COMPLEXITY: Physics of Life

Aviv Bergman on The Evolution of Robustness and Integrating The Disciplines

Episode Notes

Ask any martial artist: It’s not just where a person strikes you but your stance that matters. The amplitude and angle of a blow is one thing but how you can absorb and/or deflect it makes the difference. The same is true in any evolutionary system. Most people seem to know “the butterfly effect” where tiny changes lead to large results, but the inverse also works: complex organisms buffer their development against adverse mutations so that tiny changes cannot redirect the growth of limbs and other organs. It takes a lot to shake the pattern of five fingers on a hand, or five toes on a paw. This is robustness: how much change can something soak up before it transforms? The question leads us into a secret garden of cryptic variation: mutations waiting for their moment, pieces sitting in place that might suddenly and radically metamorphose in changing circumstances. It’s why evolution stutters, halts and leaps, and maybe it can help us think about society and mind in ways that deepen comprehension of the tangled and surprising forces playing out at all scales, in society and in ecology. For quests as deep as these, we need to wear new lenses and train inquiries stereoscopically. How can and do the sciences and the humanities inform each other as we keep evolving — not just biologically, but culturally? Can we triangulate the truth by holding theories side by side and looking through them all together?

Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I’m your host, Michael Garfield, and every other week we’ll bring you with us for far-ranging conversations with our worldwide network of rigorous researchers developing new frameworks to explain the deepest mysteries of the universe.

This week, we speak with Aviv Bergman (Google Scholar), External Professor of the Santa Fe Institute and Director of the new Albert Einstein Institute for Advanced Study in the Life Sciences.

Be sure to check out our extensive show notes with links to all our references at complexity.simplecast.com. Note that our applications for SFI postdoctoral fellowships open on August 1st! Tell a friend.

If you value our research and communication efforts, please subscribe, rate and review us at Apple Podcasts or Spotify, and consider making a donation — or finding other ways to engage with us — at santafe.edu/engage.

Thank you for listening!

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Podcast theme music by Mitch Mignano.

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Mentioned Papers:

Waddington’s canalization revisited: Developmental stability and evolution
Mark L. Siegal & Aviv Bergman

Evolutionary capacitance as a general feature of complex gene networks
Aviv Bergman & Mark L. Siegal

Phenotypic Pliancy and the Breakdown of Epigenetic Polycomb Mechanisms
Maryl Lambros, Yehonatan Sella, Aviv Bergman

Mammalian Endothermy Optimally Restricts Fungi and Metabolic Costs
Aviv Bergman & Arturo Casadevall

How on Earth can Aliens Survive? Concept and Case Study
Aviv Bergman’s 2022 SFI Seminar


Additional Mentioned Podcasts, Videos, & Writing:

Melanie Mitchell on Artificial Intelligence: What We Still Don't Know

On Coronavirus, Crisis, and Creative Opportunity with David Krakauer (Transmission Series Ep. 3)

Ricardo Hausmann & J. Doyne Farmer on Evolving Technologies & Market Ecologies (EPE 03)

Olivia Judson on Major Energy Transitions in Evolutionary History

James Evans on Social Computing and Diversity by Design

Mirta Galesic on Social Learning & Decision-making

What Determines The Complexity of Writing Systems?
on the work of SFI Fellow Helena Miton

Does the Ecology of Somatic Tissue Normally Constrain the Evolution of Cancer?
SFI Seminar by External Professor John Pepper

Explosive Proofs of Mathematical Truths
SFI Seminar by External Professor Simon DeDeo

Armchair Science
by 2022 SFI Journalism Fellow Dan Falk at Aeon Magazine

The coming battle for the COVID-19 narrative
Samuel Bowles, Wendy Carlin 10 April 2020

Ignorance, Failure, Uncertainty, and the Optimism of Science
Stuart Firestein’s 2022 SFI Community Lecture

Smarter Parts Make Collective Systems Too Stubborn
Jordana Cepelewicz at Aeon Magazine

"Ancestral forms are very different, but as you increase regulatory interactions is decreasing the space of the possible. You can think of bureaucracy..."
- SFI President David Krakauer on #DevoBias2018

Episode Transcription

Aviv Bergman (0s): Scientists should thrive on ambiguity and uncertainty. Without it we are doing engineering. Not that engineering is bad, but it's different from science. Science is an activity inherently that puts you in an ambiguous and in an uncertain situation. You are looking to pave a path that first and foremost, you do not know where it leads.

And if you are even more daring not to follow a path that others have created, but to go to a completely uncharted area and to ask whatever big questions you are asking, you are interested in asking. And I believe that this is not the characteristics of a scientist or a scientist alone.

This should be the characteristics of every intellectual in our society to be not only comfortable, but thriving and seeking to be in ambiguous and uncertain situation

Michael Garfield (1m 49s): And ask any martial artist. It's not just where a person strikes you, but your stance that matters. The amplitude and angle of a blow is one thing, but how you can absorb and or deflect, it makes the difference. The same is true in any evolutionary system. Most people seem to know the Butterfly Effect where tiny changes lead to larger results, but the inverse also works. Complex organisms buffer their development against adverse mutations so that tiny changes can I redirect the growth of limbs or other organs. It takes a lot to shake the pattern of five fingers on a hand five toes on a paw. This is robustness. How much change can something soak up before it transforms? The question leads us into a secret garden of cryptic variation. Mutations are waiting for their moment, pieces sitting in place that might suddenly and radically metamorphose and changing circumstances.

It's why evolution stutters, halts, and leaps. And maybe it can help us think about society and mind in ways that deepen comprehension of the tangled and surprising forces playing out at all scales in society and in ecology. For quests as deep as these, we needed to wear new lenses and train inquiries, stereoscopically. How can and do the sciences in humanities and form each other as we keep evolving, not just biologically, but culturally, can we triangulate the truth by holding theory side by side and looking through them all together?

