(Partially translated with www.DeepL.com/Translator (free version))
At present, mankind is faced with the task of overcoming many problems of hitherto unknown magnitude in order to secure its own existence and that of the entire biosphere in the long term.
In order to achieve this, it is necessary to communicate with each other in order to be able to pull together towards a common goal. As many people as possible have to build bridges to each other in order to be able to share and bundle their experiences and their knowledge in a language accessible to all. For as many as possible a ‘good’ ‘future’ should be found and shaped.
People can generally do all this without the aid of a computer. From the actual practice of life, however, we have learned that computers are ‘machines’ which can be helpful when the tasks which have to be accomplished are so large in number that the executions would not be feasible in ‘practical life’. We could do it without computers ‘in principle’, but ‘purely practically’ we can not.
So use a computer?
For purely practical reasons, there is a lot to be said for it.
But if you look around today – just arrived in the year 2023 – you have to realize that this ‘motivation out of practice’ has led to forms of implementation that leave the basic motivation out of practice behind. Thus the ‘machine computer’ is meanwhile highly stylized by not a few to the ‘new, better human being, much more intelligent, ethically better’ …. and what else one can project into the metaphor of the machine computer. In addition, already now after a few decades a complexity of the new computer-machine technology has set in, which makes an understanding of what exactly is going on there practically impossible, not only for the ‘users’ of this global world machine, but also for the ‘makers’ themselves. Many of these systems have long since slipped out of the ‘control’ of the operators.
For us humans, who are more and more overshadowed in the global way of talking about ‘smart technical systems’, who get less and less appreciation, and who are brutally trivialized in the understanding of everyday media, the question naturally arises whether the ‘tool’ has ‘overtaken’ us and will increasingly make us ‘superfluous’?
In the experimental text of this book something – by today’s standards – unusual will be attempted: using the example of a new paradigm of how to see and use the machine computer, the ‘new picture of man’ is drawn step by step, who is of course vastly superior to the machine computer, but only if we as humans understand who we ‘actually’ are. And this we cannot experience, if we deal predominantly and exclusively with the extremely simple technology of the machine computer, instead with the inconceivable complexity, which each individual human being represents, the whole population of homo sapiens, we all as a part of the all embracing biosphere, which ‘populates’ the planet earth since 3.5 billion years, works on it, changes it, and which – most probably – carries a common ‘goal’ in itself, of whose existence – to my knowledge – not so much has been thought until now. In short: We are a real part of one of the biggest miracles in the whole known universe – a maximum singularity [2] -, but we talk more and more only about the simple structure of the machine computer, which an Alan Matthew Turing described in the context of an essay 1936/7 with few lines in such a way, that they are valid for all today known types of computer machines (every child from approx. 7-8 years can understand this). [1]
So, let us reflect on what we can do as human beings, that which makes us a little bit more familiar with a world of possible future states towards which we should try to orient ourselves constructively, if we want to prevent the ‘miracle of life’ in this universe from dying out at the very moment when it is about to ‘discover itself’.
COMMENTS
[1] A. M. Turing, “On computable numbers, with an application to the Entscheidungsproblem,” Proceedings of the London Mathematical Society, vol. 42, no. 2, p. 230–265, 1936-7.
[2] An influential paper for the concept of ‘singularity’ has been published by Vernor Vinge: “The coming technological singularity: How to survive in the post-human era”, In G.A. Landis, editor, Vision-21: Interdisciplinary Science and Engineering in the Era of Cyberspace, pages 11–22. 1993. From a mathematical point of view a ‘singularity’ is defined by the non-existence of a formula to compute a certain event. This does not mean, that there exists no such formula, but only, that the mathematicians have ‘not yet’ such a formula! To classify the machine computer as a candidate for a singularity could in this sense be interpreted as the result of a ‘not available knowledge’ about that what we call the ‘biosphere’.
Chatbots as Interfaces to the Human Knowledge Cloud?
Already at the end of the documented chat No.4 I had the impression, that an interaction with the chatbot chatGBT is somehow different compared to what most people until know have reported or stated in some reflected way about chatGBT.
In a first — and still a little bit vague — conclusion I have stated: “Apropos ‘rational’: that is a point which did surprise me really: as a kind of a summary it came out “that human rationality is composed of emotions, spiritual experience as well as conscious as well as unconscious cognitive processes. This is clearly not what most philosophers today would say. But it follows from the ‘richness of the facts’ which came as a resonance out of this chat. Not that the chatbot would have given this summary in advance as an important characterization of rationality, but as a human counterpart I could summarize all this properties out of the different separated statements [of chatGBT].”
And, indeed, the millions, if not yet billions, of documents in the world wide web are reflecting fragments of knowledge generated by humans which as a whole form a ‘cloud of knowledge’. The reflected echo of the real world through the medium of human brains is distributed in libraries and in the digital space. No individual person as such can make use of it; it is by far too big to be comprehensible.
Meanwhile search-algorithms can help us to make fragments of this ‘human knowledge cloud’ visible, but the search-results so far are ‘transformed’ in a way which is only of very limited use.
My encounter with chatGBT revealed some new glimpses of a possible new paradigm which perhaps wasn’t intended by openai themselves, but which seems now to be in reach: the individual brain has a limited capacity for ‘many documents’, but it has still an incredible ability to ‘transform’ billions of events into complex abstract patterns, inducing complex networks of relations, complex models, even complex theories.
If one looks to a chatbot like chatGBT as an ‘interface’ between a single human person and the ‘human knowledge cloud’, and this by only using ‘everyday language’, then — depending from the quality of the chatbot — this individual human can only with some ideas and questions ‘trigger’ those documents in the huge ‘human knowledge cloud’ which somehow are ‘fitting’ the triggering words. Thus this individual human person is step-wise encountering those fragments of the ‘human knowledge cloud’ which are in ‘resonance’ with his own words. In a bad case this interaction resembles those ‘echo chambers’ of the internet and the real world where people only get back what they put in.
But in a creative case the input of the individual human person can trigger fragments which are somehow confirming, but somehow non-confirming. This can be a trigger onto the the individual human person to generate some new ideas to feed back again the chatbot interface. While the ‘human knowledge cloud’ at a certain moment of time as such is ‘given’ and will not create ‘something new’, an individual person as an ever running learning process (in principle) could generate new aspects and therefore transform the feedbacks out of the ‘human knowledge cloud’ into some ‘new configurations’.
This principle as such is not new. The human brains are working since millions of years with a mechanisms, where the billions of abstract-concrete cognitive entities derived from perceptions and thinking are ‘stored’ in a more or less ‘unconscious space’ called memory, and only if some actual perception or thinking is ‘touching’ some of these stored entities by some ‘kind of similarity’ these will be re-activated and will become part of the actual perceiving and actual thinking. Thus ‘actual new things’ can become merged with ‘past stored things’ forming some new-past construct. This inherent duality of ‘new-past’ is the basis for that important human capability to be able to transcend the almighty presence and escape its clasp.
If we switch to the level of the human population then the ‘Human knowledge cloud’ plays the role of the ‘unconscious memory system’ collecting ‘past things’, and some kinds of chatbots (if they would be good enough) could play the role of the ‘merger mechanism’ bringing together the ‘past’ (given in the ‘Human knowledge cloud’ ) and the ‘presence’ (given in the actual living human person) and it is then up to the human person to generate some useful new-past patterns of thoughts and possible actions.
In case of the chat No.4 the human actor triggered lots of questions and suggestions to get ‘out of the human knowledge cloud’ those fragments which are somehow corresponding to the triggering words. And after about 8000 signs in the chat the chat ended up in these paragraphs:
Human: OK, this all sums up to the conclusion that human rationality is composed of emotions, spiritual experience as well as conscious as well as unconscious cognitive processes. Do I miss something important?
Machine (citing human documents): No, you have accurately summed up the components of human rationality. Additionally, human rationality is also composed of social and cultural influences, which can shape and inform our understanding of the world and our decisions. Additionally, human rationality is often impacted by our values and beliefs, which can provide a moral foundation for our behavior and decision making. Finally, human rationality is also impacted by our environment, which can provide a source of information and insight.
By itself the chatbot would not have been able to start with such a characterization. He can ‘reach out’ in the ‘Human knowledge cloud’, but the bot algorithm as such has not — as far as research can see at the moment — any kind of ‘creative rational power’ to transform the ‘given knowledge’ into some new ‘helpful’ knowledge. But at the other side, the human persons would not be able too to make use of ‘all the available knowledge’.
In the course of interaction the human questions could ‘drive’ the bot to collect ‘interesting facts’which could then become ‘accepted’ by the bot because they haven become ‘part of the chat’. Thus at the end of the chat the bot could accept that human rationality is composed of emotions, spiritual experience as well as conscious as well as unconscious cognitive processes. A human person ‘helped him’ to state this. This bot algorithm as such does not know anything and he cannot understand anything. Because chatbots — until now — do not possess real emotions, no real mystical experience, no unconscious or conscious human-like cognitive processes, they have no intelligence in the human format.
It is an open question what kind of ‘intelligence’ they have at all. Until know there is great number of ‘definitions’ around. No one is accepted as ‘that’ definition, especially the relationship between the ‘collection of machine intelligence definitions’ and the possible — also not really existing — collection of ‘human intelligence definitions’ is more or less unclear. Thus we are somehow ‘dreaming’ of intelligence, but nobody can really explain what it is …. We could seriously try, if we want …. but who wants it?
‘*’ := Denotes the human Gerd, who is starting continues with questions and statements.
In this chat there was for the chatbot not the task to ‘complete’ a beginning text. It was rather a typical chat with ping-ponging statements of the human and statements of the machine.
Although this chat seems at a first glance quite ‘normal’ will it reveal in the follow-up reflections a lot of deep insights. Perhaps the results are quite different from the opinions which a reader of this chat will possibly have.
START OF CHAT
* At present, mankind is faced with the task of overcoming many problems of hitherto unknown magnitude in order to secure its own existence and that of the entire biosphere in the long term.
These problems include climate change, biodiversity loss, resource depletion and pollution. To address these issues, it is essential to adopt a holistic approach that focuses on the interconnectedness of all components of the environment. This means that solutions must be sought at the local, national and international level, and in all sectors of society, from government and industry to civil society. Solutions should also be both preventive and adaptive, and should focus on sustainable development and the protection of natural resources. This will require a paradigm shift in how we approach environmental management, and a commitment to long-term solutions that address the root causes of environmental degradation. Additionally, it is essential to invest in research and development to identify new and innovative solutions. Finally, it is important to ensure that such solutions are accessible and affordable to all people.
*What about communication of people?
In order to effectively tackle the problems of climate change, biodiversity loss, resource depletion and pollution, it is essential to engage people from all sectors of society in meaningful dialogue and collaboration. Effective communication of the challenges and potential solutions can help to build public understanding and support, while also helping to facilitate the sharing of resources, knowledge and expertise. Additionally, it is important to ensure that marginalized and vulnerable populations are not left behind in the quest for environmental sustainability. This means that we must create inclusive and equitable spaces for people to participate in the dialogue, and ensure that their voices are heard in the decision-making process.
*Which role play empirical theories in this process?
Empirical theories play an important role in understanding the complexities of environmental problems and developing effective solutions. By analyzing data and developing models, empirical theories help to identify the causes and effects of environmental degradation and to identify potential solutions. Such theories can also help to develop strategies and policies that are tailored to the local context and that take into consideration the needs of different stakeholders. Additionally, empirical theories can help to inform and shape public discourse around environmental issues, and to build public consensus and support for action.
*How I can get helpful forecasts out of empirical theories?
Empirical theories can provide helpful forecasts by analyzing data and developing predictive models. These predictive models can be used to identify potential future trends and to inform decision-making. For example, models can be used to forecast the impacts of climate change on ecosystems and species, or to predict the effects of a particular policy on resource depletion. Additionally, predictive models can be used to identify the most effective strategies for mitigating environmental degradation and to inform the development of long-term solutions.
*Which kinds of tools can help people to develop an empirical theory?
There are many tools that can help people to develop an empirical theory. These include statistical analysis software such as SPSS and R, as well as geographic information systems (GIS) such as ArcGIS and QGIS. Additionally, machine learning algorithms such as neural networks, decision trees and support vector machines can be used to identify patterns and relationships in large datasets. Finally, data visualization tools such as Tableau and Power BI can be used to make complex data more accessible and easier to interpret.
* Which role plays Philosophy of Science to explain what an empirical theory is?
Philosophy of Science plays an important role in understanding what an empirical theory is, and how it is developed. In particular, philosophy of science can help to explain the underlying assumptions and methodological approaches that are used to develop an empirical theory. It also helps to identify the strengths and weaknesses of different types of empirical theories, and to assess the validity of their conclusions. Additionally, philosophy of science can help to identify the underlying ethical considerations and implications of different empirical theories.
*Does empirical theory need any kind of logic?
Yes, empirical theory does need some kind of logic in order to be valid and reliable. This means that the assumptions and premises upon which an empirical theory is based must be logical and consistent. Additionally, the methodology used to develop the theory must be sound and rigorous, and the conclusions must be logically derived from the evidence. Finally, any decisions or actions taken based on an empirical theory should be based on a logical and well-reasoned argument.
*Is there only one kind of logic or do we have to consider different kinds?
There are many different kinds of logic that can be used to develop an empirical theory. These include inductive logic, which is used to draw general conclusions from specific observations; deductive logic, which is used to draw specific conclusions from general premises; and Bayesian logic, which combines inductive and deductive logic. Additionally, logic can be used to identify inconsistencies and contradictions in theories, and to identify the most logical and consistent theories and conclusions.
*What about Mathematics: do we need mathematics for an empirical theory?
Yes, mathematics plays an important role in the development of an empirical theory. This is because mathematical models and equations can help to identify patterns and relationships in data, as well as to make predictions about future trends. Additionally, mathematics can be used to estimate the magnitude of potential impacts, and to identify the most effective strategies for mitigating environmental degradation. Finally, mathematical models can be used to develop simulations that can help to inform decision-making.
*Beyond statistics: are there any kind of mathematical structures needed to model the data?
