Category Archives: Network Society

What is Information?

One of the most important ideas today is the idea that the world is made up of information, not things. Information is a relation and a process and not a substance, a thing, an individual entity, or a bounded individual. A world of information is a world of relations and not of things.

This idea was expressed already a hundred years ago by the philosopher Ludwig Wittgenstein when he said, “The world is the totality of facts, and not things” (Tractatus logico philosophicus 1922). Why not things? Where are the things, if not in the world? What is the world made of, if not things? According to Wittgenstein, things are in language, that is, in all that can be said about the world. These are what Wittgenstein called “facts.” For example, a fact is that the ball is red, or the tree is in the garden. These are facts, if they are true, because they can be expressed in language. This means that what cannot be expressed in language is not in the world. “It” is nothing at all. Therefore, Wittgenstein can also say: “The limits of my language mean the limits of my world” (Tractatus…).

At about the same time Martin Heidegger formulated similar ideas. He said that humans (Heidegger speaks of “Dasein”) do not face a world of things, as if things are simply there and humans, if they want, can establish a relationship with things or not. Quite the contrary, humans are always together with things in a world of meaning. This is what Heidegger calls “being-in-the-world”, and he claims that humans exists as “being-in-the-world.”

It is not the case that man ‘is’ and then has, in addition to this, a relationship toward the “World”, which he occasionally takes up. Dasein is never ‘at first’ an entity which is, so to speak, free from Being-in, but which sometimes has the inclination to take up a ‘relationship’ towards the world. Taking up relationships towards the world is possible only because Dasein, as Being-in-the-world, is as it is. This state of Being does not arise just because some entity is present-at-hand outside of Dasein and meets up with it. Such an entity can ‘meet up with’ Dasein only in so far as it can, of its own accord, show itself within a world. (Being and Time, 1927 §12)

But how can things “show themselves of their own accord within a world?” They do this, as Wittgenstein thought, by being able to be expressed in language. But how is it possible that things “of their own accord” can be expressed in language? In order to answer this question, let us recall what Heidegger said about Aristotle’s well-known definition of humans as that animal which has language – zoon logon echon. Heidegger claimed that this definition of human being can be understood in two ways. On the one hand, it can mean, as has mostly been thought throughout the history of philosophy, that humans are distinguished among all living creatures because they have reason. Among all animals there is one animal that can also speak, respectively think. This is the human being. This interpretation is understandable because the Greek word echon means “to have, to be available.” According to Heidegger, it can also mean that it is language that “has” humans, or rather, that it is language (logos) that uses humans such that all things can show themselves in and through language. Humans do not use language; the logos uses humans. As Wittgenstein said, the limits of my language mean the limits of my world. We live in a world of meaning, a world constructed by logos, with our help of course.

Today we no longer speak of logos, reason, thought, rationality, or even language when we refer to the way things and ourselves exist in the world but of information. Why information? Why has the concept of information taken the time-honored place of reason and language and worked its way up to become the main concept of understanding the world and human existence? Why does everyone talk about information today? Can we imagine that Aristotle could have said: Humans are the animals that have information? If he would have said something like this, it would today be clear that only the second interpretation is valid. It is information that has us and not the other way around. Information is everywhere and not only something that humans have.

In physics, one no longer speaks only about matter, energy, fields and particles, but about information. Physicist Anton Zeilinger, who won the 2022 Noble Prize, said in words reminiscent of Wittgenstein, “I am firmly convinced that information is the fundamental concept of our world, … It determines what can be said, but also what can become reality.” According to Zeilinger, we must get used to the idea that reality is not purely material, but also contains an immaterial “spiritual” component. 

In biology, we hear similar things. Michael Levin, one of the most important biologists today says that he no longer needs the term “life”.  Instead, he prefers to speak of “cognition.” All living things, from the simplest single-celled organisms to humans, are distinguished above all by the fact that they use information to react to environmental conditions in such a way that they can continue to live. This is called “adaptation” or “viability” in evolutionary theory. Living things are thus “intelligent”, and not only the central nervous system or even the human brain is intelligent, but intelligence can be found everywhere living things solve problems, and that is what they do as long as they live. Life in all forms and at all scales is nothing else than information processing.