Welcome to 

Complexity

, the official podcast of the Santa Fe Institute. I'm your host, Michael Garfield, and every other week, we'll bring you with us for far-ranging conversations with our worldwide network of rigorous researchers developing new frameworks, to explain the deepest mysteries of the universe. This week, we speak with Aviv Bergman, External Professor of the Santa Fe Institute and Director of the new Albert Einstein Institute for Advanced Study in the Life Sciences. Be sure to check out our extensive show notes with links to all ourreferencesat 

complexity.simplecast.com

and note that our applications for SFI post-doctoral fellowships open on August 1st. Tell a friend. If you value our research and communication efforts, please subscribe, rate, and reviewus at applepodcasts or Spotify and consider making a donation or finding other ways to engage with us at 

santafe.edu/engage

.

Thank you for listening. Aviv Bergman, such a pleasure to have you on 

Complexity 

podcast.

Aviv Bergman (4m 30s): Thank you. Thank you for having me. Even though I'm not used to be the focus of attention. I think this makes me a bit nervous.

Michael Garfield (4m 41s): No reason to be nervous. I loved the presentation that you gave here. I love the writing that you did on your new Institute. I think we're going to have a lot of fun today. So let's start first by giving people a little bit of a background into your own intellectual biography, you, as a mind, and the questions that animated you. How did you become a scientist? What is your backstory? And then we'll lead from that into the meat of today's conversation?

Aviv Bergman (5m 14s): Well, it clearly is an unsolvable question for me. I was born and raised in Tel-Aviv coming from a modest socioeconomic background, but I was lucky to live in an early Tel-Aviv where both physical and error, well education and knowledge were highly valued. I grew up in a, as I said, affluent earlier, coming from a modest background and I strive to be as knowledgeable as possible in very specific areas, not necessarily the humanities, but mainly the sciences and the math aspect of my studies.

And I arrived at a relatively early age at the Technion and from there moved to the Weitzman Institute, then served in the army, was part of the seven Yom Kipper War, 73 war, as well as the first Lebanon War. And then I was recruited to fuel think-tanks or we saw companies within Israel. And there was a moment where I always served awful.

I could not refuse from the Stanford Research Institute, the AI and robotics club that attracted me to the US, which I promised my wife that it will be four years. And this was in 1985 and then many things have happened. I was bought off think tank that Paul Allen created then moved with quite a bit of support from his foundation back to Stanford.

Well, I created what is now kind of be considered the first systems biology group. So my first education was in physics and a high energy physics, theoretical physics. And when I've arrived at Stanford Research Institute, I was, we called it as early solar physicist and then very quickly decided to switch to biology. And this was in the mid- eighties where I was also being introduced to the Santa Fe Institute.

So I started to be involved with the activities here since mid to late 80s, 95. So it's quite sometimes ago, but again, my foyer towards biology was a fairly easy walking the park for me because I never entered the lab doing my PhD in biology. It was purely theoretical. And I was asking the question that ___ Eldon philosophy, which was, why do we need to learn? Later on I switched their questions into why do we need to communicate? And the questions remains, the questions that I'm asking in biology remains relatively high-level questions. We start backround, I must say one caveat, which is whatever I'm going to say here, or whatever I've done in the past is something that not only my work, but most scientific work is going to be antiquated in 5, 10, 15 years from now.

So please stay whatever I'm saying with a grain of salt.

Michael Garfield (9m 7s): Well, I mean, for sure we treat this show, treat these episodes as snapshots and to a process of discovery. And I definitely want to loop back around to that point because in the last act of this conversation, I want to talk with you a little bit about your manifested for the new Institute. You talk a lot about the overturning and revolutionary component of science, but first I want to get into what it is that we overturn which is how and why do stable forms evolve even under conditions where there is no strong selective pressure. And so for that, I want to talk about this piece that you co-authored with Mark Siegal on Waddington's canalization revisited developmental stability and evolution, but to start, we should give the background of that. What is canalization? What is the history of thinking that you lay out in the introduction to this paper so that we can understand where your work builds on refines and challenges?

What has come before? Tell me about canalization

Aviv Bergman (10m 19s): Canalization or buffering or robustness, these terms are going to be used in this conversation interchangeably. First and foremost, I would like to credit my collaborations with Mark Siegal, who is now a Professor at NYU for this work, that time that we did, this was almost two decades ago. Mark was a postdoctoral fellow at Stanford and part of my center there.

And he was an experimental biologist for whom I have run. And I used to work as an undergrad, practically running the lab. So this is how I got my real education in biology. But nevertheless, robustness canalization is a concept that was introduced by Waddington in the thirties, in the forties, which is a concept where the observed phenotype is by far more robust to underlying _______ at the genetic level, namely everything, which is at the genetic level will percolate to the phenotypic space, the underlying valuation, which is about, let's say 600,000 base bill between any tool randomly chosen individual is not expressed at the phenotypic level.

So most of us have five fingers, two eyes, et cetera. Granted they'll all develop mental aberration, but they'll by far less frequent than what it is that we have at their underlying genetic level that brings about these phenotypes. Now, the theory that Waddington postulated is that if there is a genetic mechanism that will baffle, that will, canalize the expression of the genes, the variation in the expression of the genes when they are mapped to the phenotypic level in such a way that it will not interfere with the phenotypic expression in the phenotypes that is, let's say good for us is the five fingers, type any mechanism that baffled dislocation is going to be selected for. Now, what we have done in this piece of work, we visiting his canalization hypothesis is to challenge the idea that there is a need for natural selection to operate and to calculate from the phenotypic level all the way down to the genetic mechanism that brings about this phenotype, the phenotype, which is presumably under selection.