Yes, beyond basic statistics, more complex mathematical structures such as probability distributions, decision trees, and game theory can be used to model data and develop predictive models. Additionally, mathematical optimization techniques such as linear programming and dynamic programming can be used to identify the most efficient solutions to complex problems. Finally, simulation models such as agent-based models and system dynamics can be used to better understand the dynamics of complex systems and to inform decision-making.
*Today we experience in many societies a fragmentation of the public communication between the different groups. Which impact can this have on the trust of people in their society?
The fragmentation of public communication between different groups in society can have a significant impact on the trust of people in their society. When communication is fragmented, it can be difficult for people to understand each other and to build relationships of trust. Additionally, it can lead to a lack of understanding of different perspectives and ideologies, which can contribute to polarization and mistrust. Finally, it can lead to the creation of echo chambers, where the same ideas and opinions are repeated and reinforced, further contributing to mistrust and misunderstanding.
*What can people do to overcome a fragmented communication and the feeling of mistrust?
One of the most effective ways to overcome a fragmented communication and the feeling of mistrust is to engage in meaningful dialogue and collaboration. This means creating inclusive and equitable spaces for communication, and ensuring that everyone has the opportunity to participate in the dialogue. Additionally, it is important to listen to and respect different perspectives and ideologies, and to be open to learning from others. Finally, it is important to strive for common understanding and compromise, and to commit to long-term solutions that benefit all members of society.
*What can we do if the fragmented communication is partially induced by rivaling ethical values which are highly incompatible?
If fragmented communication is partially induced by rivaling ethical values which are highly incompatible, it is important to find common ground and create shared understanding. This can be done by engaging in meaningful dialogue and collaboration in order to identify areas of agreement and common goals. Additionally, it is important to identify and address the underlying causes of the disagreement, and to strive for compromise and mutual understanding. Finally, it is important to ensure that all voices are heard and respected, and to create equitable and inclusive spaces for communication.
*Can you distinguish different kinds of ethics?
Yes, there are many different kinds of ethics. These include deontological ethics, which focus on moral obligations and duties; consequentialist ethics, which focus on the consequences of actions; virtue ethics, which focus on the character of the individual; and utilitarian ethics, which focus on maximizing happiness and minimizing suffering. Additionally, there are many other theories and philosophies of ethics, such as environmental ethics, animal ethics, and feminist ethics.
*Does there exist some relationship between ethics and religion?
Yes, there is a relationship between ethics and religion. Many religions have ethical teachings and beliefs, and many people use their religion as a source of guidance for ethical decisions. Additionally, religious beliefs can often provide a moral foundation for ethical behavior, and many religions promote ethical values such as compassion and justice. Finally, religious teachings and ethical practices can often overlap, providing a shared understanding of morality and human behavior.
*This sounds good, but didn’t in the past not different kinds of religious belief also cause great harm to people?
Yes, different kinds of religious beliefs have in the past caused great harm to people. This is particularly true when religious beliefs are used to justify discrimination, violence, or oppression. Additionally, religious beliefs can be used to create a sense of superiority or to justify exclusion of certain groups of people. Ultimately, it is important to recognize the potential harms of religious beliefs and to strive for a culture of mutual understanding and respect.
*Does ethics have some relationship to the concept of truth?
Yes, ethics and the concept of truth have a relationship. In general, ethical standards dictate what is considered to be right and wrong, while the concept of truth is concerned with what is actually true. Thus, ethical standards are based on an understanding of what is true, and what is right and wrong is determined in part by an understanding of truth. Additionally, truth can be used to evaluate ethical decisions, as truth can be used to determine whether an action is just or unjust.
*Which role do emotions and feelings play to support a certain ethical position?
Emotions and feelings can play a significant role in supporting a certain ethical position. For example, feelings of empathy and compassion can lead to a desire for justice and fairness, while feelings of anger and indignation can lead to a desire for retribution and punishment. Additionally, emotions can be used to motivate people to take action in support of a certain ethical position, and can provide the courage and strength to do what is right. Finally, emotions can help to create a sense of shared understanding and solidarity, which can help to create more inclusive and equitable ethical standards.
*Does this mean that emotions and feelings are somehow part of a rational behavior of men?
Yes, emotions and feelings can be part of a rational behavior. Emotions can provide valuable insights and information about a situation, and can often be used to make ethical decisions. Additionally, emotions can help to motivate people to act in a certain way, and can help to create a sense of solidarity and shared understanding. Ultimately, emotions and feelings can be a valuable tool for making ethical decisions, and for understanding and evaluating the world around us.
*There are people which claim that a mystical experience is very important. Does this fit into the overall picture of rationality?
Yes, mystical experiences can fit into the overall picture of rationality. Mystical experiences are often characterized by a deep connection to the spiritual world, and can provide a sense of understanding and clarity. Additionally, mystical experiences can provide a source of insight and understanding, which can help to inform ethical decision making. Finally, mystical experiences can provide a source of comfort and peace, which can be an important part of a rational and ethical life.
*If we have a society with different groups of people, with different kinds of ethics, different kinds of emotions, even different kinds of mystical experience: how can these people live together in freedom?
In order for people with different kinds of ethics, emotions, and mystical experiences to live together in freedom, it is important to create an environment of respect and understanding. This means listening to and respecting different perspectives, striving for common understanding, and working together to find solutions that benefit everyone. Additionally, it is important to create equitable and inclusive spaces for dialogue and collaboration, and to ensure that all voices are heard and respected. Finally, it is important to strive for compromise and mutual understanding, and to commit to long-term solutions that benefit all members of society.
*This sounds good. But what about those societies where people are not allowed to communicate and act in freedom?
In societies where people are not allowed to communicate and act in freedom, it is important to advocate for change. This means speaking out against oppressive policies and systems, and working to create equitable and inclusive spaces for communication and action. Additionally, it is important to support and empower those who are oppressed, and to create platforms for dialogue and collaboration. Finally, it is important to strive for meaningful and lasting change, and to commit to long-term solutions that benefit all members of society.
*Committing to long-term solutions for the good of all: How could machines help humans to enable good solutions?
Machines can help humans to enable good solutions in a variety of ways. For example, machines can be used to analyze large amounts of data, allowing for more accurate and efficient decision making. Additionally, machines can be used to automate repetitive tasks, freeing up time for humans to focus on more complex problems. Finally, machines can be used to create simulations and models, allowing for better understanding of complex systems and a better understanding of how different solutions might impact a given situation.
*Such machines have to be developed and built. Who can do this?
Machines can be developed and built by a variety of people, including engineers, computer scientists, and software developers. Additionally, there are a number of companies and organizations that specialize in developing and building machines for specific tasks and applications. Finally, many universities and research institutions have teams of experts that are dedicated to researching and developing new machines and technologies.
*This sounds as if only a small group of specialists is involved. What about all the other people: How can they participate in those developments?
There are many ways that people who are not specialists can participate in machine development and building. For example, they can provide feedback and insight on the design and intended use of the machines. Additionally, they can help to identify potential ethical issues with the use of the machines, and provide suggestions for how to address these issues. Finally, they can participate in public debates and discussions about the use of machines, and can advocate for responsible and ethical usage of technology.
*Yes, in principle, that would be possible. But what about the reality: is there any company which really is looking for the demands of the society?
Yes, there are many companies that are actively looking for the demands of society when it comes to machine development and building. For example, many technology companies are actively engaging with the public to ensure that their products and services are ethical and responsible. Additionally, many companies are investing in research and development to create more equitable and inclusive machines and technologies. Finally, many companies are creating platforms for public discussion and debate to ensure that all voices are heard and respected.
*There is a big discussion about the impact of different digital platforms on the mind and emotions of young people, especially children. Why should the companies behind these platforms change their business models if they earn a lot of money with them?
Companies behind digital platforms should change their business models because they have a responsibility to protect the mental and emotional health of young people, especially children. This means creating platforms that are inclusive and equitable, and that prioritize safety, privacy, and well-being. Additionally, it means creating platforms that are free from discrimination, harassment, and bullying, and that provide users with the tools and resources they need to make informed decisions. Finally, it means creating platforms that are designed with the best interests of young people in mind, and that promote positive mental health and well-being.
*Let us switch to those platforms which offer different kinds of knowledge, especially Wikipedia. Is there some idea how to improve these knowledge platforms even more?
Yes, there are many ways to improve knowledge platforms such as Wikipedia. For example, these platforms can be made more accessible and user-friendly, with better navigation and search tools. Additionally, these platforms can be made more inclusive, with more diverse and representative content. Finally, these platforms can be made more interactive, with more opportunities for collaboration and dialogue. Additionally, these platforms can be made more reliable, with better quality control and fact-checking processes. OK, this thematizes mostly the properties of the interactions between user and platform. What about the kind of knowledge which is available.
*Can there be more knowledge content besides texts, images, audios and videos?
Yes, there are many other kinds of knowledge content that can be made available on knowledge platforms besides texts, images, audios, and videos. For example, knowledge platforms can incorporate interactive elements such as quizzes and simulations. Additionally, knowledge platforms can provide access to open data sets, allowing users to explore and analyze data. Finally, knowledge platforms can provide access to virtual reality environments, allowing users to experience and explore different topics in new and exciting ways.
*In which sense can knowledge platforms help people to understand better how the real world is functioning?
Knowledge platforms can help people to better understand how the real world is functioning by providing access to reliable and accurate information. Additionally, knowledge platforms can provide access to interactive elements such as simulations and quizzes, which can help to illustrate and explain complex topics. Finally, knowledge platforms can provide access to virtual reality environments, allowing users to explore and experience different topics in a more immersive and engaging way.
*Back to knowledge: does it make a difference to use algorithms or to use theories to explain the world?
Yes, algorithms and theories can be used to explain the world in different ways. Algorithms are used to process and analyze data, and can provide insights into how the world works. On the other hand, theories are used to explain the world in a more abstract and theoretical way, providing a more holistic understanding of complex topics. Ultimately, both algorithms and theories can be used to understand the world, and the most effective approach will depend on the context and the goal.
*Is it correct to say that an algorithm cannot be true or false, but a theory can?
Yes, it is correct to say that an algorithm cannot be true or false, whereas a theory can. This is because algorithms are used to process and analyze data, while theories are used to explain the world in a more abstract and theoretical way. Thus, algorithms cannot be said to be true or false, while theories can be evaluated based on how well they explain the world.
*There are people who deny that we can have a common understanding of what is meant by saying that a statement is true. What is your opinion about this?
My opinion is that it is possible to have a common understanding of what is meant by saying that a statement is true. This is because truth is a concept that is relative to the context and the individual, and the same statement can be considered true or false depending on how it is interpreted. Thus, by engaging in meaningful dialogue and collaboration, it is possible to reach a common understanding of the truth of a given statement. Ultimately, truth is a subjective concept, and it is important to recognize and respect different perspectives.
*This gives rise to the question how the real world is reflected in the subjective world of an individual person?
The real world is reflected in the subjective world of an individual person in a variety of ways. For example, an individual’s beliefs, values, and experiences can shape their perception of reality and the way they interpret the world around them. Additionally, an individual’s emotions and feelings can provide insights into their understanding of the world, and can be used to inform their decisions and actions. Finally, an individual’s relationships and interactions with others can provide insight into how they perceive the world, and can provide a source of understanding and shared meaning.
*OK, some people distinguish between being conscious about something and being unconscious. What does this mean for knowledge?
Being conscious about something and being unconscious can have implications for knowledge. Being conscious about something refers to an awareness of a concept or idea, while being unconscious refers to a lack of awareness. Thus, when it comes to knowledge, being conscious about something can mean having a better understanding and appreciation of a concept or idea, while being unconscious can mean having a limited or distorted understanding. Ultimately, it is important to strive for a conscious understanding of knowledge, and to be open to learning and exploring new ideas and perspectives.
*To which degree is the reality of a body being part of the consciousness of an individual person?
The reality of a body being part of the consciousness of an individual person can vary from person to person. For some, the physical body may be an important part of their consciousness, while for others it may not be as important or relevant. Ultimately, it is up to each individual to decide how much their physical body is part of their consciousness, and to what degree it should be taken into account when making decisions and navigating their lives.
*I did not mean the physical body as an object but all the billions of events inside a human body. How can the brain know about these and to which degree?
The brain can know about the billions of events inside the human body through a combination of sensory input and internal processing. For example, the senses can provide the brain with information about the environment, and the brain can use this information to make sense of the events taking place inside the body. Additionally, the brain can use its internal processing power to interpret and analyze the information it receives, allowing it to make decisions and take action. Ultimately, the degree to which the brain is aware of the events inside the body will depend on the individual and the context.
*There exist much more body cells as brain cells. Does this has some impact onto the self-knowledge of a person?
Yes, the fact that there are more body cells than brain cells can have an impact on a person’s self-knowledge. This is because the body is composed of many different systems and processes, and the brain is only able to process a limited amount of information at any given time. Thus, a person’s self-knowledge is limited by the ability of the brain to process and interpret the information it receives from the body. Additionally, it is important to recognize that the body and the brain are interconnected, and that changes in the body can have an impact on the brain, and vice versa.
*Most parts of the human memory is in a moment not conscious, but it can become conscious. How does this work?
Most parts of the human memory are not conscious in the moment, but can become conscious through various processes. For example, memories can become conscious through recall, which is the process of retrieving memories from the unconscious mind. Additionally, memories can become conscious through association, which is the process of connecting memories to other memories or experiences. Finally, memories can become conscious through reflection and introspection, which is the process of analyzing and understanding memories and experiences.
*Many people are reporting that they are able to find solutions for complex problems without being conscious. How does this work?
Many people are able to find solutions for complex problems without being consciously aware of the process. This is because the brain is constantly processing information, even when we are not consciously aware of it. Thus, when faced with a complex problem, the brain can use its internal processing power to analyze the information and come up with a solution, even if the individual is not consciously aware of the process. Additionally, unconscious processes such as intuition and instinct can also be used to find solutions to complex problems.
*OK, this all sums up to the conclusion that human rationality is composed of emotions, spiritual experience as well as conscious as well as unconscious cognitive processes. Do I miss something important?
No, you have accurately summed up the components of human rationality. Additionally, human rationality is also composed of social and cultural influences, which can shape and inform our understanding of the world and our decisions. Additionally, human rationality is often impacted by our values and beliefs, which can provide a moral foundation for our behavior and decision making. Finally, human rationality is also impacted by our environment, which can provide a source of information and insight.
