 Hello and welcome back to Beyond Networks, the evolution of living systems. Today, we're finally gonna move back to biology from our excursion into perspectivism and process philosophy. But before we do that, let me just quickly recap. It's been quite a dense and loaded module so far. In lecture one, we refocused our attention away from what we know to what we don't know, from facts, the questions, which are extremely important for scientific inquiry. In lecture two, we asked why it is so hard to think about processes. It's ingrained that we think about the world in terms of things. And we took a very short tour of the history of process philosophy and introduced a few tools for identifying and classifying processes. In lecture three, we looked at the process of scientific inquiry itself. And the main point I wanted to get across there, it's quite complicated, but it's really, really cool, is that our scientific theories evolve quite like other complex adaptive systems, like organisms or technological systems in the way that they adapt to reality, just like an organism adapts to its environment. And that they also share some features with organisms and other adaptive systems, complex adaptive systems. For example, their modularity or near decomposability, some interactions, some heuristics connections are more important than others, and that they have this sort of generative entrenchment, some theories become the foundation of others and become much harder to change over time. And we finished that lecture by saying that progress in science requires different strategies at different times, depending on whether you're in a phase of normal science, when you exploit an existing paradigm or revolutionary science, when you explore new perspectives. And I think we are at one of these points where the existing paradigms have exhausted themselves a little bit and it's time to explore and try new perspectives. So in this spirit, we'll move on and look at biology, taking various process perspectives and explore those in a speculative playful manner. So let's get started. I want to start this lecture by reminding you how the majority of Western philosophy and therefore also the foundation of science is based on a substance-based view of the universe. So the main question in this sort of view is what is the world made of? You try to decompose the world and then to identify what the components are of that. And then what these components do is sort of an epiphenomenon, something secondary or derived that depends on the properties of the things. This view has been the mainstream view of philosophers in the Western world since before. Socrates, the pre-Socratic philosophers, just like Parmenides, Democritus or Leukipus. The atomists were focusing on this sort of question, what is the world made of in the case of Democritus and Leukipus, of course? It was made of atoms that sort of bump into each other and cause the phenomena that we see. And so this is sort of manifested by this mechanistic worldview that modern science has adopted that goes back to René Descartes that sees the universe as a sort of an intricate mechanism. And if we take the components of this mechanism apart, we will understand how the world works. So this sort of metaphors based on machines and mechanisms are very, very prevalent. And I'm gonna use the work of contemporary philosopher Dan Nicholson, who is at the Conrad Lorenz Institute here in close to Neuburg at the moment. I'm gonna lean a lot on his work in this area. And I'm gonna quote a contribution he's made to an absolutely fantastic book called Everything Flows. I'm gonna share a link where you can get it for free. It's about processional approaches to biology. And Dan says, but out of the endless array of metaphors used in science, it is difficult to think of one that has been more dominant and has exerted a greater influence than the machine metaphor, which provided the basic theoretical foundation for a mechanistic natural philosophy in both physics and biology. And if you look at a history of science, this idea originally came from physics, but ironically, physics has moved on while biology is firmly stuck in it. So let's look at that in a second. But first of all, let's sort of think what is the consequence of this sort of world we want is that we view the world as deterministic in some, they're strong and weak forms of this. The strong form is Laplacian, the demon that sort of knows where all the parts are and how to interact and then can predict the entire future and the past of the universe. A weaker form is just to say that every effect must have a cause in some way, which is something that we can probably subscribe to. The other aspect of this mechanistic worldview is reductionism, right? So that we approach the world basically by taking it apart. If we want to understand the system, we take it apart, we try to find its parts just like a clockwork, the gears inside. And if we know how those gears interact, then we know how the system works. So as I said, in physics, about 100 years ago, physics moved away from this sort of optimistic view where you have small things that bang into each other. There's a great book by James Laderman and Don Ross, which is called Everything Must Go. And they look at physics in particular and sort of the basic fundamental reality of particle physics and all that. And they say, okay, since relativity, since quantum physics has come, physics