And we have demonstrated that there is no need for such natural selection, four or five fingers, stabilizing selection for five fingers.

Michael Garfield (13m 26s): So for people that aren't used to thinking in these terms, I'd like to posit an analogy here, see what you think of this. You know, it strikes me that this work has a lot to do with Melanie Mitchell's work in artificial intelligence and the development of concepts and the generalized ability of an idea learned in one domain to another domain, or, for people that come out of a philosophical background, you know, this has to do with, it sounds to me like this notion of there being a sort of a form of a dog.

There's all of this variation that we still recognize that this object is a dog, or, you know, you think about Helena Miton’s work on the evolution of writing systems and how much variance you get in the typography. You know, you can say, oh, that's still the letter B that there is that beingness or dogness is robust. I feel like we're going to be jumping around between levels a lot in this conversation because even though in this work, you make the case that this is happening without stabilizing selection at the evolutionary timescale this does strengthen an argument that selection is happening across multiple different spatial temporal scales.

Aviv Bergman (14m 48s): Absolutely not. I'm not against election whatsoever.  I’m Darwinian sworn through, even though we can go into more deeply philosophical question about what was the inadvertent aspect of Darwinian theory in biological thinking is, but you're absolutely right. The analogy would be kind of baffling noise to arrive at the concept. With that said the robustness aspect might be thought of as hindering the process of evolution because evolutionary selection pressure operates at the phenotypic level.

And if phenotypes are being kind of remain constant independent of the underlying genetic variation, natural selection has more valuation to select from. However, at the time of stress and this is, well, we deviate from this analogy a little bit, it is not necessarily considered as noise because this underlying valuation at time of stress is going to be expressed at the phenotypic level, enabling evolution, actually to accelerate its process, it's time of stress because the underlying accumulated cryptic palliation under normal conditions is going to be expressed at the phenotypic level and then evolution. Now it's processed and accelerated. And this is also part of the studies that we have done to demonstrate that the cryptic variation has a role when time will stress is present.

Michael Garfield (16m 39s): So this rhymes very strongly with a theme that has come up on the show again and again, which I'd like to encapsulate in the pithy statement by a Gonzo journalist Hunter S. Thompson, who said when the going gets weird, the weird turn pro, that to look at it in terms of more like human social concerns, that there's always a reservoir of neurodivergence in populations as a kind of bet-hedging against different environments, for instance, balances between specialists and generalists, which, you know, David Krakauer and I discussed in episode 29 and then as an environment becomes more and more unstable than the generalists that were punished in a stable regime end up turning pro. And you get things like lystrosaurus, which was this super generalist, almost the only thing that survived the Permian mass extinction.

Aviv Bergman (17m 33s): Yes, there are many examples of that. And there is another piece of work that was done by Joanna Maizel and myself, while she was a postdoc again at Stanford with Mark Feldman where we demonstrated that prior in yeast, even though deleterious to you now, the way they operate is by running small stock called on generated. Now it’ll be totally proteins. And what she has demonstrated is that even if it is giving you a benefit of one per million years, these prior on will evolve in fixate in the population.

So even though it is deleterious quote unquote under normal condition, when time of stress comes, all of a sudden we have a repertoire of proteins that are going to be beneficial for these. So this idea of accumulation, of cryptic, genetic variation, probably something which is prevalent in biological systems,

Michael Garfield (18m 41s): Not to spoil the climax of this episode but I do also want to just call that shot and say that this reminded me of Thomas Kuhn's work on scientific revolutions and how you get cryptic variation in the paradigm as certain researchers are more or less attuned to anomalous evidence. And so at some point there's a catastrophic shift of some kind and you get

Aviv Bergman (19m 8s): Paradigm shift.

Michael Garfield (19m 9s): But first I want to get into the way that you're actually thinking about this in terms of the phenotypic fidelity and pliancy as you discuss it in your work on development, in an organism, and just talk about how you actually see this unpacking itself. You talk about genetic capacitors and you go into a considerable amount of detail on another paper with Mark Siegal on this evolutionary capacitance as a general feature of complex gene networks.

And so what is it about the structure and the behavior of these networks that's doing what you're saying?

Aviv Bergman (19m 49s): What we asked for, what are the causes and the consequences of devolution of robustness. In this paper on evolutionary capacitance, we discuss the hypothesis by Sue Lindquist and Susan Rutherford that claimed that HSP 90, for example, into sofula is an evolutionary capacitance, which is unique and evolves for that particular property.

And what we have demonstrated, as I said with the walkabout Waddington is that we do not need natural selection or stabilizing selection to evolve. In a second early piece of work, again, was Mark Siegal. What we showed is that it is sufficient to have a complex genotype phenotype mapping in order to arrive at a robust system to sensitivity.

So it is a property of a complex gene regulatory network and not necessarily a specific gene searches HSP 90. HSP, 90 may be one off family of possible mechanism by which one can achieve robustness. And the one that we have looked at is the fact that it is, as I said, sufficient, to have a genotype phenotype map, which is complex to how build genetic variation and the more complexities and complexity in our measure, or in this particular work was the amount of interactions that are present in a gene regulatory network.

The higher it is, the more capable the system is to how build the cryptic variation. And as we said in the paper, which was later cited as, so one of the revolutionary germs, it is kind of an unavoidable consequence of genotype phenotype map that as a result, you get robust phenotype to underlying valuation.

Michael Garfield (22m 9s): So just because this is where I tend to be attractor into which my thoughts run in these conversations.

Aviv Bergman (22m 18s): It's an attractor.

Michael Garfield (22m 19s): Yes, we're getting kind of meta here, but my analogies, I think are sort of robust to perturbations in the environmental variation of our conversations on this show, But you know, something that comes up again and again, for me in thinking about stuff like this, and I'm curious what you think about this is the robustness of organizations to change and how an organization can be largely comprised of quote unquote, mutants that want some sort of systemic change.