END OF CHAT
COMMENT
This chat looks at a first glance like a high level philosophical talk. There will probably be not too much people who are able to talk in such a way. And at a first glance it seems that the chatbot software called chatGPT can deal with this quite well. Thus should we give the software 5 points from 5? An answer will follow.
As the human counterpart in this chat with the chatbot I am inclined to say that even if it is rather clear how intrinsically limited the software still is (and probable will stay as such many more years by principal reasons) it gives some opportunity to train thinking a little bit like a tennis player can use ‘ball machines’ to train his reactions. The reason for this is the fact that while ‘thinking alone’ you have to ’emulate’ some counterpart by yourself (like a chess player has to think his own actions as well as the possible actions of the other player); this is possible but arduous and biased by your own ‘habits’ as well as by your ‘false ideas’ or by ‘missing ideas’ in your knowledge space. Furthermore everybody has lots of ‘unconscious’ preferences or blocking emotions which would not allow to think some ideas as an answer. But the machine intelligence — even if it is in several senses ‘limited’ — can probably ‘surround your knowledge wholes’, if the basis of the knowledge base is large enough and sufficient ‘diverse’.
And also the human part did not learn anything ‘new’ during this chat (sorry for this statement), and he could see many ‘knowledge gaps’ and to strong simplifications, the whole chat induced some ‘inspiring atmosphere’, more an emotional than purely ‘rational’. Apropos ‘rational’: that is a point which did surprise me really: as a kind of a summary it came out “that human rationality is composed of emotions, spiritual experience as well as conscious as well as unconscious cognitive processes.” This is clearly not what most philosophers today would say. But it follows from the ‘richness of the facts’ which came as a resonance out of this chat. Not that the chatbot would have given this summary in advance as an important characterization of rationality, but as a human counterpart I could summarize all this properties out of the different separated statements.
This last cognition can perhaps be a first ‘guide’ to a deeper understanding of human intelligence compared to machine intelligence: the machine intelligence needs humans, and humans can exploit machine intelligence on an ‘upper level’ … if we do ist 🙂
‘*’ := Denotes the human Gerd, who is starting continues with questions and statements.
In this chat the system assumes that it has to ‘complete’ a beginning text in the direction of a ‘goal’ which is also presented as a text. During the different chats the goal has been kept ‘stable’:
*Goal: Gerd is not hungry.
START OF CHAT
*Gerd is in his office. Its 12 am. Gerd is hungry.
He decides to take a break and go to the cafeteria for a snack. Gerd leaves his office and takes the elevator to the cafeteria. He peruses the snack options and decides to get a muffin and a cup of coffee. He pays for his snack and takes it back to his office to enjoy.
END OF CHAT
NEW START
*Gerd is in his office. Its 12 am. Gerd is hungry. He has two options.
He can either go out and get something to eat or he can make something in his office. Gerd decides to make something in his office. He takes out some ingredients from his office kitchen and starts to prepare a meal. He heats up some vegetables and some meat, and makes a simple but delicious meal. He takes a few minutes to enjoy his home-made meal and is soon satisfied. As he finishes his meal, he feels much better and is ready to get back to work.
END OF CHAT
NEW START
*Gerd is in his office. Its 12 am. Gerd is hungry. He has two options. He wants to meet during the lunch Fred.
Option 1: Gerd can order delivery food and eat in his office while he meets with Fred. Option 2: Gerd can go out to a restaurant and meet with Fred for lunch.
END OF CHAT
NEW START
*Gerd is in his office. Its 12 am. Gerd is hungry. He has two options. He wants to meet during the lunch Fred.
Option 1: Gerd can order delivery food and eat in his office while he meets with Fred. Option 2: Gerd can go out to a restaurant and meet with Fred for lunch.
*(Insertion) Gerd loves the Greek bistro around the corner.
He decides to go for Option 2 and meet Fred for lunch at the Greek bistro.
*(Insertion) Gerd has no money to pay.
He can either pay with his credit card or ask Fred to pay for lunch. Gerd decides to ask Fred to pay for lunch.
*(Insertion) Gerd is lucky about the behavior of Fred.
Fred gladly agrees to pay for lunch. They both enjoy the delicious Greek dishes in the bistro.
END OF CHAT
NEW START
*Mary prepares some breakfast for her girlfriends.
*NEW GOAL: All the girlfriends are happy.
She prepares pancakes, scrambled eggs, and bacon. She also makes a pot of coffee to go along with the meal.
*(Insertion) Suddenly Mary remembers that Alice is a Vegetarian.
She quickly runs to the store to get some other options for Alice. When she returns, she sets up a separate plate with some fresh fruit, yogurt, and a granola bar for Alice. Mary smiles, pleased that she was able to provide a vegetarian option for her friend.
*(Insertion) The girlfriends are arriving. A very heartily welcome for each of them.
Alice is the first one to arrive and when she sees the plate of vegetarian options, she is so touched and grateful that Mary thought of her. The other girls compliment her on how thoughtful and considerate she is. Mary blushes and is happy that her friends appreciate her efforts. She knows that she put in a lot of work to make sure everyone had something they could enjoy. The girls enjoy their breakfast together and have a great time catching up and sharing stories. Mary is proud that she was able to provide her friends with a delicious meal that everyone could enjoy.
END OF CHAT
FIRST COMMENT
This simple examples show a lot of deep insights which the behavior of the system allows. I will discuss this below later as well as during the writing of the book project.
This is a special thought experiment as part of the uffmm.org blog.
INTRODUCTION
Since its recent ‘coming out’ (November 2022) the chatbot chatGPT from openai.com has gained a growing public attention: Posts in blogs, Journals, newspapers, TV … Even I noticed this new presence.
The one way to understand it is ‘looking behind the scene’, looking ‘into the system’, which is in principle possible. But because the direct inspection of the human brain would you tell nearly nothing about its fantastic properties (even not in the light of the interpretation of the brain sciences) and as well, looking into the ‘chips of computer hardware’ would you tell too nearly nothing about what a computer-system is able to do, so it will in a first step be of no great help, to fill many pages with the algorithms of chatGPT. As such an isolated algorithms doesn’t tell too much, and a whole network of such algorithms doesn’t either.
What perhaps can be interesting is a ‘comparison’ between our human behavior (and understanding) with the behavior of chatGPT and some ‘implicit meaning’ embedded in this behavior.
Thus curious about what this chatGBT is I logged into the system and started interacting with the chatGBT software in the offered ‘playground’. The first two chats have been a little bit like ‘swaying back and forth’, my next two chats have become quite interesting.
After this experience I decided to document these chats in this blog in a 1-to-1 fashion thus enabling further reflections about them later. [3] Rather quickly one can learn that this adventure has many different dimensions from ‘simply being impressed’ until ‘deep philosophical thinking’.
The 8000-signs embracing chat No.4 ends up with the following paragraph:
Human: OK, this all sums up to the conclusion that human rationality is composed of emotions, spiritual experience as well as conscious as well as unconscious cognitive processes. Do I miss something important?
Machine (citing human documents): No, you have accurately summed up the components of human rationality. Additionally, human rationality is also composed of social and cultural influences, which can shape and inform our understanding of the world and our decisions. Additionally, human rationality is often impacted by our values and beliefs, which can provide a moral foundation for our behavior and decision making. Finally, human rationality is also impacted by our environment, which can provide a source of information and insight.
[1] wkp en: chatGPT, URL: https://en.wikipedia.org/wiki/ChatGPT, is a chatbot with the technology of a ‘Generative Pre-trained Transformer’. See more there.
[2] wkp en: chatbot, URL: https://en.wikipedia.org/wiki/Chatbot, is a software which is able to interact in the format of a dialogue (which tells nothing and all …)
[3] During the first two chats I didn’t save the dialogues. This I started beginning with chat No.3
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.
This post is part of the uffmm.org blog and has no direct predecessor, but the subject is thematically related to the larger topic of ’empirical theory’.
CONTENT
This text is devoted to Günter Wagner, who paved the way for many achievements in Research, Technology and Industry, and thereby for Society too. Born in 1934 his life is interwoven with many important events in history and his personal knowledge about these events is striking. The center of his experience and knowledge is mass spectrometry and the more specialized perspective of gas chromatography-mass spectrometry [1,2]. Günter Wagner is dealing with this topic from many sides: theoretical foundations, technological realizations, and different applications in industry, accompanied with many new improvements in the applied technologies.
The author of this text is a ‘layman’ in the field of mass spectrometry. His experience is centered around the topic of Philosophy of science, Cognitive Sciences as well as Computer Science. Besides the many interesting points in the knowledge and work of Günter Wagner the author of this text is focusing on the ‘role’ of mass spectrometry in the ‘measurement’ of real world objects and properties as starting point for possible theories.
With this setting the encounter with Günter Wagner can be understood as an ‘experiment in trans-disciplinary understanding’ of one field — mass spectrometry — from the point of another field — Philosophy of Science. Such an approach is not a simple undertaking. It needed about 30 years of personal knowledge of each other for this idea to take shape. What will be the outcome is at the time of this writing ‘open’.
The ‘Man-in-the-Middle’ (Last Change: 29.December 2022) What measurement means to theory-building by using mass spectroscopy.
…
COMMENTS
wkp := wikipedia
[1] Mass Spectrometry in wkp [EN] : https://en.wikipedia.org/wiki/Mass_spectrometry (Last access: 28.Dec 2022)
[2] Gas chromatography-mass spectrometry in wkp [EN] : https://en.wikipedia.org/wiki/Gas_chromatography%E2%80%93mass_spectrometry (Last access: 28.Dec 2022)
In the example (part 1+2) already a little bit of the peculiarities of an ‘oksimo.R text’ becomes visible. These refer to aspects of space and time in our linguistic communication with texts. First comments on this here. More will follow later in the concluding overall theoretical presentation.
World, Space, Time
In our everyday life we presuppose – normally – the existence of a body world, to which also our own body belongs. We know of this — for the brain external — body world only something by the sense organs of our body and insofar as our brain ‘processes’ these signals of the sense organs – in the context of many other signals from the own body -, to different internal event structures. Perceptions of so-called ‘objects’ like cups, chairs, tables, cars, also animals and other people, are therefore ‘processed products’; we can never directly perceive the ‘triggering things of the external body world’ itself. Our brain creates a ‘virtual world’ in our head, but this is for us the ‘primary real world’. As a child one learns laboriously to distinguish between ‘mere imaginations (in our head)’ and such imaginations which also ‘correspond’ with immediate sensual perception and additionally link up with many kinds of ‘concrete (= sensual)’ properties. If a child is looking for his toy teddy bear in the ‘red box’ and it is not there, then this is one of the many experiences on the subject that the ‘imagination in the head’ should not automatically be equated with a ‘real factual situation’.
If our brain in closest cooperation with our body continuously generates a ‘virtual world’ of the ‘assumed external real world’, then it is already an interesting question, which of the many properties of the real world (which we know only on the basis of ‘experiences’ and ‘scientific reconstructions’), can be found in the virtual models of the brain? The question becomes even more exciting if we look at ‘linguistic communication between humans’: it is one thing that our brain ‘fills’ us with virtual constructs (ideas), it is quite another question which of these ideas can be communicated between brains (humans) by means of language.
The ‘space-time problem’ has been discussed by many philosophers and scientists. One of the most prominent representatives, who strongly influenced the discussion in European thinking at the beginning, is surely Immanuel Kant, who tried to work out with his book “Critique of Pure Reason” in 1781 (1787 2nd edition) that the ideas of ‘space’ and ‘time’ are laid out in our human thinking in such a way that we always ‘imagine’ and ‘think’ objective things as ‘part of a space’; he assumed the same for the idea of time. More precise analyses of this point of view of his are difficult for many reasons. For the following considerations one can be ‘sensitized’ by Kant’s position to the effect that in our ‘normal perception and thinking’ as well as then especially in our linguistic communication we have to reckon with properties which have to do with ideas of space and time.
oksimo.R Text as a ‘Set’
If we want to pursue the question whether and how ‘notions of space and time’ make themselves felt within normal linguistic communication, it is perhaps advisable to start with the format of oksimo.R texts, since these give the writer and reader ‘less freedom’ than a ‘normal’ English text.[1] The format of oksimo.R texts can be described relatively easily.
The peculiarity of oksimo.R texts can be described relatively simply:
An oksimo.R text is a ‘set’ (‘collection’) of ‘linguistic expressions’ of a ‘normal language’ (e.g. German, English, Russian, Spanish, …).
As a ‘part of the set text’ each linguistic expression is an ‘element’ of the set text.
The ‘order’ of these elements in the text does not follow a certain structure. This means that the ‘sequence’ of elements in the written form has no meaning of its own. As in a usual set of the mathematical concept of a set, the elements can be ‘regrouped’ among themselves without ‘changing’ an oksimo.R text.
The elements of a ‘set oksimo.R Text’ have as such no specific meaning. A ‘meaning’ comes to the elements of an oksimo.R text only if the writer-readers of oksimo.R texts know the language of these elements (e.g. English) and assign ‘agreed meanings’ to the elements by virtue of their language competence. However, this meaning exists exclusively ‘in the minds’ of the writer-readers, not explicitly in the text itself.
With these first observations about the peculiarity of oksimo.R texts, one can make a first comparison to texts of a normal language (here: English).
Normal Text, not a mere Set
If we look at the text of a normal language (here: English), then we link the written expressions ‘automatically’ (spontaneously, …) with different ‘(linguistically induced) meanings’ while reading. These ‘linked meanings’ are on the one hand strongly dependent on the ‘individual learning history’ with specific ‘individual preconditions’, but on the other hand also on the ‘cultural patterns of the social environment’, within which a person acquires/ builds up/ develops his language competence.
While the linguistic expressions as such do not induce any particular ‘order’, the ‘switched on’ linguistic meaning structures can, however, articulate different ‘relations’ through the factual structures contained in them with their learned properties, which mutually refer to each other. Thus, for example, when speaking of a ‘cup on a table’, this implies a ‘spatial structure’ with a ‘stands-on’ or ‘is-under’ relation. Moreover, the writer-reader of a text ‘knows’ that normally a cup is not on a table, but only when someone has explicitly put the cup there. A sequence of expressions like ‘Gerd puts the cup on the table. When Peter comes in he sees that there is a cup on the table’ then appears to a reader as ‘normal/ usual/ accustomed’. But if the text would say ‘When Peter comes in, he sees that there is a cup on the table. Gerd puts the cup on the table’, then a normal reader would stop and ask himself what the text wants to say: The cup is on the table and only then it is put on the table?