has switched from this idea that there's atoms that bump into each other and create all the phenomena to a view that's much more based on sort of fields. Here we have the enterprise, or is it Voyager? I don't know, in some sort of warp field, waves and forces to mix the sci-fi metaphors a bit here. So physics is sort of thinking in a much more systems level way. Fields are, what arrange, so the spatial temporal arrangement of forces that cause the components of the system to sort of organize in a sort of a global way. So think of them in any field. They're little iron shavings and they all align in a certain way. So there's sort of a global patterning generator there. And we rarely think about such mechanisms or such large scale phenomenon in biology. So ironically, while the mechanistic world we came originally from physics, it is much more prevalent in biology today. And this is a little funny. But I mean, so the idea that biology is purely mechanistic starts right with René Descartes as well. So he writes in two different books about the organism. And so one of the quotes here is the human body that's about us is indistinguishable from a perfectly designed automaton. Even we, our bodies at least, because of course he believed that the mind is in a different sort of realm, are purely sort of clockwork mechanisms. Later he writes description of this automaton amounts to an explanation of the organism. So for him, all living systems were purely mechanical systems. And we've already encountered the sort of perfect manifestation of this metaphor of the machine in de la maitrie and is long machine where he writes an organism is basically just a self winding clock. Of course, there's a lot resting on this sort of self winding aspect of the system. And he never tells us exactly how that is supposed to work. And so this machine metaphor, not just for the world in general, for the movement of the planets, but also for the workings, the inner workings of living beings has stayed with us, although it has mutated over time, depending on the most popular technologies of the day. So in the late 18th and early 19th century, the metaphor du jour was the steam engine, no longer the self finding clock. Later on, human bodies became chemical factories in the early 20th century. And nowadays of course we prefer metaphors to come from computer technology. So it's always the sort of the latest, most fashionable technology that provides the metaphors. And it's evolving in parallel with the technology. So what happened at the same time at the conceptual level is sort of stated here by evolutionary biologist, Richard Lewontin, who says the metaphor of all modern science, the machine model that we owe to the cart has ceased to be a metaphor and has become unquestioned reality. Organisms are no longer like machines, they are machines now. Okay, so we've forgotten, and this is the danger with metaphors, we've forgotten that we have adopted terms from or analogies from our technology to talk about natural systems. And so this leads to a bunch of very predominant sort of paradigms that are no longer valid. So we'll talk about those for the rest of the course. Let me just quickly introduce them right here. So one of the phenomena that I'll criticize here is the idea that evolution leads to organisms that are somehow designed, optimized by evolution, by selection, okay? So this idea that evolution is an optimizing process comes of course from computer science and engineering where you optimize the performance of machines as I started saying in the introductory lectures, also optimizing our schedules, our time, our performance. And the other sort of aspect of that is the idea of genetic information and the genetic program in the genome that sort of runs and creates the phenotype as it goes along. These are machine-based, computer-based metaphors. Also very famous of course is the idea that the cell is some sort of factory that's based on molecular machines. This idea of a molecular machine goes back as far as I know to Sydney Brenner. And so he thought about protein and protein complexes, little machines that work in a factory assembly line built the cell. And this has been taken to its culmination in the BioBricks Synthetic Biology Project where the idea is that you create a sort of collection of plasmids that encode different circuit elements. And just like you can build an electronic circuit from basic elements, you could build regulatory circuits in synthetic regulatory circuits and cells by putting together these different plasmids that form the basic elements of those circuits. This project is spectacularly failing right now. In very few cases is it true that these elements are put together and they do what they're supposed to do. We'll talk about why that is later on in the course. And so here we're clearly sort of hitting a wall, hitting the limitations of this engineering metaphor of the machine. And so I'm gonna quote a physicist, David Bohm, with a diagnosis of what's going on in biology. And he says, and why it's so strange, right? He says, modern molecular biologists, okay? He's writing this in the 70s, but things haven't changed very much. Modern molecular biologists generally believe that the whole of life and mind can ultimately be understood in more or less mechanical terms. Thus, we arrive at the very odd result that in the study of life and mind, which are just the fields in which formative cause