And yet there is a tension between the agency and the desires of the individuals that constitute an organization or a society, and the phenotype and the agency of the entire organization. So you end up with these things like, I guess one example might be the hippies going square, that like everybody had these aspirational hopes that they were going to be able to change society. And just the quote unquote long arc of history takes an incredibly long time to bend and generations and generations to bend in a different direction.

So I'm curious your thoughts on that kind of analogy, because again, that's kind of foreshadowing the conversation I want to have with you at the end of this, about the formation of new academic projects and so on.

Aviv Bergman (23m 41s): There is an interesting interplay between development often organization, often no biological organization and its evolution. So just going back for a second to Waddington, he was the first one to recognize that when we study evolution, we neglect development and he was the first one to indicate that such a thing is required.

And this is what we have done in our work. But what I wanted to bring about is to go back for a second to evolution without necessarily focusing on the development aspect in evolution. There are few modes. There is the kind of gradual mold that Darwin was talking about when he described the process of slow accumulated mutations. That brings us to the hill on one hand.

And in contrast to that, we have the illusion Gould type of evolutionary process with cheese, a punctuated process. Now the punctuated process is not working in a vacuum. It works where you have underlying genetic variation accumulated, and there are moments in which there is enough of those to arrive at the point where the entire population is being shifted into a very dramatic, different phenotypic characteristics.

So there are many ways, again, to explain this phenomenon. there was the shifting balance theory by civil rights that was introduced in the 1930s later, been used as a mechanism to explain punctuated equilibrium. But again, what we have demonstrated we is that there is nothing new under the sun. This is a simple stochastic process that is the interplay between the size of the population and their mutation rate that can cause for example, these shift from one phenotype to another phenotype, and this goes to society. There was an interesting student at Stanford I forgot his name, he was a political theorist who study Mount Temple in Israel and specifically the moment where the change of direction in Islam was from Jerusalem to Mecca.

And it was a moment where the idea came from disciples of Muhammad and they approached him to suggest that possibility. And he probably knew more than anybody else about human behavior at that time. And what he did was assemble a large group of people. And at the middle of the prayer, he switched the direction himself.

The rest of the crowd follow in the rest is history. This is kind of a punctuated phenotypic characteristics at the global level that changed something culturally very, very dramatically.

Michael Garfield (27m 23s): I guess the other example, I mean, examples abound here. You know, the other one is, was it Sweden that on the same day they had everyone starting to drive on the opposite side of the street, or another one that a little closer to home here at SFI, as I remember and love and constantly reference this talk that Simon DeDeo gave here a few years ago on, if you think about mathematical proofs, not as a linear series of premises that build upon each other, but as a network of postulates or arguments that you can basically kick a good number of legs out from under that table without knocking over the actual proof.

But then, it gets interesting because then, if you're using a network analysis, you can kind of figure out in the same way that you figure out who is the person capable of changing the cardinality of prayer, or, getting everyone out onto the dance floor. You know, you can identify what Bucky Fuller called the trim tabs, where are the points of leverage to think in Donella Meadows terms? So in passing, you mentioned in Waddington revisited that there are times when de-canalization occurs when the entrenchment, which like, you think about like a flood washing out a terrain and you lose the characteristics of memory as it's encoded in the landscape.

And I'd love to hear you talk a little bit about that and like the resetting of the plain table as it were.

Aviv Bergman (28m 54s): This touches a little bit about more recent work we have done with respect to the breakdown of robustness. When does robustness breaks? Now, there are two types of, there are many types of robustness, but the ones that we are focusing on, or we have focused in the latest work on was the link between all the decoupling between genetic robustness and environmental robustness. In a single cell organism it has been demonstrated that when you evolve genetic robustness as a side effect, you evolve in sensitivity to environmental variation and vice-a-versa, namely when you'll have an environment, a rule evolve, for instance, that insensitivity to environmental valuation as a side effect. You end up with insensitivity to genetic variation. And this gives kind of a question mark as to the evolution of multicellularity namely, how can sail that compose of the exact identical set of genes in every organs in our body end up with a differentiated in completely different cell type, having exactly the same genotype.

So we did a little bit of work on how to decouple genetic from environmental valuation. And we looked at a complex called the Polygon complex, which was discovered quite some time ago into a sofula, which is a mechanism by which you can quote unquote, think about it as a mechanism that dynamically carved the system during development.

And if a cell experience a particular environment during development before certaincritical time point a sale, that experience that specific environment will develop into a specific cell type one cell type while if it were to experience a different environmental condition, external environmental condition, the same cell with the same genotype, we'll end up with a very different phenotypic characteristics.

Now from there on those two different cell types will beget the same cell types again and again and again. So a skin cell will beget skin cell level cell would beget level cell and so on and so forth. Now imagine what happened if that Polygon mechanism that ensure the fidelity of the cell is broken to cell become juvenile, namely it is influenced by its neighbors, and it can assume all possible phenotypes that are imposed upon him as a condition of the environmental conditions.

So it is not flattening the map, but it rattles opening the possibility of tunneling practically and not to use physical term between phenotypes without the need to go back to a much primitive quote, unquote state like a stem cell state or pluripotent stem cell condition where the cell possesses in itself, the possibility of differentiate into all those possible genotypes.

So it is not flattening the map, but enabling the phenotypic landscape to be accessible from any point to any other point.

Michael Garfield (33m 0s): So correct me if I'm getting anything wrong in this, but again, you know, the someone broke the handle off on analogies. So first of all, there was a paper that came out a few years ago reported in Science Advances, but then in covered in Quanta and a few of our people, Jessica Flack and Albert Cowdry commented on this research led by Neil Johnson at George Washington University. The article was smarter parts, make collective systems too stubborn. And it was about this balance between the not smarter per se, but nodes in a network with a longer memory being resistant to the propagation of changes across the network.