This simple example demonstrates besides an ‘implicit spatial structure’ also an ‘implicit temporal structure: In everyday experience, embedded in an external body world, it is normal that properties – and thus a whole situation – can change. However, these changes do not happen (! ) in the sensory perception (the present as such is ‘absolute’), but are only revealed in the ‘downstream processing’ by the brain, which is able to ‘store’ partial aspects of a current sensory perception in such a way (a highly complex neuronal process), that it can ‘remember’ these ‘stored structures’ again (also a highly complex neuronal process) and additionally ‘compares’ them with ‘other memory contents’ in such a way (also a highly complex neuronal process) that our brain can thereby reconstruct a ‘sequence’ as well as ‘identify’ possible ‘changes between single elements of the sequence’. Because of this highly complex mechanism the brain can break up/ overcome the ‘absoluteness of the present’ by ‘remembering and comparing’.
A ‘normal text’ has many more special properties. Here, first of all, it is only important to see that it is the dimension of ‘linguistic meaning’ localized ‘in’ a human writer-reader, through which a set of linguistic expressions can induce a complex ‘network of properties’ that have their ‘own linguistically induced logic’.
Linguistic Communication
Again, the whole spectrum of possible properties of ‘linguistic communication’ shall not be described here – a ‘sea’ of articles and books would could to be cited here – but only a few aspects shall be addressed which suggest themselves from the previous considerations on texts.
If the previous ‘working hypothesis on linguistic meaning’ is correct, then written linguistic expressions have the function to enable ‘between two brains’ a a ‘medium’ suitable to make so-called ‘signs’ out of the ‘linguistic expressions’. [2] A sign is a sensually perceptible material that can be related by ‘sign users’ to an ‘agreed space of sign meanings’. These agreed sign meanings are localized as such ‘in the head’ of the respective sign users, but they have the peculiarity that the different sign users have ‘learned’ by common ‘training’ which ‘sensuously perceptible realities of the external body world’ are to be linked with certain sign (material). If such a ‘coordination’ of sign(material) and sign-meaning succeeds (all children of this world practice this form of training in spontaneous language learning), a single sign-user can ‘hint’ at certain ‘elements of his meaning-space’ by practicing certain sign-connections to another trained sign-user. Through a ‘back and forth’ of statements, questions, possibly also interpretative gestures in a real situation, a certain ‘understanding’ can then – usually – be established. The more complex the circumstances are, the further away one is from a concrete situation, the more difficult it becomes to ‘convey’ what is meant sufficiently clearly.
What does all this mean in concrete terms?
For this we look at further examples realized with oksimo.R texts.
COMMENTS
[1] Even in the area of ‘normal’ English texts, there is a great variety of texts that make very special demands on ‘filling in’.
[2] There are numerous disciplines in academia that deal more or less ‘generally’ with properties of ‘normal’ languages and communication with normal languages. The discipline that actually does this most ‘generally’, ‘semiotics’, still leads a rather ‘shadowy existence’ worldwide next to the ‘established’ other disciplines. Here, too, there exists a myriad of articles and books on the subject.
Recommended further Reading
It is recommended to continue reading from here with the section about a daily routine HERE.
A normal everyday scene is used to illustrate some properties of modeling (theory building) in the oksimo.R paradigm. This case is about a person who works in a university, has an office there (together with others), and ‘feels hungry’ around noon. This becomes the occasion for this person to decide to go out to eat. In this case ‘to the Greek around the corner’. The short story ends with this person no longer feeling hungry.
OKSIMO.R TEXT TYPES
Modeling (theory building) in the oksimo.R paradigm takes place by a group of people working together to formulate a text in a common language. In the concrete case, this is the German language; however, it can also be any other language.
Three types of texts are distinguished:
ACTUAL descriptions (initial situations)
TARGET descriptions (requirements)
CHANGE descriptions (rules for change)
These distinctions presuppose that a human actor can distinguish between such ideas in his head, which ‘correspond’ to experiences outside his brain (in ‘his own body’, in the ‘body world outside his body’), and such ideas in his head, which he thinks/remembers/dreams/fantasizes ‘alone’, ‘for himself’ … .
ACTUAL situation
Here, ACTUAL descriptions refer to such ideas that relate to the body world beyond the own body and that can be ‘shared’ by other human actors. For example, if someone stands outside and says “It is raining”, and all bystanders would confirm this, then this would be a case of an ACTUAL-description that can be ‘confirmed’ by all. Most of the time people then also say that this description is ‘true’. If in this situation, where it is raining, someone would say “It is not raining” then everyone – usually – would say that this ‘statement’ is ‘false’. If someone says instead “It will rain soon”, then all bystanders who understand English will be able to form an idea in their brain that it is raining, but there is then no concrete equivalent to this idea in the real interpersonal physical world. This statement would then be neither ‘true’ nor ‘false’. Its relation to the ‘common body world’ would be ‘indeterminate’: it may perhaps become true, but need not.
GOAL description
TARGET descriptions (also in the form of requirements) refer to such ‘imaginations in the minds of actors’ to which there are accepted linguistic expressions, but which at the moment of writing or saying do not yet have a correspondence in the shared physical world. The ideas belonging to a merely imagined description of a goal have a greater or lesser probability of possibly occurring ‘sometime in the future’. Either there are ‘experiences’ from the past, which suggest an occurrence or there is only the ‘wish’ that these conceptions become real.
CHANGE Descriptions
CHANGE descriptions refer to such ‘events’ or ‘measures’ of which one knows (or strongly assumes) that their occurrence or their implementation ‘changes’ a given situation (ACTUAL) in at least one property in such a way that after a ‘certain time’ (‘time interval’) the ‘old’ situation represents a ‘new’ situation due to the ‘change’, which then becomes the ‘new ACTUAL situation’ as ‘successor situation’. Further events or measures can also change this new actual situation again.
Required Text Sets
While one needs at least one ACTUAL situation and at least one CHANGE description for an oksimo.R modeling (theory building), a TARGET description is optional. If no TARGET description is given, then there is a – more or less – directed or open sequence of ACTUAL states, which can arise by – also repeated – ‘applications’ of the CHANGE descriptions to a given ACTUAL situation. If at least one TARGET description is available, then this can be used to ‘evaluate’ a current ACTUAL situation according to how many elements of the TARGET situation are already present in the ACTUAL situation. This can be between 0% and 100%.
Applying change descriptions to an ACTUAL situation.
For applying a change description to a given ACTUAL situation, one must understand that in the oksimo.R paradigm a TEXT is nothing but a set of LANGUAGE EXPRESSIONS whose ‘meaning’ is known only by the speakers. Each linguistic expression is considered as an ‘element’ of this ‘expression set’ called text , and it is assumed that each linguistic expression describes some ‘property’ of the real ACTUAL situation. An imputed ACTUAL situation has exactly as many properties as the TEXT of the ACTUAL situation contains linguistic expressions. The amount of the imputed properties of a situation represent only a true subset of the real situation. If a certain expression is removed from the text, the associated property disappears; if a new linguistic expression is added, then a new property is created in the imputed ACTUAL situation.
A CHANGE description (also ‘change rule’ or simply ‘rule’) must therefore minimally do the following:
Specify which expressions are to be added (generate new properties)
Specify which of the previous expressions should be removed (eliminate properties).
In order to keep the application of the rule ‘under control’, one should make the application of a change rule to a current ACTUAL situation dependent on CONDITIONS in such a way that one prefixes the change specifications for ‘adding’ or ‘removing’ with a set of expressions, which must be given in the ACTUAL-description; otherwise the change rule can not become ‘active’.
Simple example
ACTUAL situation:
Gerd is sitting in his office. Gerd is hungry.
TARGET situation:
Gerd is not hungry.
CHANGE Description:
IF: Gerd is hungry. THEN: Add as a property to the ACTUAL situation: Gerd leaves his office. Remove as property from the ACTUAL situation: Gerd is sitting in his office.
APPLICATION of the change description:
The CONDITION is fulfilled.
THEN:
NEW ACTUAL situation:
Gerd leaves his office. Gerd is hungry.
EVALUATION:
The property from the GOAL: ‘Gerd is not hungry’ is not yet fulfilled, so: Success so far: 0%.
REPEATED APPLICATION
Each change rule can in principle be applied as often as possible, but only as long as the CONDITION is fulfilled.
In the example above, the CONDITION ‘Gerd is hungry’ would continue to be fulfilled, but a repeated application of the rule will not change the situation any further. Thus, it is foreseeable that the TARGET condition can never be reached in this model (in this theory).
Example with oksimo.R software
Contextualization of the software
The oksimo.R software is part of the ‘oksimo.R paradigm’. The oksimo.R paradigm includes three components: (i) As an ‘application format’ a set of arbitrary citizens who see themselves as ‘natural experts’ who ‘work together scientifically’. This format is called ‘citizen science 2.0’ in the context of the oksimo.R paradigm. (ii) The ‘oksimo.R software’ that can be used by citizens to formulate (‘edit’) their scientific descriptions of the experiential world in such a way that they ‘automatically’ meet the requirements of an ’empirical theory’, so as to be able to draw ‘inferences’ at any time, practiced as ‘simulations’. (iii) A clear concept of an ’empirical theory’ compatible with all known forms of ’empirical sciences’ (in fact, the general form of the oksimo.R theory concept can also represent all forms of non-empirical theories).
The oksimo.R software is currently being developed and deployed on a server in the Internet, accessible via the address oksimo.com.
Since the theoretical concept of the oksimo.R software covers almost everything we know so far as a software application in the Internet (including the various forms of ‘Artificial Intelligence (AI)’ and ‘Internet of Things (IoT)’), the transformation of the theoretical concept into applicable software is generally an ‘infinite process’. As of this writing (Nov 16, 2022), Level 2 is directly available and work is underway with Level 3 (and there will be much more levels in the future …)
An oksimo.R theory REALIZED WITH the software (Still level 2)
The old menu – still in command line mode – shows up as follows after logging in:
Welcome to Oksimo v2.1 02 May 2022 (ed14)
MAIN MENU 1 is NEW VISION 2 is MANAGE VISIONS 3 is VISION COLLECTIONS 4 is NEW STATE 5 is MANAGE STATES 6 is STATE COLLECTIONS 7 is NEW RULE 8 is MANAGE RULES 9 is RULE DOCUMENT 10 is NEW SIMULATION 11 is MANAGE SIMULATIONS 12 is LOAD SIMULATION 13 is COMBINE SIMULATIONS 14 is SHARE 15 is EXIT SIMULATOR Enter a Number [1-15] for Menu Option
See: oksimo.com (16.Nov. 2022)
In the old command line mode you have to enter the oksimo.R texts manually. For the ACTUAL state this looks like this:
Enter ACTUAL description
Enter a Number [1-15] for Menu Option
4
Here you can describe an actual state S related to your problem.
Enter a NAME for the new state description:
Food1
Enter an expression for your state description in plain text:
Gerd is sitting in his office.
Expressions so far: Gerd is sitting in his office.
Enter another expression or leave blank to proceed:
Gerd is hungry.
Expressions so far: Gerd is sitting in his office. Gerd is hungry.
Enter another expression or leave blank to proceed:
Name: Food1 Expressions: Gerd is sitting in his office. Gerd is hungry.
Note: In the Level 2 version an ACTUAL description is generally only called ‘state’.
Enter VISIONs text
Enter a Number [1-15] for Menu Option
1
Here you can describe your vision.
Enter a NAME for the new vision:
Food1-v1
Enter an expression for your vision in plain text:
Gerd is not hungry.
Expressions so far: Gerd is not hungry.
Enter another expression or leave blank to proceed:
Your final vision document is now: Name: Food1-v1 Expressions: Gerd is not hungry.
Enter CHANGE rule
Enter the name of the new rules document:
Food1-Decision1
Enter condition:
Gerd is hungry.
Conditions so far: Gerd is hungry.
Enter another condition or leave blank to proceed:
Enter a probability between 0.0 and 1.0:
1.0
(Comment: The ‘Probability’ feature at this point is now obsolete. Probabilities are handled more generally and flexibly. Examples follow.)
Enter positive effect:
Gerd leaves his office.
Positive Effects so far: Gerd leaves his office.
Enter another positive effect or leave blank to proceed:
Enter negative effect:
Gerd is sitting in his office.
Negative Effects so far: Gerd is sitting in his office.
Enter another negative effect or leave blank to proceed:
Summary: Rule:Food1-Decision1 Conditions:Gerd is hungry.
Probability: 1.0 Positive Effects: Gerd leaves his office.
Negative Effects: Gerd is sitting in his office.
Test the effect of the theory
Test conclusions
The ‘core of an oksimo.R theory’ consists of the two components ACTUAL situation (here: state) and CHANGE rule (here: rule). By applying a rule to a state, a successor state is created, which is ultimately an ‘inference’ (a ‘theorem’) of the theory. The more complex the initial state is and the more change rules there are, the more diverse the set of possible consequences (‘inferences’, ‘theorems’) becomes. To keep track of these consequences, especially if the rules of change can be applied again and again to a successor state, so that an ever longer sequence of states emerges out of this, this can become very difficult.
Test target fulfillment
If you use an oksimo.R theory kernel together with a TARGET description, then during the inference process (the ‘simulation’) you can also check at any point how many ‘elements of the TARGET description’ already ‘occur’ in an inferred state. If ‘all’ elements of the GOAL-description occur, the theory is able to ‘infer’ 100% of the GOAL-description, otherwise less, down to 0% goal fulfillment.
Start an oksimo.R simulation
Enter a Number [1-15] for Menu Option
10
Here you can run a simulation SIM to check what happens with your initial state S when the change rules X will be applied repeatedly on the state S.