Finally, thanks to the invention of the computer, at the level of human society we speak of an information society. People in all their activities are characterized by the processing of information. Not only that, but an “artificial” intelligence” is emerging that promises in the future to far exceed human information processing abilities – formerly known as “reason.” Information processing is independently evolving beyond humans and is increasingly determining human existence. This is reminiscent of Heidegger’s interpretation of Aristotle; it is not humans who possess language, but language, or information, which has humans, and everything else, in its grip.

What exactly information is remains ambiguous and different in each field, whether in physics, biology, or philosophy and sociology. Is there a common denominator that fits all forms of information? Can we define information in general and for all cases? It is striking that wherever information is spoken of it is understood as a difference between at least two states. Whether we are talking about quantum states, for example, “upspin/downspin,” or biological information, for example, whether something is “edible/non-edible,” or electronic bits that are either 1/0, it is always about a relation between two states that can be measured as a relation. Information is, it seems, at the most general level, a relation and not a thing. From the perspective of philosophy, Bruno Latour has given a name to this peculiar entity that is information. He speaks of “irreduction.” What does “irreduction” mean? Latour writes: “Nothing is, by itself, either reducible or irreducible to anything else.” (Pasteurization of France, 158). What does this cryptic statement means? When something is “reduced” to something else, this means that there are no longer two, but only one. The difference between the two disappears and thus there is no longer a relation. If nothing can be subject to reduction, then everything that is exists as a relation and not as a thing. What does this have to do with information? Information is this relation, without which nothing can be. Relations, it must be emphasized, are not things. They are something else that cannot be understood as a thing.

Because information is relational, it exists in networks. Networks are not things either. Otherwise, we would simply have collective things in addition to individual things, much as in sociology we speak of organizations in addition to individuals. Networks are neither organizations nor individuals. They are neither things nor compositions of things. Networks are processes of making relations, associations, connections. One should speak of networks as a verb – networking – and not of network as a noun. Networks are not bounded systems which operate to maintain their structures. If, as Michael Levin claims, life consists of cognition, then living things are not things, but dynamic processes of adapting, changing, and networking. Humans, like everything else in the world, are made up of information processes which we experience as consciousness. We exist as networks/networking i.e., we are ongoing, historical processes of networking. It is these processes that we call society. There is no fundamental difference between individual and society, but only a difference of scale of information processing or networking. In the information world, systems, i.e., limited entities whether individuals or organizations, become networks. In the global network society, which is the world we are now entering, we will network with many other beings that also process information, be it humans, robots, cyborgs, AIs, artificial beings, etc., and collectively shape our lives. Living in an information world means networking, thinking and acting in networks. This is the challenge of our time.


Q & A on AI

Q: Where does AI begin and where does it end?

A: AI will probably have neither beginning nor end, but will be seamlessly integrated into our daily lives, which could mean that in the future we will no longer speak of “artificial” intelligence at all, but only of “smart” or “dumb”. Either we and everything around us, for example, our houses, our cars, our cities etc. are smart or dumb.

Q: How does AI relate to philosophy?

A: At the moment, philosophy is concerned with AI insofar as it can be compared to human intelligence or consciousness. But it is to be suspected that a useful philosophical theory of AI would have to be a philosophy of information. Being “smart” is about the optimal use of information. Information and not cognition, consciousness, or mind is the correct fundamental concept for a philosophy of AI.

Q: When is AI obligatory and when is it voluntary?

A: Obligation and freedom are terms that refer to individual human beings and their position in society. According to modern Western beliefs, one has duties towards society and towards oneself one is free and independent. AI, in this frame of thinking, is seen as something in society that is a threat to freedom for the individual. But as for all social conditions of human existence, i.e., as for all technologies, one must ask whether one can be truly independent and autonomous. After all, when is electricity, driving a car, making a phone call, using a refrigerator, etc. voluntary or mandatory? If technology is society, and an individual outside of society and completely independent of all technology does not exist, then the whole discussion about freedom is of little use. Am I unfree if the self-driving car decides whether I turn right or left? Am I free if I can decide whether I want to stay dumb instead of becoming smart?