And so there's a big conversation at SFI about the balance between biological inheritance and cultural inheritance and now that we live in this modern era, where culture seems to have taken over in some ways that this is where I worry I'm getting this wrong. It seems almost like there's a bias for each of us as individuals towards like amnesia.

The environment is changing much more rapidly because culture can propagate horizontally. It doesn't require an evolutionary timescale and the way that we are talking about this. And so you get people that are storing all of their memory outboard and you go to Google for everything. And so each of us as individuals that are depending more and more on the storage of memory in the environment are somehow losing our definition as people.

And there's all of these associated concerns about challenges to the accumulation of expertise. And I've know you've written on that, but I guess generally there's a sense in which, you know, throughout history people have been criticized for not having a kind of a core in different cultures, that they don't have a strong stable identity. And if you look at attachment traumas in human ego development, things that come from a very, very unreliable environment in early childhood, specifically that you get all of these sort of ego development disorders, people that in a way sound like the metastatic cells that you're talking about that change and they can move from one environment to the other, but then you don't actually have any sort of continuity of character from one setting to another.

Aviv Bergman (35m 37s): The latter examples that you gave is closer when it comes to culture. I think the gap between the genetic level of that I’m talking about in the cultural level that you have mentioned is similar to what Murray Gell-Mann, once whimsically said that if particles could think physics would have been by far more difficult. I would make the analogy of the genetic level to physics and the behavior level to biology.

But your point about losing the ability to commit to a particular phenotype as a mechanism that is somewhat broken, namely the commitment mechanism is broken is correct analogy.

Michael Garfield (36m 36s): So it's not the stem cell pluripotent thing, but there is something in that about the criticism of like people with a Peter Pan syndrome, people who refuse to settle down, who refuse to commit. And this is interesting because as pertains to comments about how all of this influences connectivity of regulatory networks, I think a lot about the work of people like Ricardo Hausmann at SFI, who are very strong proponents of a very, very mobile, global economic situation.

You know, lots of cultural interchange, lots of the migration, the reallocation of people, and know-how between nations. And I brought this up with him when he was recently on the show with Dwayne Farmer for the emergent political economies series that, you know, there's the, and yet, that we all experienced in the last few years with Covid and the fact that you get beyond a certain point and hyper-connectivity undermines everything.

So I'm curious about, again, like how this shapes your thinking on the upper and lower bounds of all of that.

Aviv Bergman (37m 47s): No, you're absolutely right. There is an upper bound to what a extreme connectivity can do to you, at least in biology. So as I was saying earlier the Polygon like mechanism is a mechanism by which the entirety of the gene regulatory network during development is carved into a small little segment shunting, certain part of the network from being active while activating others, depending on the mechanism of Polygon like commitment mechanism.

And when broken, all of a sudden the entirety of the network is capable of being interacting with one another. Making it possible, as I said, to assume all possible phenotypes. And this is how hypothesis of their transition, that cell that have been originated in one environment can go through multitude of foreign environment for, and to the origin, to the environment, but in which the cell was originated and steal not only survive, but when arriving at a secondary or tertiary site can thrive.

And I do not think that anybody in the audience who listen to that would think of cancer or metastatic cancer as a positive thing. So from the cell point of view, it is a positive thing, but from the organism of point of view, it is deleterious. It is very harmful to you.

Michael Garfield (39m 29s): So I'd like to raise an unpleasant inquiry, which kind of comes up on this show a lot ever since I saw John Pepper speak at SFI a few years ago on cancer and metabolism, and many, many people have drawn this correlation between the way that cancer is able to hack its way into acquiring additional resources from the body and its glucose intense metabolism with innovations in the origin of the modern human in cooking.

And then later in fossil fuels and so on and how every innovation we've had an energy technology and in the augmentation of our own metabolism has allowed us to spread over the surface of the planet and become this extreme, super invasive species and reshape everything, again, like to our own benefit, but again, to the increasing destabilization of our ecosystemic base. So again, do you think that first of all, is that just like justifiable and second of all, do you think that your work provides a kind of intuition or the possibility of steering research and understanding what the actual limits are to the degree, to which we can exploit ecological resources.

Aviv Bergman (40m 47s): As you said, this is an unpleasant fact on one hand, on the other hand, I would not dare to assume that my workj can be scaled to such a level. With that said do is yet another interesting observation, which is very much related to that, the fact that we have only one reward mechanism, which is dopamine. And if we get addicted to this energy consumption, we will have to deal with this process of suppressing the reward mechanism.

But this reward mechanism is extremely deleterious to us when we become addicted to whatever it is on one hand. On the other hand, it was evolution created, quote unquote, in order for us to survive. We need that mechanism to know when we all sell steel, when we need food, et cetera. So there is a very interesting balance between the misuse of one evolutionary process levels when we are abusing it.

But this is something that you can edit out.

Michael Garfield (42m 6s): I'll be editing a lot of my own stuff out of this. So in passing here, cause I, I do want to get to the work on the Albert Einstein Institute for Advanced Study in the Life Sciences, but on the way there, we were talking the other day at lunch and you brought up a paper that you wrote with Arturo Casadevall.

Aviv Bergman (42m 26s): He is now at a John Hopkins University.

Michael Garfield (42m 34s): So again, just to sort of like a loose analogy here in thinking on upper and lower bounds, the paper that you wrote together on mammalian endothermic and the trade-off between the metabolic trade-off going on there and you know, what you think. So could you give a little bit about just a little background on the, on this paper and the question that you're asking about the susceptibility of mammals to fungal infection.