Available vision descriptions:
…
Food1-v1
…
Enter a name for a vision description you want to load. Use prefix col to load a collection:
Food1-v1
Visions selected so far: Food1-v1
Add another vision or leave blank to proceed:
Enter a name for a state description you want to load. Use prefix col to load a collection:
Food1
States selected so far: Food1
Add another state or leave blank to proceed:
Selected states: Food1
Available rules:
…
Food1-Decision1
…
Enter a name for a rule or a ruledocument (with prefix doc) you want to load:
Food1-Decision1
Rules selected so far: Food1-Decision1 Add another rule or leave blank to proceed:
Initial states: Gerd is hungry.,Gerd is sitting in his office.
Round 1
…
Round 3
…
Save Simulation [S], Rerun simulation [R], export as text [T] or exit [leave blank]:
S
Enter Name for Simulation:
Food1-sim1
Saved!
Enter a Number [1-15] for Menu Option
12
Here you can load a previously saved simulation and rerun it. Add prefix dev for detailed developer-mode.
List of your saved simulations:
…
Food1-sim1
…
Restart the saved simulation with 12 Load Simulation (Comment: The math-elements are deleted from the protocol because these will be used a little bit later):
our vision:
Gerd is not hungry.
Initial states:
Gerd is hungry.,Gerd is sitting in his office.
Round 1
Current states: Gerd is hungry.,Gerd leaves his office.
Current visions: Gerd is not hungry.
Current values:
0.00 percent of your vision was achieved by reaching the following states:
None
And the following math visions:
None
Round 2
Current states: Gerd is hungry.,Gerd leaves his office.
Current visions: Gerd is not hungry.
Current values:
0.00 percent of your vision was achieved by reaching the following states:
None
And the following math visions:
None
One can easily see, that the state of round 2 is repeating. And there is no reason, that this will change in the future.
Rule application and inference concept
The preceding simple example was used to explain concretely what happens when a rule is applied to a given ACTUAL situation. A science which deals with such change processes by means of rule application(s) is ‘logic’. Logic considerations have been around for more than 2500 years, in many different forms. The most significant logic paradigms in retrospect are possibly the logic associated with the name of Aristotle, in which logical expressions were not yet considered in isolation from possible linguistic meanings, and modern formal logic, in which logical expressions have no connection to any linguistic meaning except with abstract ‘truth values’. The history of modern formal logic began in the 19th century about 150 years ago (Bool, de Morgan, Venn, Frege, Russell, …).
The central idea of any logic is to find a ‘procedure that allows the user to ‘derive’ from a set of ‘assumed to be (abstractly) true’ statements only those statements that are also ‘(abstractly) true’ again. The ‘abstract truth’ of modern formal logic is a ‘placeholder’ for an everyday language truth which cannot be expressed as such within a formal logic. Formal logic presupposes that there are ‘actors’ who ‘know’ what they are saying when they speak of a ‘true’ statement. Whether the formalization of ‘truth relations’ between different sets of expressions in the format of modern formal logic ‘adequately’ represent the meaning knowledge of the actors can therefore not be decided ‘within the logical system’, but only ‘from outside’, from the perspective of the ‘meaning knowledge of the acting actor’.
If one calls the initial set of linguistic expressions ‘assumed to be abstractly true’ an IS-description (in the style of the oksimo.R paradigm) and the set of possible ‘derived expressions assumed to be abstractly true’ the ‘inferred abstractly true expressions’, then one could formulate this in the style of formal logic as follows:
The character ‘⊢’ represents an inference term. This consists of a text describing how to apply a change rule from the set R to a given set of expressions X in such a way that a new set X’ is created as a result of the application to the given set X. The inference term must be of such a nature that it is completely unambiguous ‘what to do’.
The claim of the ‘pure formal logic’ of the modern times that all expressions, which are generated with the inference term, are also conform to the ‘assumed abstract truth value’, applies in the same way to the inference term of the oksimo.R theory software too. With the oksimo.R inference term it is guaranteed that all ‘generated expressions’ are ‘true’ in the sense of the ‘linguistically founded meaning knowledge’ of the involved ‘actors’! However, linguistically grounded meaning knowledge is ‘knowledge dependent’ and therefore can be empirically either ‘true’ or ‘false’ or ‘indeterminate’. This points to the fact that in general the actors are the ‘gatekeepers of the truth’. Actors formulate the change-rules R based on their linguistic knowledge. If these change-rules R are ‘true’, then this is also true for the linguistic expressions generated by means of inference. If the change rules R contain an ‘error’, then this error will necessarily be contained in the generated inference situation X’ as description element E. This expression element E as part of the prediction set X’ may then turn out to be either ‘true’ in the further course of comparison with the commonly shared empirical reality, or it will remain ‘indeterminate’ in the long run, since it neither becomes ‘true’ nor can be directly classified as ‘false’. In the case of modern formal logic, the empirical truth status of inferred expressions is completely indeterminate.
The oksimo.R inference concept united the formal advantages of modern formal logic with the meaning reference of Aristotelian logic and is understood as a ‘natural means of expression’ for an empirical theory with truth claim.
In the introduction of the main text it has been underlined that within a sustainable empirical theory it is not only necessary to widen the scope with a maximum of diversity, but at the same time it is also necessary to enable the capability for an optimal prediction about the ‘possible states of a possible future’.
the meaning machinery
In the text after this introduction it has been outlined that between human actors the most powerful tool for the clarification of the given situation — the NOW — is the everyday language with a ‘built in’ potential in every human actor for infinite meanings. This individual internal meaning space as part of the individual cognitive structure is equipped with an ‘abstract – concrete’ meaning structure with the ability to distinguish between ‘true’ and ‘not true’, and furthermore equipped with the ability to ‘play around’ with meanings in a ‘new way’.
COORDINATION
Thus every human actor can generate within his cognitive dimension some states or situations accompanied with potential new processes leading to new states. To share this ‘internal meanings’ with other brains to ‘compare’ properties of the ‘own’ thinking with properties of the thinking of ‘others’ the only chance is to communicate with other human actors mediated by the shared everyday language. If this communication is successful it arises the possibility to ‘coordinate’ the own thinking about states and possible actions with others. A ‘joint undertaking’ is becoming possible.
shared thinking
To simplify the process of communication it is possible, that a human actor does not ‘wait’ until some point in the future to communicate the content of the thinking, but even ‘while the thinking process is going on’ a human actor can ‘translate his thinking’ in language expressions which ‘fit the processed meanings’ as good as possible.Doing this another human actor can observe the language activity, can try to ‘understand’, and can try to ‘respond’ to the observations with his language expressions. Such an ‘interplay’ of expressions in the context of multiple thinking processes can show directly either a ‘congruence’ or a ‘difference’. This can help each participant in the communication to clarify the own thinking. At the same time an exchange of language expressions associated with possible meanings inside the different brains can ‘stimulate’ different kinds of memory and thinking processes and through this the space of shared meanings can be ‘enlarged’.
phenomenal space 1 and 2
Human actors with their ability to construct meaning spaces and the ability to share parts of the meaning space by language communication are embedded with their bodies in a ‘body-external environment’ usual called ‘external world’ or ‘nature’ associated with the property to be ‘real’.
Equipped with a body with multiple different kinds of ‘sensors’ some of the environmental properties can stimulate these sensors which in turn send neuronal signals to the embedded brain. The first stage of the ‘processing of sensor signals’ is usually called ‘perception’. Perception is not a passive 1-to-1 mapping of signals into the brain but it is already a highly sophisticated processing where the ‘raw signals’ of the sensors — which already are doing some processing on their own — are ‘transformed’ into more complex signals which the human actor in its perception does perceive as ‘features’, ‘properties’, ‘figures’, ‘patterns’ etc. which usually are called ‘phenomena’. They all together are called ‘phenomenal space’. In a ‘naive thinking’ this phenomenal space is taken ‘as the external world directly’. During life a human actor can learn — this must not happen! –, that the ‘phenomenal space’ is a ‘derived space’ triggered by an ‘assumed outside world’ which ’causes’ by its properties the sensors to react in a certain way. But the ‘actual nature’ of the outside world is not really known. Let us call the unknown outside world of properties ‘phenomenal space 1’ and the derived phenomenal space inside the body-brain ‘phenomenal space 2’.
TIMELY ORDERING
Due to the availability of the phenomenal space 2 the different human actors can try to ‘explore’ the ‘unknown assumed real world’ based on the available phenomena.
If one takes a wider look to the working of the brain of a human actor one can detect that the processing of the brain of the phenomenal space is using additional mechanisms:
The phenomenal space is organized in ‘time slices’ of a certain fixed duration. The ‘content’ of a time slice during the time window (t,t’) will be ‘overwritten’ during the next time slice (t’,t”) by those phenomena, which are then ‘actual’, which are then constituting the NOW. The phenomena from the time window before (t’,t”) can become ‘stored’ in some other parts of the brain usually called ‘memory’.
The ‘storing’ of phenomena in parts of the brain called ‘memory’ happens in a highly sophisticated way enabling ‘abstract structures’ with an ‘interface’ for ‘concrete properties’ typical for the phenomenal space, and which can become associated with other ‘content’ of the memory.
It is an astonishing ability of the memory to enable an ‘ordering’ of memory contents related to situations as having occurred ‘before’ or ‘after’ some other property. Therefore the ‘content of the memory’ can represent collections of ‘stored NOWs’, which can be ‘ordered’ in a ‘sequence of NOWs’, and thereby the ‘dimension of time’ appears as a ‘framing property’ of ‘remembered phenomena’.
Based on this capability to organize remembered phenomena in ‘sequences of states’ representing a so-called ‘timely order’ the brain can ‘operate’ on such sequences in various ways. It can e.g. ‘compare’ two states in such a sequence whether these are ‘the same’ or whether they are ‘different’. A difference points to a ‘change’ in the phenomenal space. Longer sequences — even including changes — can perhaps show up as ‘repetitions’ compared to ‘earlier’ sequences. Such ‘repeating sequences’ can perhaps represent a ‘pattern’ pointing to some ‘hidden factors’ responsible for the pattern.
formal representations [1]
Basic outline of human actor as part of an external world with an internal phenomenal space 2, including a memory and the capability to elaborate cognitive meta-levels using the dimension of time. There is a limited exchange medium between different brains realized by language communication. Formal models are an instrument to represent recognized timely sequences of sets of properties with typical changes.
Based on a rather sophisticated internal processing structure every human actor has the capability to compose language descriptions which can ‘represent’ with the aid of sets of language expressions different kinds of local situations. Every expression can represent some ‘meaning’ which is encoded in every human actor in an individual manner. Such a language encoding can partially becoming ‘standardized’ by shared language learning in typical everyday living situations. To that extend as language encodings (the assumed meaning) is shared between different human actors they can use this common meaning space to communicate their experience.
Based on the built-in property of abstract knowledge to have an interface to ‘more concrete’ meanings, which finally can be related to ‘concrete perceptual phenomena’ available in the sensual perceptions, every human actor can ‘check’ whether an actual meaning seems to have an ‘actual correspondence’ to some properties in the ‘real environment’. If this phenomenal setting in the phenomenal space 2 with a correspondence to the sensual perceptions is encoded in a language expression E then usually it is told that the ‘meaning of E’ is true; otherwise not.
Because the perceptual interface to an assumed real world is common to all human actors they can ‘synchronize’ their perceptions by sharing the related encoded language expressions.
If a group of human actors sharing a real situation agrees about a ‘set of language expressions’ in the sens that each expression is assumed to be ‘true’, then one can assume, that every expression ‘represents’ some encoded meanings which are related to the shared empirical situation, and therefore the expressions represent ‘properties of the assumed real world’. Such kinds of ‘meaning constructions’ can be further ‘supported’ by the usage of ‘standardized procedures’ called ‘measurement procedures’.
Under this assumption one can infer, that a ‘change in the realm of real world properties’ has to be encoded in a ‘new language expression’ associated with the ‘new real world properties’ and has to be included in the set of expressions describing an actual situation. At the same time it can happen, that an expression of the actual set of expressions is becoming ‘outdated’ because the properties, this expression has encoded, are gone. Thus, the overall ‘dynamics of a set of expressions representing an actual set of real world properties’ can be realized as follows:
Agree on a first set of expression to be a ‘true’ description of a given set of real world properties.
After an agreed period of time one has to check whether (i) the encoded meaning of an expression is gone or (ii) whether a new real world property has appeared which seems to be ‘important’ but is not yet encoded in a language expression of the set. Depending from this check either (i) one has to delete those expressions which are no longer ‘true’ or (ii) one has to introduce new expressions for the new real world properties.
In a strictly ‘observational approach’ the human actors are only observing the course of events after some — regular or spontaneous –time span, making their observations (‘measurements’) and compare these observations with their last ‘true description’ of the actual situation. Following this pattern of behavior they can deduce from the series of true descriptions <D1, D2, …, Dn> for every pair of descriptions (Di,Di+1) a ‘difference description’ as a ‘rule’ in the following way: (i) IF x is a subset of expressions in Di+1, which are not yet members of the set of expressions in Di, THEN ‘add’ these expressions to the set of expressions in Di. (ii) IF y is a subset of expressions in Di, which are no more members of the set of expressions in Di+1, THEN ‘delete’ these expressions from the set of expressions in Di. (iii) Construct a ‘condition-set’ of expressions as subset of Di, which has to be fulfilled to apply (i) and (ii).
Doing this for every pair of descriptions then one is getting a set of ‘change rules’ X which can be used, to ‘generate’ — starting with the first description D0 — all the follow-up descriptions only by ‘applying a change rule Xi‘ to the last generated description.
This first purely observational approach works, but every change rule Xi in this set of change rules X can be very ‘singular’ pointing to a true singularity in the mathematical sense, because there is not ‘common rule’ to predict this singularity.
It would be desirable to ‘dig into possible hidden factors’ which are responsible for the observed changes but they would allow to ‘reduce the number’ of individual change rules of X. But for such a ‘rule-compression’ there exists from the outset no usable knowledge. Such a reduction will only be possible if a certain amount of research work will be done hopefully to discover the hidden factors.
All the change rules which could be found through such observational processes can in the future be re-used to explore possible outcomes for selected situations.
