Pascal Sieber conducted this conversation with Marc Leuzinger ahead of the CNO Panel. A compact summary of the central theses can be found in the short version.

From natural science to the Digital Society

Pascal Sieber: Marc, you studied mathematics and biochemistry, with a focus on complex systems. What gripped you about that field back then – and how did you get from there into the digital economy?

Marc Leuzinger: The fascination began when, as a teenager, I read the novel Jurassic Park, or rather its sequel The Lost World. In it, Michael Crichton took up the then still young field of complexity research and, through the figure of the chaos researcher Ian Malcolm, who does research at the Santa Fe Institute, made a new way of seeing the world tangible: that highly complex behaviour can arise from simple rules and that complex systems can only be predicted or controlled to a limited extent. Some years later, driven by this idea, I actually began studying biology, but did not find what I was looking for. I then turned to the Santa Fe Institute, and the researchers there advised me to study mathematics and biochemistry to enter this field, so I changed my course of study. But here, too, the connection to what I wanted to do was slight. Around the same time, Stephen Wolfram published «A New Kind of Science». There I finally found what I had been searching for. As my professors showed little openness to this new field, I dropped out and founded a startup in the health sector that pursued this science. At the time, however, we lacked the possibility of very broad measurement, as would be possible with today's technologies. After a few years, we therefore had to give up. Around that time, social media was just emerging, and I founded SMLY, one of the first social-media agencies in Switzerland.

Pascal Sieber: In 2010, social media was uncharted territory – Facebook campaigns, fan gates, competitions. When did it first become clear to you that this was not just about new channels, but about a fundamentally different way in which society functions?

Marc Leuzinger: At the very beginning, the fascination with what was suddenly technically possible dominated. What we made were above all interactive campaigns, personalised through the integration of user data or images. The next step was building our own communities. At the centre stood dialogue, working with people, but also the fear of losing control and of «shitstorms», as they were called back then. That was the first time it was palpable that something fundamental was changing here.

From campaign to theory

Pascal Sieber: A few years ago, SMLY became TRIB3S. What did you learn about digital communication over these years that ultimately had to lead to an independent theory?

Marc Leuzinger: The new name TRIB3S (pronounced «Tribes») actually says a lot about what we observed and learned. We saw that, in the digital sphere, people come together into a «tribe» through shared values, topics and horizons of meaning: a loose group that defines itself through a sense of belonging, a kind of shared identity that is not precisely graspable but can rather be described as a pattern in a dynamic system. In recent years, these identities have become ever stronger and no longer remained in the digital sphere, but shape the whole way of life. One example of this is the manosphere.

Pascal Sieber: I think you'll have to explain that. What is a manosphere?

Marc Leuzinger: The manosphere is an internet ecosystem of influencers, podcasters and self-proclaimed life coaches who explain to young men what masculinity should look like. These are digital communities that spread a way of life built around a dominant ideal of masculinity, along with misogynistic content. Their most prominent figurehead, the influencer Andrew Tate, has since been charged in several countries with sexual violence and further offences.

Pascal Sieber: Your theory of the Digital Society combines three very different intellectual traditions – Stephen Wolfram's generative systems, Niklas Luhmann's systems theory and Shalom Schwartz's model of basic human values. How did you come to bring precisely these three together?

Marc Leuzinger: For that, we have to take another step back to social media and the question of when it became clear to us that something fundamental was changing. The longer we observed digital communication — its unpredictability, the patterns that were observable yet hard to grasp, like communities, or trends that pop up, generate incredible attention and then disappear again shortly afterwards — the clearer the connection became to the complex systems that had accompanied me since my youth. With his science of generative systems, Stephen Wolfram provides the mode of operation on which our model builds. Niklas Luhmann described society as a system. From him comes the understanding of what society actually is. He provides the concepts and the historical observation of society that we use to apply and test our generative model on society. With the ten basic human values, Shalom Schwartz provides a model that is universally applicable and makes people's motivational dispositions graspable — that is, why they act the way they act. We need these values to get our system running: they decide which communication is connectable for a person in the first place.