Aviv Bergman (42m 59s): Oh, this is a very, very different topic, which at some point to approach me and says, asked me the following question is the fact that that between 27 degrees Celsius and 40 degrees Celsius, every one degree increase eliminates 6% of the fungal species and what it's relation to the fact that is this something that was a driving force for a mammalian hot bodies.

And if so, what would be the optimum temperatures that we will arrive at? So he introduced me to this question and it was a kind of something that bothered me for an afternoon. And so I decided to do the back of the envelope calculation. And if you take the benefit of reduction, the ratio between the reduction of the number of species of fungi that can infect you, can infect mammals relative to how costly it is to acquire that, eh, energy from Boltzmann type of calculation.

You take this ratio lo and behold, you get an optimum independent of body size, independent of the shape, et cetera. You end up with optimal mentality, 6.7 degree. So now this is kind of a very surprising and serendipitous result because we did not take into account all the effect of the immune system, et cetera. This is by far more, this process is by far more complex, but just to, as a really quick back of the envelope calculation to arrive at 36.7 degree was a result and it caught fire.

People got interested in, in this paper more than actually I believe not that it does not deserve, but the complexity of the processes by far more than we put into it.

Michael Garfield (45m 23s): Well, I mean, it certainly strikes me again, to reference Simon DeDeo and the conversation we had about the paper that he co-authored with, Zach Wojtowiczon how you have a balance in the sciences between people who are seeking the simplest most parsimonious explanation and the most conciliate or all encompassing explanation and how other people have pointed to this in terms of a sweet spot in modeling. It's the sweet spot between the amount of time that you spend gathering data or running your computations and the simplicity and elegance of a model.

Aviv Bergman (46m 6s): Your comment brings me back to what I said earlier about the inadvertent pass that Darwin put us on. It is not to discount the contribution that indeed by no means, eh, he was the one who actually recognized that. And he put that at the conclusion of the introduction of the first edition. And ever since that natural selection is only one of the processes that are involved in a generation of valuation and contributing to natural selection.

He wrote that the history of science will prove that the misrepresentation of his theory at that time is not going to be long. Then now it is about 163 years. And still people believe that natural selection is the one and only modes of modification and the powerful aspect of evolutionary biology, which I agree it is very powerful, but he inadvertently put us on the path where we are worshiping diversity on the experience of probing for commonalities.

And by that, I mean, if we take again, Stephen Jay Gould questions seriously, namely, if we were to play the tape again and again and again, what will remain in volume. This question actually is to a large extent, fall into biologists because biologists like to think about what are the differences between a potato and a tomato between case and control between disease and healthy, not knowing what's common.

And this is something which is need to be, we thought and arrived at something that may cause the tradition of biologist to think more like a physicist, to think about commonalities rather than the diversity. And it is actually a parent, not only in the way of thinking, but also in the technology which we are building.

We are building technology to look for gene differential expression, methylation, differential, expression, RNA differences, et cetera. It's all about the difference between a potato and a tomato, not about what comments between the two of them. So this kind of goes towards your argument.

Michael Garfield (48m 56s): And so at this point, sensitive to time, I want to bridge kind of a hail Mary pass. It's a long bridge, but I want to bridge into the vision statement that you circulated on the Albert Einstein Institute for Advanced Studies in the Life Sciences, where you are the guy in charge of this, this new place and the statement that you made in here, which I think folds everything that we've been discussing today into a bouquet.

You say science accepts rationality is the final judge of all alternatives. You mentioned that “Coon points out that even the most rigorous empiricism must rest on some basis that determines what counts as admissible evidence. There is no such thing as an undeniable reality, no way to get outside of one beliefs. The so-called common groundlessness is what makes the conflict between obedience and transgression a non-problem.” So, you know, in thinking about this, I've asked contrary to the rhetoric of people like Richard Dawkins to whom we much, I don't know, personally, if there really is quite the qualitative difference between religious fundamentalism and modern, empirical thinking in as much as both of them, ultimately default to something like a sacred text. The difference being that fundamentalists leap to consult the King James version or whatever.

Whereas when we run in the modern world, we run a scientific investigation. We default to the five senses in spite of the fact that we know there are more than five senses. And so again, we get to this question of the forces that govern a sweet spot. And that's where I felt like there was a connection between the paper that you wrote on endothermy and the resistance of a body to fungal infection with the resistance of an academic domain to infection, quote unquote, by some new idea.

So how much patience do we have for the expansion of our sacred texts with non-canonical additions? Anyway, that's an insane rant, but I think like this is my invitation to you to talk a little bit about the justification and the motivation for forming this Institute and what you're hoping to accomplish there.

Aviv Bergman (51m 21s): Before going there, there is a difference between religion and science in the following way. Not this time is not based on a wearable set of beliefs, but in religion, and in some aspect, for example, or philosophy, the closer you are to the origin, the better you are. The closer you are to this regional scripture, the more quote unquote, genuine you are. Science, even though it is based on set of beliefs, today's science or nature or cell or any journal’s paper can obviate, what's been done in the past and the set of beliefs are malleable.

And this is well changes of paradigms changes of the way of thinking, actually differentiate what we do in the scientific realm, as opposed to we, what we do in the religious realm. So this is the difference between the two, but on a daily basis, say a scientist is walking within a certain part day, the actual activity may look very much the same in terms of the practical activity of us scientist.

Now, the rational between creating this Institute for Advanced Studies into Life Science at Albert Einstein College of Medicine, which I have to give credit to the Dean that allow me to do something of that nature, which is fairly unique, not only among medical institution, which I am embedded within, but also in other academic institution is to allow it is to create a platform, to allow people to sit back and think about problems.