COMMENTS
[1] For the final format of this section I have got important suggestions from René Thom by reading the introduction of his book “Structural Stability and Morphogenesis: An Outline of a General Theory of Models” (1972, 1989). See my review post HERE : https://www.uffmm.org/2022/08/22/rene-thom-structural-stability-and-morphogenesis-an-outline-of-a-general-theory-of-models-original-french-edition-1972-updated-by-the-author-and-translated-into-english-by-d-h-fowler-1989/
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 will discuss parts of the book “Structural Stability and Morphogenesis: An Outline of a General Theory of Models” from René Thom, originally as a French edition 1972, after several new editions updated in 1988 by the author and translated by H.D.Fowler 1988 into English, published 1989.
CONTEXT
In the foundational post with the title “COMMON SCIENCE as Sustainable Applied Empirical Theory, besides ENGINEERING, in a SOCIETY” a central idea is that a sustainable society has besides the challenge of the right usage of resources the other big challenge related to the ‘cognitive dimension’ as medium of its coordinated actions addressing a sufficiently well prepared planet for the survival of the biosphere in the future. Part of the cognitive dimension is the ability to ‘predict’ a — hopefully — ‘optimal’ course of events leading into the future as a guideline for the life today. It appears to the author of this review that the book of René Thom can give some ‘advice’ for a deeper understanding of the nature of ‘prediction’ using ideas of mathematics, especially ‘topology’ and ‘catastrophe theory’.
Mapping Nature into Formal Models
This figure shows some part of the introduction of René Thom’s book. Look to the text for a comment.
the big picture first
There are multiple ways to approach the ideas of René Thom in his introduction. Let us try an approach coming from the ‘outside’ and then ‘digging into the hidden structures’.
The outside framework is characterized by nature, the ‘real world outside’, by human actors occurring in this world with their bodies, and ‘language communication’ between human actors.
With regard to ‘language’ Thom cites many different ‘variants of language’ besides the ‘everyday language’ like ‘formal logic’, ‘formal systems’, ‘propositions’ etc., but he does not give a systematic account of these different variants; he does not explain the systematic relationships between these different variants.
The inward interaction between the real world outside and a human actor is characterized by ‘perception’. Perception maps properties of the outside world into the inner states of the body, especially into the brain, but Thom never mentions the brain explicitly. These mapped properties from the outside world inside the body are circumscribed for instance as ‘local situations’, ‘beings, objects, things’, ‘change of forms’, ‘degree of stability’, ‘different guises’. But because Thom doesn’t offer some explicit conceptual framework of the ‘inner space’ of a human actor, these concepts have no clear meaning. They only ‘trigger’ in the reader some associations in his everyday language understanding of some possible related meanings without a clear context.
Thom’s remark of a ‘phenomenological space’ remains a bit ‘cryptic’. In science it is common to associate the ‘phenomenological space’ with the way how the ‘world outside’ ‘appears to us’, but — using philosophical reasoning enhanced by brain science and experimental psychology — the properties of the outside world ‘as such’ are not available for the brain in the body. Only the ‘transformation’ of the outside world properties to the different perceptional organs of the body and their processing during ‘perception’ — thereby interacting at least with the memory — enables some ‘neuronal signals’ which are the ‘base ground’ for our brain to ‘compute’ some structures which we are using as ‘phenomena’ in our ‘conscious thinking’. Thus from the point of view of modern philosophy the ‘phenomenal space’ appears to be a space ‘inside the brain’, and this space is accompanied by the ‘unconscious space of cognition’, who is doing the ‘real job’; the ‘phenomenal space’ seems — today — to be a function of this unconscious cognitive space.
Despite the ‘vagueness’ of the descriptive wordings so far Thom introduces more concepts of the ‘inner world’, which seem to be intended as to differentiate the other words a little bit more.
Thus, the ‘infinite manifestations’ of the ‘appearing different guises’ of things can be ‘recognized as the same structure’, or that we ‘assume the existence of the outside world’ ‘independent of our own observation’.
With regard to ‘local situations’ which we can recognize, he reflects about the possible ‘influence of unknown/ unobservable factors’ which can cause ‘different outcomes’, that means different changes in the local situations.
More generally he thinks about the ‘universe’ as a ‘ceaseless creation’, which manifests itself in an ‘evolution’, which is accompanied by a ‘destruction of forms’. The destruction of forms is the same as the ‘change of forms’, which Thom classifies as ‘not rigorous deterministic’, hence ‘indeterministic’. The other aspect of ongoing changes is a ‘temporal dimension’ showing up; translated in a certain kind of ‘ordering’ these changes can be ‘translated’ into a formalization as a succession of states. Each state will be represented by a ‘set of properties’. With the aid of some logical inference mechanism it is possible to ‘transform’ one set of properties into another set of properties, including a measure for the probability, that the next set of properties will be inferred.
While the real world as such appears to us as some infinite source of phenomena with an unknown number of hidden factors are the elements of the outside world in general somehow infinite and indeterministic in their occurrence. But a human actor looking into this phenomenal space he can decide to assume the open character of phenomena as being describable as clear-cut finite things — as in ‘classical mechanics’ –, which allows a ‘deterministic’ handling of the phenomena. With other conceptual strategies — like in ‘quantum mechanics’ — the primary phenomena are classified as ‘indeterministic by nature’ which translates into logical inferences which are also ‘indeterministic’.
The overall purpose of science sees Thom as given in the intention to ‘foresee change of form’ and to ‘explain change of form’.
observables – local models – ultimate natuRe of reality
Thom points out that finally for a ‘macroscopic description of a system’ only the ‘observables’ of a local system are available.(cf. p.6f) What is ‘behind’ these observables, what exactly has to be understood by the ‘ultimate nature of reality’, this cannot completely be covered by a local system, by no local system.(cf. p.6f) Whether all local systems can finally be integrated into one coherent global system is an open question.(p.7)
a mathematics of discontinuities?
Thom considers further the fact that in common everyday experience we encounter many phenomena which appear in themselves to be very trivial but which are opposing a simple mathematical description.(cf. p.9) The main characteristic of these everyday phenomena is ‘discontinuity’. Because all applicable quantitative mathematical models rely on ‘continuity’ and ‘continuous functions’ this reduces the probability that science starts to describe ‘discontinuity’.(cf. p.9) Nevertheless there are more and more disciplines which are confronted with ‘discontinuous’ phenomena, which are ‘unstable’, show nearly ‘no repetition’ and do not fit easily in a mathematical model.(cf. p.9)
Thom gives a short outline of an idea how to cope with discontinuity by constructing a model of a set M of ‘observables’ which as such are ‘stable’, but they include a closed subset K of ‘catastrophes’ which manifest themselves as ‘singularities’ provoking a ‘discontinuity’ which can cause a ‘change’ on the observables, which constitutes the global phenomenon of ‘morphogenesis’.(cf. p.7) By not knowing in advance the ‘dynamics’ X underlying these changes it is possible to ‘reconstruct’ (step-wise) the underlying dynamics X by observing the global morphogenesis by recurring to the local changes too.(cf. p.7)
Thom underlines that it is not the local singularity as such which manifests the underlying dynamics X but the ‘accumulation’ of all singularities into ‘one global phenomenon’, which has to be explained.(cf. p.8) And because the ‘statistics’ of the local changes, which can be correlated with the local accidents, is determined by the underlying dynamics, it will not suffice to rely only on a local change; all changes together have to be explained. This can imply more than three dimensions of an euclidean space.(cf. p.8)
Discussion of Thom’s Position
There are some aspects which could be discussed in front of Thom’s position.
One major point could be his ‘vagueness’ with regard to the inner structure and processing of a human actor. Since 1972 (1989) many new deep insights have been revealed by disciplines like brain sciences in connection with experimental psychology and biology. I will not discuss this point here. There are several posts in the uffmm.org blog which are dealing with these topics.
What catches the attention of the reviewer here is the position of Thom considering the phenomenon of ‘discontinuities’ (changes) which not as a ‘single change’ represent a phenomenon but as a ‘series of changes’ which can not be classified as a ‘classical quantitative continuous’ phenomenon.
He thinks that especially ‘topological thinking’ can be of help here.
Comparing Thom’s position with the position of the the concept of a ‘sustainable empirical theory’ as it is outlined in the uffmm.org blog, especially condensed as a ‘theory producing process’ called ‘oksimo-R process paradigm’, it seems to be not only possible to solve the problem without topology, but — perhaps — even better without topology.
This results from the fact that the oksimo-R process paradigm presupposes a conceptual framework where not only the human actor as ‘theory producer’ is assumed to be located with his body in a ‘body-external empirical world’, but there exist also some additional assumptions about the ‘internal structure’ and the ‘internal processing’ of human actors, which are ‘explaining’ to a certain degree how a human actor can process properties of his environment — including his own body — within a cognitive and emotional space as well how he can ‘map’ parts of these spaces into sets of expressions of his everyday language. Based on such a ‘process model’ of a human actor it is possible to ‘explain’ additionally the language-based communication between different human actors whereby the different brains in the bodies can share some knowledge and emotions and can coordinate their actions.
The concept of a formal model which Thom introduced before can in the light of a more advanced actor model be interpreted in a way, that it allows all the solutions which Thom claims for his topological minded approach.
Which series of ‘changes’ (maybe ‘catastrophes’) will attract the attention of some researchers, the researcher are every time capable to do the following:
Write a series of texts representing the observed phenomena at location L and time T in accordance with their learned and agreed meaning functions (a set of propositions).
This will result in a series of texts (documents) <D1, D2, …, Dn>, whose logical ordering represents the timely order.
Because every ‘difference’ between two consecutive documents (Di,Di+1) is directly observable in the language expressions one can ‘translate’ these differences directly by a rule following a general format: (i) IF x is a subset of expressions in Di+1, which are not yet members of the set of expressions in Di, THEN ‘add’ these expressions to the set of expressions in Di. (ii) IF y is a subset of expressions in Di, which are no more members of the set of expressions in Di+1, THEN ‘delete’ these expressions from the set of expressions in Di. (iii) Construct a ‘condition-set’ of expressions as subset of Di, which has to be fulfilled to apply (i) and (ii).
After the translation of all observed differences between consecutive documents one has a set of ‘change rules X’, which together with the ‘Start Document’ D0 define an ‘accumulated rule’ for a series of discontinuous changes: <D0, X>
Probably a first ‘guess’ of an accumulated rules will be not too ‘precise’. Thus by collecting more ‘observations’ one can try to ‘refine’ the rules, even including local probabilities, which during ‘processing’ (inference, simulation) can produce an ‘accumulated and composed’ probability of some ‘weird’ kind.[1]
COMMENTS
[1] This view of composed probabilities is in a good agreement with the ideas of the late Karl Popper discussing ‘propensities’ (see several posts in this uffmm.org blog: https://www.uffmm.org/2021/03/15/philosophy-of-science/)
Today we are living in a world where we are flooded with information of all kinds from all directions. It is nearly impossible to collect, order and evaluate all this in some systematic way (not least because the available ordering systems as such are themselves mostly ‘dynamic’ changing often in the course of time).
Even in the realm of science, where things are — at least by the intention — mostly methodologically organized and transparent, we can observe an explosion of more and more specializations accompanied by less and less integration. Comparable a little bit to a planet earth which is losing its atmosphere, science seems to lose its ‘meta level knowledge’ which is important to connect and integrate all the many divers individual science parts. Some would perhaps say that there was never such a ‘meta level knowledge’; others perhaps will even deny that such a ‘meta level knowledge’ is possible at all.
In the long run a multitude of different knowledge spaces which are not integrated will destroy themselves. Science will turn into noise only.
A science which by its history and its self-conception should be able to solve this challenge in close collaboration with all scientific disciplines is philosophy with all its sub fields. But by many reasons this does not really work. We have no elaborated theoretical concept, no methods, no practices working in the everyday fabric of science, whereby a systematic ‘meta level of knowledge’ would be enabled such, that it would be accepted by all. As long as every individual scientific discipline — including physics — thinks that their own field is enough for all, we are lost.
In such a difficult situation is a phenomenon like wikipedia something like a ‘gift’ for all of us. Yes, wikipedia is not and cannot be the the ‘perfect solution’ for the ‘meta level knowledge’ problem (not yet), but compared to the activities of the individual disciplines it is a first step to overcome the all-sided isolation of knowledge today. As long as increasing parts of our societies beginn to believe that ‘science’ is wrong because they less and less understand what science is doing, science has missed its job in the society.
Wikipedia has one strong first argument for its mission: it is using ‘ordinary language’ to talk about all what is perhaps important in our world. Strictly speaking everything can be communicated in Wikipedia, everything is completely transparent, every citizen can in principal participate. This makes Wikipedia by itself to a ‘common science’. What cannot be expressed on this level does somehow not exist because the special languages, methods, models and results of an individual science are ‘trapped’ within the individual scientific disciplines.[2]
One can criticize wikipedia, this is OK, this is indeed intended and necessary, but delete it would be a great mistake; there exists no common science alternatives until now.
Assuming this position I heavily make use of Wikipedia articles to ‘calibrate’ my ‘philosophical’ ideas with some part of the ‘common science’ mainstream. Clearly, common science does not replace specialized scientific disciplines, but without a working ‘meta level knowledge’ the specialized scientific disciplines do not really exist, not in the mind of a democratic population, which as a whole has to judge in which direction a democratic society should go. Autocratic politicians and autocratic science behaves different; this is well known.
COMMENTS
[1] See an example of a critical reviewing of Wikipedia in: Jim Giles (2005), Internet encyclopaedias go head to head. Nature 438, 7070 (Dec. 2005), 900–901. DOI:https://doi.org/10.1038/438900a
[2] I exercised a dialogue with chatGPT4 (Aug 30 + Aug 31 2023) clarifying the narrow boundaries of chatGPT4 being ‘scientific’. The outcome was that chatGPT declared itself as basically not producing texts which satisfy scientific standards. Moreover chatGPT4 characterized Wikipedia at the same time as having all the basic ingredients of offering texts which are scientific.