Pascal Sieber: That sounds a bit abstract — could you give us an example?

Marc Leuzinger: Gladly. Let's look at the simplest form of communication in the digital space, reactions — for example, the Like button.

A like can be understood as communication, because it connects to a preceding communication. Someone posts something, others react with a like. This carries the post further along the social graph, and further likes become more likely. The question is what exactly arises from this.

Through Luhmann's lens, that is not so easy to answer. One might think of an interaction system, of communication among those present, with the platform producing the presence. An interaction system, however, depends on the participants perceiving one another and knowing that they are being perceived. With the like, that is precisely not the case. On top of this, an algorithm carries the post through the system. So there is a hidden authority that makes connecting communication likely. Here, the space is determined by a program within a platform.

With generative systems in the sense of Wolfram, it becomes simpler. The like is an operation that activates a rule. The event thereby connects the participants with one another: the one who created the post and the one who reacts. And because others can react again, a kind of wave arises that runs through the system. So we observe how a post moves onward, activating rules again and again. That produces a pattern. If the post receives very many likes, this pattern becomes observable, and the term virality is used for it. The question now arises: why does a particular post lead to such a pattern? What exactly leads others to like the post?

This brings us to Schwartz. With the values, we can describe the state of the participants — those who post or like, and equally those who are reached by the post and its likes. The question then is which values are activated and through what virality becomes possible at all. The answer is that such patterns can be described as constellations of values. If a particular constellation carries a post, the probability that it is liked increases.

This is of course greatly simplified. But only when we describe communication as a generative system do we obtain any means at all to characterise such patterns. For they are enormously dynamic and unpredictable.

When society fragments

Pascal Sieber: What does that mean quite concretely for the way we experience the public sphere, politics or markets today?

Marc Leuzinger: For that, I have to note briefly that, for Luhmann, society consists of communication that connects again and again to communication. What we just saw with the like therefore applies generally. From this ongoing connecting, patterns arise, and their totality we can understand as society. The digital has changed how such patterns arise. Concretely, each of us today moves within a highly networked system of communication. We exchange, we sort, we develop ideas and opinions. In this way, new communication spaces form continuously, and within these spaces, distinct horizons of meaning develop with which I can identify: a topic, a whole cluster of topics, a lifestyle, particular values. What is remarkable is that these spaces are unpredictable not only in their emergence and their duration, but that we can also choose which of them, and how many, we want to take part in.

This shifts what we perceive as the public sphere. There are no longer the few stages on which what concerns everyone is negotiated. New publics form continuously, each with its own horizons of meaning and values. From the individual's point of view, the public sphere is the pattern they perceive from their perspective, defined by which communication spaces they take part in. For the media and politics, the public sphere becomes an attempt to recognise the patterns that are dominant at the moment. These may collapse again a few months later, but they can equally stabilise over years. On markets, the same dynamics appear: an offering finds resonance in one space and, within days, is everywhere — and just as quickly, attention moves on again.

Pascal Sieber: Would you go into an example to illustrate this?

Marc Leuzinger: A good example of this is AI. The topic is omnipresent, yet enormously difficult to grasp societally. Depending on which values are activated, the topic is interpreted differently and leads to different horizons of meaning. Even a shared value can develop different, contradictory horizons of meaning. If, for example, I regard universalism as an important value — so if the well-being of humanity and the planet stands at the centre — it already becomes quite complex. Topics such as resources and energy consumption lead into a horizon of meaning in which AI represents a problem for our environment. Equally, I may hold the view that AI could find better and more efficient solutions to solve the climate crisis, fight hunger or resolve social injustice. I can understand AI as a problem that replaces people and destroys jobs. At the same time, the same value can result in the opinion that AI leads us into a future in which technology frees us from the burden of work and better solutions are developed for the good of all. I can take one or the other to be reality and absorb it into my horizon of meaning. The same value, but a completely different interpretation. But other values can drive this too. Security demands control through frameworks, and where control is lacking it leads to fears. Stimulation would advocate exploring the possibilities at any price, and self-direction leads to understanding AI as a boost to human creativity. Power, in turn, raises the question of infrastructure, resources and who controls them. With the value of achievement, the possibilities for increasing efficiency are fascinating. Tradition, finally, can lead to simply closing oneself off to the technology, or to seeing it as dangerous for our culture and our life together.