Q: What can the status quo be maintained during permanent development?

A: This question is answered everywhere with the term “sustainability”. When it is said that a business, a technology, a school, or a policy should be sustainable, the aim is to maintain a balance under changing conditions. But it is doubtful whether real development can take place within the program of sustainability. Whatever I define as sustainable at the moment, e.g., the stock of certain trees in a forest, can be destructive and harmful under other conditions, e.g., climate change. Sustainability prioritizes stability and opposes change. To value stability in an uncertain, complex, and rapidly changing world is misguided and doomed to failure. We will have to replaced sustainability as a value with a different value. The best candidate could be something like flexibility, i.e., because we cannot or do not want to keep given conditions stable, we will have to make everything optimally changeable.

Q: Who is mainly responsible for AI development in a household?

A: In complex socio-technical systems, all stakeholders bear responsibility simultaneously and equally. Whether this is a household or a nation, it is the stakeholders, both humans and machines, who contribute to the operations of the network and consequently share responsibility for the network. This question is ethically interesting, since in traditional ethics one must always find a “culprit” when something goes wrong. Since ethics, morals, and the law are only called upon the scene and can only intervene when someone does something voluntarily and knowingly that is immoral or illegal, there needs to be a perpetrator. Without a perpetrator, no one can be held ethically or legally accountable. In complex socio-technical systems, e.g., an automated traffic system with many different actors, there is no perpetrator. For this reason, everyone must take responsibility. Of course, there can and must be role distinctions and specializations, but the principle is that the network is the actor and not any actors in the network. Actors, both human and non-human, can only “do” things within the network and as a network.  

Q: Who is primarily responsible for AI use in a household?

A: Same as above

Q: Who is mainly responsible for AI development in a company?

A: Same as above

Q: Who is primarily responsible for AI use in an enterprise?

A: Same as above

Q: Who is primarily responsible for AI development in a community/city?

A: Same as above

Q: Who is primarily responsible for AI use in a community/city?

A: Same as above

Q: Who is primarily responsible for AI development in a country?

A: Same as above

Q: Who is primarily responsible for AI use in a country?

A: Same as above

Q: Can there even be a global regulation on AI?

A: All the questions above reflect our traditional hierarchies and levels of regulation, from household to nation or even the world. What is interesting about socio-technical networks is that they do not follow this hierarchy. They are simultaneously local and global. An AI in a household, for example Alexa, is globally connected and operates because of this global connectivity. If we are going to live in a global network society in the future, then new forms of regulation need to be developed. These new forms of regulation must be able to operate as governance (bottom up and distributed) rather than government, i.e., hierarchical. To develop and implement these new forms of governance is a political task but it is not only political. It is also ethical. For as long as we are guided by values in our laws and rules politics ultimately rest upon what people in a society value. The new values that guide the regulation of a global network society need to be discovered and brought to bear on all the above questions. This is a fitting task for a digital ethics.

Q: Who would develop these regulations?

A: Here again, only all stakeholders in a network can be responsible for setting up regulatory mechanisms and also for control. One could imagine that a governance framework was developed bottom up and that in addition to internal controlling also an external audit would monitor the compliance with the rules. This could be the function of politics in the global network society. There will be no global government, but indeed global governance. The role of government would be to audit the self-organizing governance frameworks of the networks of which society consists.

Q: Should there be an AI driver’s license in the future?

A: The idea of a driver’s license for AI users, like for a car or a computer, assumes that we control the AIs. But what if it is the AIs that are driving us? Would they perhaps have to have a kind of driver’s license certifying their competence for steering humans?

Q: What would the conditions be for that?

A: Whether AIs get a human or social driver’s license that certifies them as socially competent would have to be based on a competence profile of AIs as actors in certain networks. The network constructs the actors, and at the same time is constructed by the actors who integrate into the network. Each network would need to develop the AIs it needs, but also be open to being conditioned as a network by those AIs. This ongoing process is to be understood and realized as governance in the sense described above.