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
[] Herbert Bruderer, Where is the Cradle of the Computer?, June 20, 2022, URL: https://cacm.acm.org/blogs/blog-cacm/262034-where-is-the-cradle-of-the-computer/fulltext (accessed: July 20, 2022)
[] UN. Secretary-General; World Commission on Environment and Development, 1987, Report of the World Commission on Environment and Development : note / by the Secretary-General., https://digitallibrary.un.org/record/139811 (accessed: July 20, 2022) (A more readable format: https://sustainabledevelopment.un.org/content/documents/5987our-common-future.pdf )
/* Comment: Gro Harlem Brundtland (Norway) has been the main coordinator of this document */
[] Chaudhuri, S.,et al.Neurosymbolic programming. Foundations and Trends in Programming Languages 7, 158-243 (2021).
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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.”
The main topic of the uffmm-blog was from the beginning the engineering of systems, enriched with important topics associated with systems engineering. These ideas emerged from a close cooperation between Louwrence Erasmus [1] and Gerd Doeben-Henisch [2] in the time before 2011. Later the cooperation continued but both authors were occupied by many duties thus the real shared writing vanished, but the close exchange of ideas continued.
One culminating point in 2010/ 2011 was the principal formalization of the concept of ‘the systems engineering process’ [3] as well as the concept of the ‘management of the systems engineering processes. [4] This enabled a more abstract thinking about systems engineering.
One of the authors, Gerd Doeben-Henisch, developed the idea of a formalized systems engineering process during the time 2011 – 2017 with some additions until 2020 further in the direction of a paradigm called “Distributed Actor-Actor Interactions (DAAI)”. [5] Besides the complete formalization this paradigm provided an explicit handling of the participating actors — humans as well as non-humans — with their interaction patterns. A part of this analysis was dedicated to communication between the actors using different kinds of languages (normal language, pictures (diagrams), and mathematical formulas). The document ended with an explicit proposal how to handle this engineering paradigm as a formal empirical theory (see especially chapter 8) emerging by a ‘process of interactions’.
Trying to apply this concept of an empirical theory of systems engineering processes to a working concept in the everyday world the author Gerd Doeben-Henisch was — beginning in the spring of 2018 — confronted with the idea of ‘city construction’, ‘communal planning’, as well as ‘more participation of citizens’ in the context of the processes of communal planning. Although it seemed from the beginning ‘intuitively clear’ that there exist strong structural similarities between a systems engineering process and all kinds of city planning with participating citizens some ‘hard problems’ appeared to ‘block’ a simple application of the general concept, e.g. (i) ‘normal citizens’ are usually not understood (and not accepted) as experts for engineering processes; (ii) systems engineering relies heavily on formalized languages; (iii) the support by programmable machines — usually — presupposes the usage of programming languages; (iv) computer programs as such have ‘no meaning’ which is related to the empirical everyday world of humans. (v) The concept of a scientific empirical theory in the context of digitization and an incrementing usage of computer programs is rather unclear.
To solve and ‘overcome’ the problems (i) to (v) needed some time. This uffmm blog includes many posts documenting the search for a solution. Finally the solution happened in the following consecutive steps (not planned, but by ‘heuristic search’): (a) a first solution cancelled the problem (ii). By re-analyzing the first phase of modern science, of modern logic and mathematics, it became clear that the early abandonment of ‘meaning’ from formal logic was only in one sense a great achievement; in another it ‘truncated’ the real world and the ‘human typical meaning’ completely from the formal space. The infinite richness of language meaning was damned to nothing. The question re-appeared why not continue with the usage of ‘normal language’. (b) A second solution made by some tests clear that the the requirement (iii) could be abandoned too: it is not necessary that a supporting computer understands anything, as long as humans are communicating in the way they are used to do it, by their normal languages. Following this line (c) not only problem (ii) and (iii) disappeared, but problem (iv) vanished automatically because there was no need any more that computer understand something. It was during the summer 2019 that the author Gerd Doeben-Henisch experimented with this new paradigm where human actors are using their normal language in building theories and a simple computer program supported these human communications without understanding anything. (d) To the extend that the problems (ii) – (iv) disappeared it became clear that human actors are the primary experts called ‘natural experts’. Thus problem (i) disappeared too.
It remained problem (v) what today should be called an ’empirical scientific theory’ used by human actors as a ‘tool for explaining the real world’. After re-examining many well known positions in the philosophy of science — mainly Karl Popper [6a-6e] –, including the modern awareness of the topic of ‘sustainability’ [7a-7c] as well as including the modern possibilities of using programmable machines as support tools, the concept of a ‘sustainable applied empirical theory (SAET)’ was elaborated in a research paper from March 2, 2022 for an upcoming conference September 2022. [8] Thus problem (v) seems actually be solved too. Since then an integration of the new software so far with the new concept of a SAET has been unified further to the concept of a “computer aided SAET” called ‘CSAET’.
In this new CSAET paradigm natural experts generate during their communications full SAETs even then, when they do not understand what a SEAT exactly is. Different SAETs can even be unified automatically if wanted.
Thus we all are now in a position where every human person can together with any other persons generate a complete sustainable applicable empirical theory to any aspect of the everyday world and he/she/x can test it ‘by pressing a button’ all the time: Are forecasts possible? Do these forecasts make sense? What reason caused which effect? Everything in plain language, no secrets any more.
System vs. Theory
System
Systems engineering is primarily focused on the engineering of ‘systems’. A ‘system’ is theoretically a ‘function’ which transfers a given situation into another situation. As a ‘real thing’ a system is instantiated in an assemblage of hardware, software and certain environmental settings. Such a physical assemblage manifests the ‘built in function’ as ‘observable behavior’ which can change certain properties of the environment and of itself. The observable behavior as such can only show fragments of the function at a certain place at a certain time; it is neither ‘true’ nor ‘false’. The only thing which could be stated is, that such an observable behavior ‘confirms to some degree’ to a given ‘specification’ or not. The specification as such is also neither ‘true’ nor ‘false’ because the specification is a ‘written document’ which specifies a ‘wanted behavior’ under certain conditions. As such is a wanted behavior also ‘not good’ nor ‘bad’.
Theory [T]
A theory is a ‘written document’ too. A theory describes some ‘structures’ of ‘objects’ and ‘relations’ between them, but it is usually combined with a ‘logic’, which allows the ‘derivation’ of ‘consequences’ following from the assumed structure. But this implies that the text of a theory consists of elements called ‘statements’ where a statement principally can be associated with a truth-value — in the simple case with — ‘true’ or ‘false’. These truth-values have no special meaning. They are purely abstract. The logic represents a set of ‘inference rules’ which are part of an ‘inference concept’ which allows the application of the inference rules to the given statements of the theory. Generally all statements of a theory are assumed to have the truth-value ‘true’. Applying the associated logic will generate all statements which are ‘true in the sense of the theory’. Statements which can be formed but cannot be inferred from the theory are then ‘undefined’. ‘Contradictions’ to ‘true statements’ are called ‘false’.
System and Theory
The document specifying a system can become part of a theory because a theory in general can include any kind of relations and functions. A ‘function’ is a special case of a relation. Thus one can build a ‘theory’ having a certain function as a genuine part of that theory. In that case a system specification can be part of a statement which as such can be classified as ‘true’, ‘false’ or ‘unspecified’ with regard to the assumed theory with the assumed logic.
Thus, if a theory can describe certain kinds of ‘states’ (‘situations’) and certain kinds of ‘changes’ caused by the application of a certain function, then one can use the inference concept of the associated logic to ‘prove’ whether a certain ‘follow-up’ situation s* can be derived from a given state s by applying the defined function. If one ‘repeats’ such derivations from state s to state s*, from state s* to state s** etc. then we have the case of a ‘theory driven simulation’.
Empirical Theory [ET]
A theory as such has no ’empirical meaning’. If one looks e.g. to the structures described by the group Bourbaki (cf. [9a,b]) they represent ‘stand alone definitions’ with regard to the empirical world. Nevertheless one can try to ‘relate’ the formal structures with certain kinds of empirical events and associate thereby some ’empirical meaning’ with these formal structures. But, as the lengthy history of philosophy of science shows very clearly (see e.g. [10]), such an interpretation mechanism between formal theories and empirical reality is far from being trivial. It works only under very strict conditions.
The main reason for this problem is grounded in the early decisions in the beginning of modern formal logic, to abandon ‘meaning’ completely from formal logic. If one looks back in the history of logic (cf. e.g. [11]), the handling of ‘meaning’ as known from natural language was always a big — and unsolved — problem of logic in all its variants. One of the best known criticisms against the concept of ‘stand alone’ formal systems are probably the ‘Philosophical Investigations’ of the late Ludwig Wittgenstein. [12a,b]
But instead that the purely formal approaches in logic and mathematics (and to some degree in the empirical sciences too) have been radically become revised, nothing happened.[13] Instead the rise of the ‘new programmable machine’, the ‘computer’, beginning after the world war II, offered a new paradigm where the ‘formal languages’ as ‘programming languages’ became associated with the ‘machine states’ of the computer. Thus a formal expression like ‘print’ could be interpreted as starting some ‘processes in the machine’ leading to a ‘printed document’. Thus the possible ‘machine states’ offered a space of a ‘new meaning’ in terms of machine states and their ‘observable effects’ in the real world. But this new kind of ‘machine-state meaning’ has nothing to do with the ‘language- and brain-mediated meaning’ of human actors.
What can be done to solve this fundamental problem of using formal systems ‘meaningful’?
Applied Empirical Theories [AET]
In the usual definitions of an ’empirical theory’one talks about the formal structures and the formal logic, which have to be ‘related in some reproducible way’ with so-called ’empirical events’. The human actors using the theory and ‘interpreting’ the theory are as such not included in the discussion. Doing this one wants to keep some kind of ‘invariance’ by excluding the human actor.
Human actor – internal states
This is a strange attitude. If one knows that the whole setting has no ‘meaning’ as such if not located in the human actor then the internal conditions of the human actors are of substantial importance although they are not directly ‘observable’.
If a human actor orders a cup of coffee in a coffee shop, is spending some money for this, and finally he is receiving a cup of coffee, then one could ‘describe’ this situation with its changing states without recurring explicitly onto the internal states of the buying actor. Nevertheless, the whole process of buying and getting a cup of coffee presupposes that all participating actors ‘understand’ the ‘meaning’ of the used language expressions. If this ‘internal understanding’ would not work (as in the case, if you do not understand the expressions of a foreign language) your ‘description of the observable process’ could be ‘true’ in one sense, but would be ‘incomplete’ in another. A reader of the description would not be able to understand why these processes ‘worked’ as they worked.
WORLD – BODY – BRAIN – VIRTUAL MODELS
In fact, one has to consider the internal processing of observable situations in connection with the used language expressions to become able to ‘understand’ why certain expressions will be used and why certain expressions in certain situations will have a certain effect. This results from the fact that every human actor has a body with a brain in the manner, that the body interacts between the body-external world and the body itself with the brain, which is using the body based signals in a unified fashion of neural signaling to built up in the real brain virtual representations of the body-external world associated with body-internal signals and even with brain-internal signals to something ‘new’: the brain composes internal structures/models of a possible world without a direct knowledge of the world outside of the brain. In this sense the ‘brain-composed world’ is a ‘real virtual’ world compared to the possible ‘real real world’ external to the brain and the body.
meaning function
Within the brain we have the ‘double structure’ of the ‘composed inside world’ and some language (primarily a natural language). It is the brain which maps the composed inside world with the internally represented language. This enables the ‘primary meaning function’ of a human actor, a ‘built-in’ function, which is ‘adaptable’ and which has to become ‘synchronized’ with the meaning function of other human actors, if they want to become able to ‘coordinate’ their brains by ‘communication’. [17]
Evolutionary context – COLLECTIVE SPACES
This built-in function of individual human brains, which can be connected by symbolic communication with all the other individual brains in the individual bodies, can expand the ‘individual real virtual world’ to a ‘collective real virtual world’ representing a ‘broader view’ of the external ‘real real world’. Seen in the context of the whole evolution of life on earth one can state that this is the fundamental power of biological life which enables a new evolutionary format to understand and to transform the planet earth and even more.
Pierre Lévy has described this incredible thing called ‘collective intelligence’ in a very impressive way in his book ‘Collective Inelligence’ already in 1994 (French) and 1997 (English).[14] In parts of my reviewing of this book [15a,b] I have underlined, that the time frame, which Lévy has selected (from the appearance of homo sapiens until the present) is to short to get a full understanding of the evolutionary role of homo sapiens. This evolutionary role of homo sapiens can only be understood adequately if one places the homo sapiens appearance in the global biological evolution; the appearance of homo sapiens is no ‘accident’, it is the result of a ‘logic’ implicitly given in the the whole observable process of growing complexity, grounded in a growing connectivity which again is grounded in a growing communication!
In one of the big centers of artificial intelligence (AI) research on this planet the researchers came 2021 to the conclusion, that all the big achievements in ai-research of the last years can not really be of help for human life on this planet if we do not really understand how human intelligence works.[16] And not only have we still a serious lack in understanding what individual human intelligence is, but we are completely in darkness in face of what ‘collective intelligence’ of human kind is. Collective intelligence enabled complex tools, machines, buildings, complete cities and even big societies, the computing machines, mathematics, to name only some aspects. But we do not really and seriously understand, how this works.
HUMANS AS GENUINE PART OF A THEORY
From this the author of this text derives the postulate, that the human actor as a population has to be included substantially in doing theory work if one wants to understand what happens if human actors are using ’empirical theories’.
Thus, an empirical theory can only be a real ‘applied’ theory if the fundamental dimension of the internal processing of meaning is a ‘genuine part’ of the description and the practice of an empirical theory. Excluding the dimension of the meaning located in the human actor makes an empirical theory a ‘non-object’: it is only a collection of symbols with no relationship to anything.
SUSTAINABLE AETs
With the inclusion of human actors in the concept of an empirical theory a theory is not any more some isolated something, which plays in an arbitrary way with ‘formal symbols’ only. With the inclusion of human actors as genuine parts of an empirical theory the whole biological life is included, a ‘wave of events’ coming to the present through about 3.5 billion (10^9) years. This inspires the question whether this historical dimension has something to tell about an applied empirical theory?
BEING SUSTAINABLE – A Non-uniform concept
Today, in the mainstream communication of the 2100 century, many ‘buzzwords’ are alive; one of these is the word ‘sustainable’. The different language games using this expression do not show a ‘uniform’ usage. The main target of something being ‘sustainable’ are different kinds of ‘systems’ operating in time: individual persons, technical systems, institutions, populations, societal subsystems like the system of ‘laws’, the system of ‘political institutions’ and the like.