All these horizons of meaning can arise in the digital space, in which different communication spaces form that exist simultaneously. And everyone can decide for themselves which one they enter and how they combine them.

The fascinating thing is that these communication spaces do not lead to a single, whole public, but only serve and stabilise their respective horizons of meaning. This means, however, that certain events are not discussed societally, but are always negotiated within the individual spaces according to their horizon of meaning. If, for example, there is a new model that can do something new, this new thing is discussed and interpreted completely differently — depending on which values drive the horizon of meaning in each case. And in the process it can happen that certain horizons of meaning suddenly gain enormous resonance, because a particular opinion formed within them is carried through the system and gains reach. Which one that will be is practically impossible to foresee.

For politics, for example, this is an enormous challenge. Which laws will be necessary, which can be enforced, and which connections determine when and how majorities form? What gains resonance today may already be over tomorrow. So what is right or wrong in dealing with AI, what is good for us as a society, what the necessary frameworks for the economy are — this is not negotiated on a few stages, but takes place in countless communication spaces that shift, strengthen or weaken again and again and influence one another.

Pascal Sieber: One of your sharpest theses is that polarisation is an observation artefact, not the actual structure of society. What do we overlook when we divide the world only into two camps?

Marc Leuzinger: That has a lot to do with the dynamics of these communication spaces. In the digital space, spaces form very quickly in which certain values are activated and a distinct meaning arises. What counts as true, as right, in one space can mean exactly the opposite in another. These spaces are strongly moralised. The prevailing morality shows me where I can take part and where I am excluded. We call this a micro-morality: it applies only to the specific space and only to the topics negotiated there. So it is not a societal morality that builds up there. Micro-morality is situational, fragmented and multidimensional, because in every space different values are activated.

What we perceive as polarisation is, to a large extent, the result of this mechanism. People developed it in order to orient themselves in a field of virtually infinite possibilities. Micro-morality decides where I find connection, which communication spaces I can take part in and where I am excluded. As long as one thinks of society as a unified whole, this division appears as a splitting of that very society, and we reduce it to a familiar linearity — for example, left and right. In reality it is much more multidimensional. On different topics, people activate different values and divide into different spaces. Polarisation is therefore taking place constantly, but it does not split society into two halves. It divides and re-orders itself again and again, and the whole thing is extremely dynamic.

From identity to the capacity to act

Pascal Sieber: From the theory, a concrete model for organisations has emerged with the soul Framework. What is the soul of an organisation – and why is a classic mission statement no longer enough for it?

Marc Leuzinger: The soul Framework, too, understands the organisation as a complex system: if something is changed in one place, it can lead to unexpected effects in a completely different one. The soul Framework consists of different segments, all of which stand in dependence on one another. At the centre is what makes up the organisation at its core: its purpose, its values, its culture. And by that we do not mean something written on paper — a classic mission statement — but reality as it is actually lived. And this is the observable emergence that arises from the structure, the processes, the decisions, the products and the communication. The soul Framework defines the different segments, how they are constituted, their relationship to one another and the dynamics between them — and that is precisely what we call the soul. It is what makes an organisation what it is, its identity, what makes it alive. To translate it into current AI language: it is the context of an organisation.

Pascal Sieber: This summer, with soulOS, you launched a technological layer meant to make this identity legible for AI agents, secured by a so-called Human Gate. How much autonomy is acceptable for you before the human has to come back into play?