Q: How will society from young to old be sensitized and educated?

A: At the moment, there is much discussion of either “critical thinking” or “media literacy” in this context. Both terms are insufficient and misleading. When critical thinking is mentioned, it is unclear what criticism means. For the most part, it means that one is of the same opinion as those who call for critical thinking. Moreover, it is unclear what is meant by thinking. Critique is everywhere. Everything and everyone is constantly being criticized. But where is the thinking? Again, thinking mostly means thinking like those who say what one should criticize. Since this is different in each case and everyone has their own agenda, the term remains empty and ambiguous. The same is true of the term media literacy. In general, media literacy means knowing how the media select, process and present information, and it also means being aware that this is done not according to criteria of truth-seeking, but criteria of the media business. Knowing this, however, is not a recipe for effectively distinguishing truth from fake news. For that, one needs to know a lot more about how to research for information and how to judge its reliability.

Q: Where do the necessary resources for this come from?

A: There is a tendency to defer the task of education and training to the education system. Schools are supposed to ensure that children grow up with media literacy and the ability to think critically. But how this “training task” is understood and implemented is unclear. Since the school system has largely shown itself to be resistant to criticism in terms of pedagogy and curriculum, and since it still sees certification rather than education as its primary task, the traditional education system cannot be expected to be capable of doing the job that is needed. As in other areas of society, schools will have to transform themselves into networks and learn to deal with information much more flexibly than is the case today. Perhaps schools in their current form will no longer be needed.

Q: Will there ever be effective privacy online?

A: It could also be asked whether there is or could be effective privacy offline. In general, it depends on what one means by privacy. At the moment, privacy or data protection is a code word for the autonomous, rational subject of Western democracy, or in short, the free, sovereign individual. It looks like the digital transformation and the global network society are challenging this assumption. Before talking about privacy, we must therefore answer the answer the question, what is the human being. If the human being is not what Western individualism claims, then privacy can be understood differently. There is much work to be done in this area, as it seems that the humanistic and individualistic ideology of Western industrial society has chosen to fight its last stand against the encroaching global network society over the question of privacy.


Holding Things Together

When it comes to order as opposed to chaos, that is, of holding things together, physicists speak of four fundamental forces of the universe. There is gravity, electromagnetic force, and the so-called “strong” and “weak” forces that hold particles together and govern their relations. These four forces supposedly explain everything. But what about life? And what about meaning? Do not living organisms have their own “life” force that holds the cells and parts of cells together and regulates their interactions? As for meaning, what holds the words a language together so that they make sentences? Why can’t just any word be combined with just any other? There must be something that makes meaning happen. Can these forces not also be considered “fundamental” forces of the universe? This question is important, at least if we want to avoid “physicalism,” that is, reducing everything to matter.

Let us call the force that turns inanimate matter into living organisms “negentropy” and let us call the force that holds words together to make meaningful sentences and thoughts “power.” In 1944 the Nobel Prize winning physicist Erwin Schrödinger published a book entitled What is Life?. The question arises because living systems do not follow the Second Law of Thermodynamics, that is, the law of entropy. In living systems, order increases rather than decreases. This goes against the law of entropy. Life, therefore, is a fundamentally different form of order than matter. Life is a so-called “emergent” phenomenon which means that we don’t know where it comes from or how it comes into being, but we know it did and that it is very different from the purely physical organization of matter which the law of entropy regulates. In distinction to merely physical organization, which does not negate entropy, life seems to do this. Negentropy means the negation of entropy. Entropy is the tendency of energy to dissipate to equilibrium, that is, the equal probability of all states. For Schrödinger, this was a paradox. How can entropy be negated, and systems move from being less organized to being more organized? Another Nobel Prize winner, Ilya Prigogine, spoke of “dissipative systems” which run energy through their structures much like water running through a mill or food going through the metabolism of organisms. Such systems use entropy to negate entropy.