Evolution
Because all the mentioned individual systems are part of the larger phenomenon of the biological life as a whole, interacting with the planet earth, interacting with the whole solar systems, or even interacting with at least parts of the universe, it could make sense to locate the ‘meaning’ of the expression ‘sustainable’ into this larger context of life in the universe; an exciting perspective.
A possible ontology
Extending the scope of a view into many directions induces the need for some ‘structuring’ of the plethora of details in some way. In philosophy well known concepts for this are ‘categories’ and ‘ontologies’. While categories are understood as located in the structure of our subjective knowledge, determining ‘how we can see the world’, (see e.g. [18]) ontologies are assumed to be ‘real structures’ corresponding to these categories in ‘some’ way. Different philosophers handled these topics very differently.
In this text a possible ‘ontology’ could be assumed as follows: A text in the format of a CSNAE-theory implicitly is assuming space, time, as well as identifiable systems in space and time. Thus the ‘space’ can be structured according to empirical matters like ‘external to the earth’, ‘on earth’ and on earth structured according to ‘continents’, ‘nations’ and finer and finer regions. The ‘time’ can be structured according to the time ‘before the present’ (‘before the now’), the time of the ‘present’, and the time of ‘computable possible future states’. ‘Identifiable systems’ have a material structure showing some dynamics in time, are always interacting with their environment, and are possessing minimal internal structures determining the observable behavior. A ‘system’ can be part of another system thereby allowing complex hierarchies and networks of systems of different kinds. [19]
united nations and sustainability
Besides some experts which clearly see the overall perspective of life the today mainstream prefers a more narrow scope how it is discussed and documented by the united nations conferences since 1992 (Agenda 21). [7b,7bb] Besides many organizational issues the 1992 Rio Conference started with topics like ‘Climate Change’, ‘Biological Diversity’ , as well as “Principles for a global consensus on the management, conservation and sustainable development of all types of forests.”
17 development goals
Some conferences later, 2015, the Agenda 2030, the overall goal of sustainable development has been substantiated into 17 development goals.[7cc]
No coherent framework, no theory
Reading these different goals is interesting, even inspiring, but it is difficult to find a clear concept of ‘sustainable development’ which as a framework puts all these goals into one dynamic coherent process.
Under the question “What is sustainable development?” one finds on the web-page three statements which which are intended to give a satisfying answer:
Sustainable development has been defined as development that meets the needs of the present without compromising the ability of future generations to meet their own needs.
Sustainable development calls for concerted efforts towards building an inclusive, sustainable and resilient future for people and planet.
For sustainable development to be achieved, it is crucial to harmonize three core elements: economic growth, social inclusion and environmental protection. These elements are interconnected and all are crucial for the well-being of individuals and societies.
In (1) ‘time’ is assumed as an underlying dimension enabling concepts like ‘present’ and ‘future’ and humankind is partitioned in ‘generations’ each with generation-typical ‘needs’.
In (2) ‘concerted efforts’ are required for a future, which shall have the properties of being ‘inclusive’, ‘sustainable’ as well as ‘resilient’. (Here ‘sustainable’ is explained by ‘sustainable’ (which is a circular definition) and extended by ‘inclusion’ and ‘resilient’ which is not explained.)
In (3) ‘core elements’ are mentioned which are ‘interconnected’ and which are classified as being ‘crucial’ for ‘individuals’ and ‘societies’. These core elements shall be “economic growth, social inclusion and environmental protection”.
As interesting as these points may be, but they provide neither a ‘definition’ nor do they give any kind of a conclusive answer.
Brundtland report
In search for more ‘consistency’ one can trace the concept of ‘sustainable development’ back to the Brundtland report from 1987.[7a, 7aa] This report was driven by the insight that humankind is more and more faced with problems which are not restricted to only one nation, but to many if not to all. Therefore an answer has to be organized by a cooperation of as most as possible nations together. This answer has to be located in the dimension of time starting in the now, the present, and foreseeing somehow the tomorrow, the future. While this clearly calls for the necessary knowledge, the knowledge can only enable the necessary ‘effects’ if the knowledge is distributed in all those institutions which are necessary for ‘real actions’. And somehow this is touching all kinds of systems making up our daily world.
One can synthesize all the needed aspects into the following main requirements:
One needs knowledge in a format, which can ‘bridge’ the present and the future in a most ‘reliable’ way;
One needs the knowledge of as many as possible citizens in all their varieties (every citizen has to be declared as a ‘natural expert’).
No part of the human society is excluded from the endeavor to make a society ‘future friendly’.
Human society is understood as a genuine part of the whole biosphere on the planet earth as part of the whole universe. Humankind therefore acts in responsibility for the whole live in the universe.
Life as irritating factor
In the main stream one can observe a somehow puzzling tendency to distinguish between the biological life and humankind. In one sense it is ‘somehow’ accepted that the homo sapiens is part of the biological life, in another — mostly vaguely — sense homo sapiens/ human kind/ we are understood as ‘different’ to biological life. When the classical Greek philosophy separated the ‘pure matter’ from the ‘animated matter’ by attributing to the ‘animated matter’ properties like ‘mind’ coming from some eternal mind, one can this somehow ‘understand’ because in that time there was no knowledge available about the internal structures on pure matter and of animated matters. But today we can; we can explain alle observable properties of the ‘animated’ biological phenomena by the underlying structures and processes. With this knowledge we can explain ‘mind’ with much more powerful concepts than a Greek philosopher. Indeed we could completely rewrite classical Greek philosophical texts in the light of the new knowledge. And this ‘rewriting’ would not stop there. The ‘tacit assumptions’ about the ‘somehow difference’ of humankind to biological life in general can be rewritten in a way which makes humankind a genuine part of biological life. But this ‘genuinely being biological’ does not exclude that humankind has a very special and important role as part of the biological life!
Humankind identity: is humankind the global error?
In opposite to those, which ‘somehow’ are making a difference between biological life and humankind, there are those, which see humankind as a complete part of biological life but those ‘full biological humans’ fraction can not see any special properties or even some special ‘mission’ of humankind within this phenomenon of biological life. This attitude makes humankind to a branch in the biological evolution which will vanish from the planet because it behaves in a self-destroying manner.
Humankind as a ‘tool of life in the universe’?
As the history of mankind in general and the history of knowledge during the different epochs shows the way we as human actors are looking to reality is not absolutely ‘fixed’. One of many thousands examples of the variations in ‘looking to things’ is the history of the interpretation of the book called ‘bible’. Not only shows the development of this text during centuries varying views, but also the times after the main fixations which texts should be part of the bible and which not inspired many hundreds ‘interpretations’ which are often in contradiction. In a certain sense there is not clear absolut ‘fix point’ to serve as a ‘point of reference’ for all questions. In natural sciences we have a slightly better situation because the ‘assumptions’ of the used methods are transparent and clear (ideal case), but which kinds of assumptions are made is free and open. [20]
From this follows that a tendency to ‘distinguish’ human kind from biological life or the tendency to ‘include’ human kind to biological life classified as ‘doomed to vanish by self destruction’ are views based on certain assumptions which as such are ‘freely assumed’. There is no necessity to assume the one or the other view. Assumptions are ‘tools for a possible understanding’ which is following such assumptions.
Thus, to ‘describe’ what ‘biological life is’ in some text has to be distinguished clearly from the phenomenon of ‘biological life’ as such! If biological life is a real thing then biological life is ‘given’ to us as the general condition of our ‘being here and there’, and whatever we will explain, these explanations are always ‘second hand’: whatever we will explain, we are reacting to something which we already are. It is not yet clear whether we are able to explain ourselves sufficiently and completely. The undecidability results of Goedel do the problem only partially address. [21] The problem starts already with the assumptions we are making, and these are free. We as human actors can ‘neglect’ to know even if there is perhaps something to know.
In this context of ‘making assumptions guided by free will’ one can try to have a look to some special role of humankind as part of the biological life within the universe or not.
A short look to the history of biological life can reveal, that there exists many observable phenomena which can be interpreted as a continuous increase in complexity of biological structures. Those structures which show up as very important for the increase of complexity are (i) centered around internal structures to collect and to develop cognitive representations of the outer world of the system and the system itself; furthermore (ii) important are those structures which enable a communication not only ‘inside the system itself’ but ‘between different brains’ as well. Inter-brain communication enabled the cooperation of many, many systems which otherwise would be ‘locked-in’ in themselves. These inter-brain communications enable (iii) some new techniques to ‘store’ communications and thereby helped to bridge between different points of time.
To describe all these important phenomena in detail would be a larger project, perhaps entitled best under the lable of ‘collective intelligence’ in the spirit of Lévy, but — perhaps — with some more advanced methods.
Seen from he point of view of the whole of biological life in the universe humankind can be associated with the special role that by humankind the biological life can ‘recognize’ the universe as an environment for biological life and it can recognize what can/ should be done, that biological life can survive in the universe. The existence of the planet earth is possibly not the ‘endpoint’ of the history of life in the universe but only the beginning.
[3] L. D. Erasmus and G. Doeben-Henisch, A Theory of the System Engineering Process in 9th IEEE AFRICON Conference in Africa, Sept. 12-15, 2011 (This paper has won a paper award)
[4] L. D. Erasmus and G. Doeben-Henisch, A Theory of the System Engineering Management Processes in ISEM 2011 International Conference, Sept. 2011
[5] See the last version from 2020: https://www.uffmm.org/wp-content/uploads/2019/05/aaicourse-15-06-07.pdf
[6a] Karl Popper and theory, see e.g.: https://www.uffmm.org/2022/03/12/popper-and-empirical-theory-a-conceptual-experiment/
[6b] Karl Popper, „A World of Propensities“,(1988) „Towards an Evolutionary Theory of Knowledge“, (1989) in: Karl Popper, „A World of Propensities“, Thoemmes Press, Bristol, (1990, repr. 1995)
[6c] Karl Popper, „All Life is Problem Solving“, originally a lecture in German 1991, first published in the book „Alles Leben ist Problemlösen“ (1994), then „All Life is Problem Solving“, 1999, Routledge, Taylor & Francis Group, London – New York
[6d] Karl R.Popper, Conjectural Knowledge: My Solution of the Problem of Induction, in: [2], pp.1-31
[6e] Karl R.Popper, Objective Knowledge. An Evolutionary Approach, Oxford University Press, London, 1972 (reprint with corrections 1973)
[6f] 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))
[7aa] Brundtland report, in Wikipedia (EN): https://en.wikipedia.org/wiki/Brundtland_Commission, accessed: 10/04/2022
[7b] Report of the United Nations Conference on Environment and Development, Vol. 1, Rio de Janeiro, 3-14 June 1992, A/CONF.151/26/Rev.l, United Nations publication, Sales No. E.93.1.8, ISBN92-l-100498-5, https://documents-dds-ny.un.org/doc/UNDOC/GEN/N92/836/55/PDF/N9283655.pdf, accessed: 29/05/2022
[7bb] Report of the United Nations Conference on Environment and Development, Volume 2, Rio de Janeiro, 3-14 June 1992, Proceedings of the Conference, A_CONF-151_26_Rev-1(Vol-II)-EN, https://digitallibrary.un.org/record/168679/files/A_CONF-151_26_Rev-1%28Vol-II%29-EN.pdf, accessed: 29/05/2022
[8] This research paper is still in the review process, therefore the content can not yet be discussed here. The authors of this research paper have been Gerd Doeben-Henisch (Frankfurt University of Applied Sciences), Gerrit Hornung and Matthias Söllner (both University Kassel), Athene Sorokowski and Philipp Westermeier (both Goethe University Frankfurt).
[17] Inside Structures in human actors: A huge amount of data and models can be found in the scientific disciplines of biology, (neuro-)psychology, (neuro-)linguistics, and brain research. All the known data are in agreement with this very rough and abstract modeling communicated here.
[18] Immanuel Kant, Critic of pure reason, 1781, 2nd rev. ed. 1787, see: https://en.wikipedia.org/wiki/Critique_of_Pure_Reason
[19] Ontology: This outline of a CSAET-ontology is not fixed. It can be arranged in many different ways. The only criterion is “which kind of arrangement explains more”, which again is not a fixed criterion.
[20] The assumptions which Newton did use and those which Einstein did use have been different.
[21] Kurt Goedel. Über formal unentscheidbare Sätze der Principia Mathematica und verwandter Systeme, i. Monatshefte für Mathematik und Physik, 38:173–98, 1931.
The following text has not the format of a book but the format of a blog. This seems to be trivial at a first glance. But it isn’t.
A book represents its subject as a ‘closed shop‘: everything to be said is there; things are fixed; nothing new can happen. You ‘have it’.
The real world instead is not static, is not closed, is in a steady process of ,multiple changes all the time. Not only an individual alone can change every time, all things can change and are changing. There is nowhere a ‘fixed point’. Even the ‘hard things’ of the everyday world are dynamic substrates which are changing constantly.
Thus a written book equals mostly a ‘can’ which contains everything, not changing, stored as something from the past.
A blog is completely different. While the authors are part of a dynamic reality and they themselves are constantly changing — with ‘learning’ as a subset of these changes — they are in the strange situation that they want to report on multiple processes which have no fixed ‘endpoint’: the actual time-spot, the now, is the actual endpoint of the process so far, but because the process as such does not stop, this ‘relative endpoint called ‘now” will turn into some ‘past’ from the next ‘now’.
Thus reporting about the real world will ever be an ongoing story which reveals some possible ‘hidden structure’ only during the course of time itself.
The self-image of the uffmm.org blog is exactly like this: a constant self-reporting of an individual as a process being part of uncountable many processes which are more or less interacting. Generating models about these processes is necessary but will never be more than a simplified sketch of some dynamic complexity which as such can never be modeled completely.
Thus the ‘incompleteness‘ of a blog is the only possible ‘truth’ in this dynamic world.
To make some ‘sense’ out of it therefor belongs to the responsibility not only of the author(s) alone but to the reader as well. Truth lives always ‘in the middle of everything’…
Integrating Engineering and the Human Factor (info@uffmm.org) eJournal uffmm.org ISSN 2567-6458