Marc Leuzinger: This question can only be answered individually for each organisation. And the answer, again, is found in the soul. A company oriented solely towards achievement, whose promise is to deliver the best, the fastest or the cheapest, can introduce a very high level of autonomy without corrupting its own core. An organisation, on the other hand, for which societal responsibility is part of its identity — a non-profit, perhaps — must consider very carefully which tasks and decisions it hands over to AI. For if human relationships, goodwill or a sense of community make up an essential part of the identity, then through automation it may damage precisely what it stands for. The Human Gate therefore defines no universally valid limit for autonomy. It translates the soul of the respective organisation into concrete decision spaces: where may AI act autonomously, where must the human be involved, and what may fundamentally not be delegated?

From Digital to Impact

Pascal Sieber: Your keynote at the CNO Panel bears the title «Impact in a society that is reinventing itself». If an organisation can no longer address a shared whole, how can it achieve any impact at all?

Marc Leuzinger: If one understands society as we describe it — as a dynamic pattern of communication spaces with their own horizons of meaning, their own moral notions and their own truths — then an organisation, just like people themselves, must ask the question of which of these spaces it can take part in. Impact means contributing something to the horizon of meaning of these people. The more moralised such a space is, the higher the identification, the approval — but equally the rejection from another space. For organisations, it is incredibly difficult to orient themselves in this wild environment that keeps forming new patterns.

Modern society was structured in such a way that morality was kept out of the functional system. That is why, in most organisations today, one finds employees with very different value profiles. But these employees now suddenly bring their new behaviours into the company, and so moralised spaces with diametrically opposed horizons of meaning form there too. What one space wants to create, another wants to prevent. The organisation is paralysed and lasting impact is prevented. These dynamics confront organisations with immense challenges. To continue achieving impact, they must become clearly aware of which spaces they can belong to, and enable a clear identification both internally and externally. Only in this way can they ensure that, over time, an alignment emerges that makes long-term impact possible.

Pascal Sieber: As I listen to you, I keep swinging back and forth between multiple belonging and loneliness. Is there a tendency for people to grow lonely in this constant need to make micro-moral judgements?

Marc Leuzinger: This swinging is understandable and shows how we are currently struggling to bring the physical and the digital world together. We recently met a young entrepreneur from Gen Z who, every three months, rents an Airbnb in a different country and meets his digital, international community there to live and work together. When we asked him why he does this, he said he had tried to live in a shared flat here. But he had nothing in common with these people and could not exchange with them. So he found his tribe in the digital world — a group with which he shares values and a horizon of meaning. In the physical world, in his shared flat, he could not find these people and this sense of belonging, and grew lonely.

The interesting thing about this is that, of course, micro-morality is thereby also circumvented. In the digital world it helps one to orient oneself; in the physical world it becomes a problem. To have nothing in common means, translated, to follow different horizons of meaning, which makes micro-morality to be expected. To seek out one's tribe therefore also means, conversely, to circumvent the effects of micro-morality as far as possible. This phenomenon — wanting to circumvent micro-morality — can be observed in both the physical and the digital space. In so-called safe spaces, clear rules are set for who may take part, what may be discussed and which values apply. The concept of the network state can perhaps be understood as its most extreme form: values and purpose lay the foundation for the emergence of a global community, which then begins to manifest itself geographically through the purchase of land and understands itself as a new form of state.

Pascal Sieber: What is the one thought you want to give the CNOs in the audience on 26 October, before they set their AI strategy for the coming years?

Marc Leuzinger: AI is not simply a technology; it becomes an actor in the system. Like society, organisations too consist of communication — concretely, of decisions about what they do and want to do. Agents now take part in this communication, decide alongside or prepare decisions. AI thus affects the dynamics of the organisation, at every possible point. And the first big strategic question is what effects are to be expected from this: on the structure, the offering, the culture, the collaboration, the communication both outwardly and inwardly.

The second question is how AI can be deployed to strengthen the organisation's identity — that is, to improve the alignment of the different segments. This leads to an even more fundamental question: how can AI understand at all what this identity is? How can it decide the way the organisation would decide? How can it communicate the way the organisation would communicate? That is extremely complex; from the experiences it gathers in communicating with people, it must learn to draw the right conclusions.

Pascal Sieber: Dear Marc, thank you for these insights and reflections, and I wish you all the best for your professional and personal experiences.