acting in undivided and unbroken flowing movement is most evident to experience and observation. There is now the strongest belief in the fragmentary animistic approach to reality in biology, no longer in physics. And he thinks, as a physicist, he thinks that's weird. Let's contemplate this again for a second. So the study of life and mind, just the fields in which formative cause, we'll talk about what a formative cause is, acting in undivided and unbroken flowing movement is beautiful, is most evident to experience and observation. We can see it with our own eyes. That's how living systems are different from mechanical ones. And especially it's weird that exactly in this area of investigation, we have such a strong belief in the fragmentary animistic approach to reality. There is a disconnect between what we see in biology and how we go about studying. And I've chosen a physicist to tell you that, but of course, there's also a lot of biologists who have noticed this. So basically, this whole mechanistic view of the world comes from substance-based philosophy that underlies Western science and Western philosophy. And the main problem this creates in biology is that you have explanations in terms of things, and then you need to attribute agency to those things. So let's talk about elementary particles and physics or genes as determinants of heredity, form, physiology and behavior in biology. The genes have to do stuff. And it's sort of, the main problem here lies in explaining how they do it. In the 1990s, there was a headline, late 1990s, Dean Hamer, I think, and other people who were involved who found the alleles of a gene that were associated with being gay, so enriched in the gay population. And there were headlines saying, we found the gay gene here. There's a gene that makes you gay. It's absurd, okay? These were, I think Hamer was himself gay. So the idea was that if you would have a genetic explanation for being gay, there would be less pressure in sort of trying to explain that it's a natural thing. That's fair enough. But what do you mean by saying that the gene makes you gay? So there is no connection, causal connection between the two things. The gene produces a protein, that's it. And that's all it does. And so there is a huge gap in trying to explain how a gene is supposed to act to make you behave in a different way, of course. And I'm drawing, this is oversimplified, of course. We are much more sophisticated nowadays, but the problem has sort of remained the same. So we nowadays, we no longer have single genes that cause complex phenotypes, but we have gene regulatory networks. So this is an example, beautiful work by Eric Davidson and his collaborators over 30 years, 40 years of very hard work. They have pieced together a network of those genes that are involved in the determination of the endomysoderm in early sea urchin development. And what you can see here is a diagram. So the names and this diagram are different genes and the arrows show you how these genes are connected in different tissues at different times indicated by color, sort of boxes in the background. Massively complicated, a lot of work, very much detail. Everything has been decomposition. This is the mechanism that creates pattern in this embryo. But the problem is it doesn't really explain how the pattern is formed because it's just a diagram. It's a summary diagram of a lot of work, but the problem here is it doesn't tell you what this system does, right? So in a way, it still has this explanatory gap. It's a thing, it's a static diagram and we need to know how we get from this thing to its behavior and that's the big challenge. In a way, this is not an explanation. It's a challenge. This is wonderful work, but it doesn't explain how the sea urchin grows. It is sort of a challenge for us to sit down and figure out what this system actually does, but it doesn't do this by itself. So if we take a process perspective on biology, we want to know how things work, what they do. This is a problem because a lot of systems biology is not really systems biology. It's the type of systems biology where you go to a meeting, you have a bunch of shapes connected by lines thrown at you and everybody is really impressed, mainly because these diagrams show you, A, it's complicated, B, this person has done a lot of work in their lab. Fantastic, and we're all impressed, but we shouldn't be asking, so how do we get from those diagrams the actual behavior? I think there's two problems. One I've already mentioned, the diagram doesn't tell you what the system actually does and the other one is that these diagrams are not just summary of work, they're also idealizations that sort of distort and also ignore a lot of what's going on underneath and we'll come back to that, of course, during the course. So how can we move beyond this sort of systems biology of the networks? And also by moving beyond networks, networks are an engineering metaphor based on the machine view of the world. How can we move towards a more organic processional view of biology? So several people have tried, there's a long tradition. Aristotle himself was very much influenced by biology, it wasn't called biology at the time, but he was very much interested in animals and their natural history. But I think so the main sort of philosophy modern in modern times here that connects to biology is probably Alfred North Whitehead's philosophy of the organism. He