is part of the real situation S he/ she can recognize that the given situation is an instance of the abstracted structures encoded in the used expression. And recognizing this being an instanceinterprets the universal expression in a way that makes the universal expression fitting to a real given situation. And thereby the universal expression is transformed by interpretation with φ into a concrete decidable expression.
SUMMING UP
Thus the decisive moment of turning undecidable universal expressions U(U)E into decidable concrete expressions (D)CE is a human actor A behaving as a speaker-hearer of the used language L. Without a speaker-hearer every universal expressions is undefined and neither true nor false.
makedecidable : S x Ahum x E —> E x {true, false}
This reads as follows: If you want to know whether an expression E is concrete and as being concrete is ‘true’ or ‘false’ then ask a human actor Ahum which is part of a concrete situation S and the human actor shall answer whether the expression E can be interpreted such that E can be classified being either ‘true’ or ‘false’.
The function ‘makedecidable()’ is therefore the description (like a ‘recipe’) of a real process in the real world with real actors. The important factors in this description are the meaning functions inside the participating human actors. Although it is not possible to describe these meaning functions directly one can check their behavior and one can define an abstract model which describes the observable behavior of speaker-hearer of the language L. This is an empirical model and represents the typical case of behavioral models used in psychology, biology, sociology etc.
SOURCES
[1] Jakob Johann Freiherr von Uexküll (German: [ˈʏkskʏl])(1864 – 1944) https://en.wikipedia.org/wiki/Jakob_Johann_von_Uexk%C3%BCll
[2] Jakob von Uexküll, 1909, Umwelt und Innenwelt der Tiere. Berlin: J. Springer. (Download: https://ia802708.us.archive.org/13/items/umweltundinnenwe00uexk/umweltundinnenwe00uexk.pdf )
[3] Wikipedia EN, Speech acts: https://en.wikipedia.org/wiki/Speech_act
[4] Ludwig Josef Johann Wittgenstein ( 1889 – 1951): https://en.wikipedia.org/wiki/Ludwig_Wittgenstein
[5] Ludwig Wittgenstein, 1953: Philosophische Untersuchungen [PU], 1953: Philosophical Investigations [PI], translated by G. E. M. Anscombe /* For more details see: https://en.wikipedia.org/wiki/Philosophical_Investigations */
Integrating Engineering and the Human Factor (info@uffmm.org) eJournal uffmm.org ISSN 2567-6458