We still do not have tools to address though. There is a great field medalist, Terry Tao, who said in his blog, once that during the education process of him as imitation a person has to go through all three stages. Well, you have an intuition, you wave your hands, but this is well thinks, remains the rigorous stage. Well, you learn how to proof their rooms and the post rigorous stage where you'll go to the intuition. You wave your hands, knowing that you can fall back on the rigorous aspect and prove whatever intuition it is that we have life science for the most. While there are pockets here, and there it is pretty rigorous, which is not a bad thing to be at, but it is a place where tools that are not necessarily related to physics, mathematics, modeling, et cetera of computer science are helpful to the initial stages.

Other tools like generation of narrative, close readings, historicity that we acquire much longer gestation time to create. Prior to jumping into a development of this or the other mathematical tool diesel. The other model that is going to reflect the phenomenon that you have observed. These tools are tools that are foreign to most scientists. And these are the bread and butter of the humanist. So the idea behind the Institute is to bring together humanists artists and scientists, not in order to create science inspired art piece, but rather to bring beg the privilege that we, the scientists have deprived the humanities from. Pick their brain and learn from them, how actually they do their job when they analyze the text, when they analyze that historical event, when they read the poem. In order for us to look at the problems, the big problems that we have no tools to address as of yet to look through a very different lens, this might help us push the envelope towards the rigorous stage, where we will be able to potentially develop mathematical tool, new, physical tool, new modeling processes that will enable us to address those questions that cannot easily be addressed today.

And there are many problems that in life science, and when I say life science, I look at it really broadly. Now, cognitive science. Now cognition is part of that. Development is part of that and other aspects of life science issues that are not being addressed due to the fact that now everybody and our spouses are looking at the molecular level, not at the bigger picture are being neglected.

And the goal of the Institute is to bring these new methodologies to a scientific inquiry. And I hope to be able to attract philosophers, mathematicians, historians, architects, musicians, et cetera, to teach us how they think in order to push the envelope in areas that we are just having baby steps. It won't happen in my lifetime, but it is a worthwhile exercise to push the envelope here.

Michael Garfield (57m 36s): Well, I mean, I, I just think of episode 55, I had James Evans on talking about social computing and how he's seeks to use machine learning, to augment our ability to search the space of possible questions and identify unexplored areas between disciplines, where you can drop people that are naive to one another's expertise into the middle and explore these sort of blind spots that we don't recognize. I think again, there was talk about this on the show a lot just about how what you're getting at really connects that institute with this one.

And as much as fundamental research is historically immensely hard to fund because there's no obvious immediate benefit because the whole point is you're coming up with something new that's still a legible to the economy. It has no obvious return. And so again, you know, this question of, you know, yes, thank the Dean, for being willing to make a long bet on this stuff. Because as you point out in your writing on the goals of this institute, that so many of the, the major paradigm shifts of the past, including Newton's theory of gravity, Darwin's theory of evolution, Eistein's theory of relativity relied on thought experiments that may have initially appeared in your words, fanciful and imprecise.

And you know, so just, you know, we'll link to this in the show notes, 2022 SFI journalism fellow Dan Falk wrote a great piece on this a few years ago on thought experiments and how it's easy to mistake these as totally on empirical. But in fact, your ability to run these kinds of thought experiments depends on internalized models of the environment that have developed in you over evolutionary or what you call somatic time. That in a way it is actually a sort of deeper if less formal and in-precise kind of empiricism.

Aviv Bergman (59m 34s): No, it is. We tell ourselves narratives. So why don't we ask the professionals who create now at this fall, they'll leaving, teach us how to do that. And I think most of those paradigm shifts and major advances in science or kill first and foremost is started as a narrative, as a storytelling to oneself about what it is that they are looking at.

Michael Garfield (1h 0m 7s): So in your vision statement, you say as regards narrative that you want to offer a story about human beings alienated not from higher authority in the modern world, but from rather a meaningful and fulfilling relationship with community. And again, something that comes up on the show a lot is Wendy Carlin and Sam Bowles writing on how shocks to economies of scale and to the responsivity of the state, by things like Covid-19 seem to remove the oppressive superstructure of these enormous networks and allow the human scale to return, what they call the civil society, mutual aid networks, neighborhood organizations, and everything.

Suddenly we had externalized all of these things into the convenience of just depending on state authority or on market dynamics to solve these things for us. But that again, when we are challenged by a sudden uptick and environmental instability, that all of a sudden we remember why it is that we needed things like the family or the guild.

Aviv Bergman (1h 1m 18s): You are absolutely right. But again, I would not claim to stretch what it is that I'm doing to that level. What I was talking about in the vision statement with respect to going back to community is only within the academic environment. Now their academic environment does not exclude intellectuals that comes from outside of academia. I don't think that academia, as it is defined today is the right form of intellectual or even scientific activity.

We should include other communities like communities of writers, communities of poets, communities of musicians, communities of architects, communities of choreographers. These are the type of people that I think we as scientists can learn a lot from, in questions again, that we have not clue as to how even to begin address. And we have them.

Michael Garfield (1h 2m 26s): Does it perhaps a great place to tie a bow on this, which is in a statement that you make about the meta problems you want to examine what this institute you say “Currently, our politics are marked by a crisis of trust and scientific truth. We can begin to address such a crisis by clarifying our own understanding of what constitutes truth and admissible evidence and how to effectively and ethically communicate uncertainty.” And this is where I just want to nod and tip my hat to Stuart Firestein and the community lecture he just gave on what he sees as the virtues of uncertainty and the questions of how we can make more space for that. And as someone grew up in Israel and it was, surrounded by the sort of kibbizing, there's this ongoing rabbinical process of sense-making that goes very deep into history. I would just love to hear you speak for a moment on how you think about that and on the open questions and yeah, maybe we can just leave people with a big illustrated or illuminated embellished question mark.

Aviv Bergman (1h 3m 38s): This is a great challenge that you put in front of me. When we get, when scientists get their degree, what they get and not only scientists, when you arrive at a certain stage in your life, you'll get a license to ask a question, no matter how big the question is and to not know the answer to that question. Scientists should thrive on ambiguity and uncertainty.