builds on earlier work by Henri Bergson and other people, but basically what he's saying, what he's trying to say with this is that in a way, biology is more important than physics because he denies that there's a distinction between organic and inorganic matter. He goes very far in this. So he becomes a pan-psychist where he believes that even simple matters are in some way sanctioned. We don't have to follow down that path, but the other remarks that he's making are very interesting. He says, biology in a lot of ways is more fundamental than physics because physics is just looking at those aspects of the natural world that are not organic. They're not influenced by this matter. There's no distinction between matter that is organic and inorganic. And he sort of says physics is just explaining that part of the world, which is not a wide, which is less than the world in total, which is living and non-living things. So also he has this sort of idea that through perceiving you become part of the world, you're being in the world and you experience causality directly. So he moves away very much from earlier arguments where or contemporary arguments in philosophy where people were focusing on how we represent the world by language. He says, this is not the case. There's a much more direct way of perceiving the world, just like Michael Polanyi will later say, that you build up a sort of a tacit understanding and awareness of your circumstances. And so in a way you are in the world, you are part of the world and emerging, your insights are emerging directly from the world. And there is no sort of disconnect between the world in itself and your representation. So very interesting sort of aspects. I highly recommend you read Science in the Modern World if you're interested in this. We will not have time to go much into his ideas, but so Whitehead is at the beginning of a long tradition of process philosophy moving into biology and this tradition is carried on by one of his students, Suzanne Langer, who is mainly famous as a philosopher of art, but she in the 1950s and 60s also developed what she calls a process-oriented philosophy of biology, which is very interesting. And she says, living systems are composed of acts and by acts she means temporally drawn out living processes. She said, it doesn't make sense to organize, to analyze organisms in terms of what they are made of, their composition, but the acts that constitute them, these processes that work together, an organism is built up by its own acts, she says. Remember, these are processes and these processes should be examined in terms of their temporal structure. We're gonna go a lot into what that means with a temporal structure is in later lectures. Okay, so these are the beginnings of philosophers moving into biology, but here we're gonna focus on the work of biologists who took an explicitly process-based perspective. And one of the important people, of course, at the beginning of that tradition is Conrad Howe Waddington, who in 1957 wrote his fabulous and famous book, Strategy of the Genes, still as accurate and important as it was ever. And he introduced and promoted, mainly in that book, of course, his metaphor, his image of the epigenetic landscape that you can see here in an unusual artistic depiction. So I want to show you that it's actually moving during development and evolution, it's constantly changing its shape. His work, Waddington's work was later formalized by French mathematician, René Tom, who invented a whole branch of mathematics called catastrophe theory to formalize that the ideas that Waddington had in his landscape metaphor. And that work in turn inspired Salvador Dali, who here, this is his last painting that he ever painted. It's called Swallow's Tale, and he depicts one of Tom's mathematical structures in this painting. So this is a formal science of processes and biology and we'll introduce this and talk about it. We'll take a little bit and see what we can still get out of this today. Or take the work of Stuart Kaufman, who in the late 60s starts to model the dynamics of chain regulatory network and also their evolutionary dynamics, how order emerges from random behavior in those networks. Beautiful work that we'll talk about. And most dear to me, the tradition of process structuralism in biology, Waddington's students, Brian Goodwin, was the most prominent figure in this movement. He was my master supervisor, but also other people who would not directly identify themselves as process structuralists like George Oster and Perra Albert, who worked in the tradition of Ivo Divo, took a very similar approach to study the evolution of developmental processes, very much based explicitly on the fact that we're dealing with processes. So we're gonna go into the work of those people and many, many, many more that followed them over the course of this lecture series. But before we can get to the sort of nitty-gritty practicalities, we need to ask ourselves a very fundamental question. I've been throwing this term system around a lot. And it's sort of at the basis of systems biology, what is a system? We'll ask ourselves this question in the next module and also how you can understand systems with the tools of using mathematical models. This will be the topic of the next module. I hope you tune in again next week when we talk about systems and models. Thank you very much for listening. Enjoy the rest of your Sunday. Bye-bye.