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Tesla is a Philosophical Problem

Of course, this is not about Tesla, but about intelligent-mobile- autonomous-systems (IMAS) – also known as robots. The philosophical problem comes from the fact that the robot, in this case the automobile, says “Leave the driving to us” which was an advertising slogan for Greyhound Bus. If the robot takes over the driving, and this means the decision making, then who is responsible for accidents? This was not a problem for Greyhound since the driver and in some cases the company were held liable for their mistakes. But what about the AIs? Indeed, the question of accountability, responsibility, and liability for robots and other AIs has become a major topic in digital ethics and everybody is scrambling to establish guidelines and norms for “good,” “trustworthy,” and “accountable” AI. It is at once interesting and unsettling that the ethical norms and values that the AI moralists inevitably fall back on arise from a society and a culture that knew nothing of self-driving cars or of artificial intelligence. This was a society and culture that categorized the world into stones, plants, animals, and human beings, whereby the latter alone were considered active subjects who could and should be held responsible for what they do. All the rest were mere objects, or as the law puts it, things (res). But what about the Tesla? Is it a subject or an object, a potentially responsible social actor or a mere thing? Whenever we go looking for who did it, we automatically assume some human being is the perpetrator and if we find them, we can bring them to justice. Who do we look for when the robot “commits” a crime? How do you bring an algorithm to justice? And if we decide that the robot is to be held responsible, aren’t we letting the human creators all to easily off the hook? These were the questions that the EU Parliament recently had to deal with when they discussed giving robots a special status as “electronic personalities” with much the same rights as corporations who have a “legal personality.”

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Data – Information – Knowledge

Who doesn’t know the classic distinction between data, information, and knowledge? And who hasn’t seen at least one version of the famous pyramid with data on the bottom, information making up the next level and knowledge making up the layer above that with the peak consisting of wisdom? There are several assumptions and implication of this model of data, information, and knowledge: First, it is assumed that they are qualitatively and quantitively different. Data, for example, is different from information and there is more data than information just as there is more information than knowledge with wisdom being the rarest sort of knowledge. Second, it is assumed that they are hierarchically interdependent, that is, you cannot have information without data or knowledge without information, but you could have data without information and information without knowledge. Third, the hierarchy implies a value judgement, that is, data is not as valuable as information and information is not as valuable as knowledge, and of course, wisdom is the most valuable of all. Finally, the hierarchy also implies a kind of temporal or ontological priority. Since information depends on data, data must come first, and since knowledge depends on information, information comes before knowledge, at least temporally. This means that first we have data, then we somehow construct information out of data, and then we can go on to construct knowledge out of information. Data is something like the raw material out of which is constructed information and information is the raw material out of which knowledge is constructed. There is nothing in the model that implies how this construction process works. The model itself does not tell us where data comes from or how exactly information is constructed out of data or knowledge out of information. In order to answer these questions, we are left to speculation.

There is of course a kind of consensus among interpreters that there are also different kinds of construction. In short, these may be termed “transcription,” “cognition,” and “praxis.” Data are said to be constructed by means of some kind of transcription, that is, something is preserved, fixed in some material form, in some medium, whether it be sound, text, or pictures. Today, data is above all transcribed into bits and bytes, that is, into digital media, which, as the dominant media in today’s world, also determine what is usually meant by the term “data.” Data are just bits and bytes, 1s and 0s, electronically fixed upon some memory medium. Information is usually thought to be constructed out of data. When the otherwise meaningless bits and bytes are combined into signs in a language and are given meaning, then data becomes information. This is above all a cognitive process. Somebody makes “sense” of the images or marks on paper or the bits and bytes on the chip via a cognitive process of “reading.” This is information. But it is not yet knowledge. Knowledge is what information becomes when it used practically to solve some specific problem. The practical use of information in problem-solving activities is called “praxis.” It is in praxis that mere information, for example, mere theory or mere textbook knowledge, becomes situated in a particular context in the real world. It is through praxis that we know what information is good for, what it can do, how it can be used in complex situations. Knowledge is knowing by doing. This separates the apprentice from the master, the inexperienced from the experienced. It is the experienced master who alone can be said to possess knowledge.

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