Without it we are doing engineering, not that engineering is bad, but it's different from science. Science is an activity inherently that puts you in an ambiguous and in uncertain situation. You are looking in to pave a path that first and foremost, you do not know where it leads. And if you are even more daring not to follow a path that other have created, but to go to a completely uncharted area and to ask whatever big questions you are asking, you are interested in asking.

And I believe that this is not the characteristics of a scientist or a scientist alone. This should be the characteristics of every intellectual in our society to be not only comfortable, but thriving and seeking to be in ambiguous and uncertain situation. So if there will be a big question that I would like to ask is what would be the mechanism by which we change the views of our society, about what is the role of a scientist in the society and not necessarily to ask.

And when I say scientist, I include in it, all those adult disciplines that I have introduced in this Institute, musicians, et cetera. These are kind of scholars, the role of scholars in our society and what type of funding mechanism should be in place other than the standard mechanism that are currently driven by the political arena.

So in my view, what we need to create, and I do not know how to do that is to create the equivalent of a scientific French Revolution that will enable us to do things like what we are proposing without thinking that this is at the fringe of science, because this is that in my view, one of the only ways, and this is where Santa Fe Institute is really good at. This is the only way by which we will address the next generations official because past generations issues can be transferred into the engineering style stuff, can be passed into creating something which is beneficial to human being immediately.

The rest of our activities should focus on how to create what will be beneficial in the next decade, in the next millennium for your main condition.

Michael Garfield (1h 7m 51s): That would be a really potent place to end it but because you brought up the issue, I just have to UPenn on this. If you'll indulge me, because I've had this conversation with David Krakauer too, this is something that keeps me up at night. We talk about this in the Facebook group, actually quite a bit, or have this issue of funding and why it is that we run into these political issues and what, in spite of the spirit and the mission and identity of science, as you've articulated it here, as many have this issue of why certain questions are unfundable.

And it seems like it may have something to do with like the problem of prestige. Like if you think about Mirta Galesic in the conversation I had with her about the way that people can form their own voting intentions to match their compatibility with friends and family, so that people wanted to vote for, for instance, for Hillary Clinton in the 2016 election, until they realized that they would be ex-communicated from their family groups, if they didn't vote for Trump.

And so it seems like something, something similar goes on, the more beholden researchers or academic institutions are to the protection of their reputation. And so I'm curious what you think about the opportunity for pseudonymous and decentralized funding through stuff like, you know, there's this DSI movement going on and blockchain space now to offer people the opportunity to basically crowdfund innovative research without having their names attached to it.

And I'm wondering if you think that that's the kind of thing you're talking about here.

Aviv Bergman (1h 9m 34s): This is one possibility. The other possibility, which is even more feasible in the short term is the following observation. When I send a proposal to the NIH or NSF or wherever, it is evaluated by my peers, by the same scientists that I am communicating with on a regular basis outside of the funding institution.

But nevertheless, the system is such that those individuals who are in charge, myself included when I'm on study sections, et cetera, the system is such that it lowers the bar to the lowest common denominator, not allowing things that are outside of the current existing paradigm to be funded. So the NIH funds areas and proposals that for the most part they've already been done, and the certainty of success is really high.

There is very little mechanism by which you can submit a proposal where you do not have preliminary data that shows the results of what it is that you are going to investigate. And I think it is up to us, the people in the study section to create quote unquote, this scientific French revolution, and to change the criteria of what constitutes a valuable scientific inquiry.

The fact that what I ask has already been answered is not necessarily the criteria for the value. Even if that finding is really significant finding, now you can publish it, find something that you do not know the answer to.

Michael Garfield (1h 11m 41s): I mean, well, this gets to conversations like the one I've had with our fellow Cole Mathis about what it would take to stage a coordinated walkout on pay gated, peer reviewed journals. Something we talked about earlier in the conversation about we were thinking about canalization and the tension between individuals and institutions. Everyone may want this, but how do you actually like unionize, if this is the kind of thing you're talking about.

Aviv Bergman (1h 12m 10s): I do not have the answer to now earlier today or approached you and I told you, I am depressed. There was a reason for that. And this is one of the reasons talking about Jonah Ziman’s interactions with a reputable journal about a certain publication that regardless of the quality of the results, it is so far away from what is the current way of thinking about the problem that the reviewer will sometimes have no bandwidth on one hand and time to go deep enough in order to evaluate whether or not this is a valuable result.  It's very easy to dismiss something. It's not easy to take the time and invest in something you have no clue. At least initially prior to receiving the manuscript or receiving the proposal. The reward system reflects our values. And I think this is a big source sociological issue that I don't allow myself or I don't have the audacity to claim that I know how to solve, but I think it's worth thinking about, and if this, the uncertainty issue how to communicate is going to be part of my institute.

If we were to arrive at a baby, step it, addressing it. I will be thrilled.

Michael Garfield (1h 13m 60s): It certainly seems like “a horse, a horse, my kingdom for a horse.” How do we afford ourselves more time for these conversations? And at any rate I'm, I'm grateful that we've been afforded the time to have this one.

Aviv Bergman (1h 14m 14s): No, me too. A I'm really grateful to her, to you and to the Institute for her hosting me for the last six or seven months. It's been a pleasure of being here,

Michael Garfield (1h 14m 28s): Dude. Thank you so much for being on the show.

Aviv Bergman (1h 14m 30s): Thank you.

Michael Garfield (1h 14m 33s): Thank you for listening. Complexities produced by the Santa Fe Institute, a nonprofit hub for complex systems science located in the high desert of New Mexico. For more information, including transcripts research links and educational resources, or to support our science and communication efforts. Visit Santafe.edu/podcast.