Channel Title: Santa Fe Institute Channel Description: Our researchers endeavor to understand and unify the underlying, shared patterns in complex physical, biological, social, cultural, technological, and even possible astrobiological worlds. Our global research network of scholars spans borders, departments, and disciplines, unifying curious minds steeped in rigorous logical, mathematical, and computational reasoning. As we reveal the unseen mechanisms and processes that shape these evolving worlds, we seek to use this understanding to promote the well-being of humankind and of life on earth. Learn more at https://santafe.edu <video> From Proof of Work to Proof of Theorems Description: Simon DeDeo, Carnegie Mellon University, SFI The Bayesian Revolution of the last two decades has transformed cognitive science, enabling us to tie together a vast array of disparate phenomena under the rubric of evidence gathering in the face of uncertainty, in an elegant mathematical framework that just happens to connect to the technological advances in AI. It contains, however, a crucial gap: while it tells us how new experiences ought to change our beliefs, it gives us no systematic way to account for the mental load of actually doing so which means that our most crucial questions appear as ad hoc corrections. I ll present recent progress towards unification, which draws on foundational results and novel conjectures in computational complexity, cryptography, and formal theorem proving. Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video> <video> A Markov Chain Theory of Self Organization Description: Jacob Calvert, Georgia Tech University Fundamentals of statistical mechanics explain that systems in thermal equilibrium spend more time in states with greater order because these states have lesser energy. This explanation is remarkable, and powerful, because energy is a "local" property of states. Nonequilibrium systems, like living systems, can also exhibit order, but there is no property analogous to energy that generally explains why states with greater order tend to emerge. However, recent experiments suggest that a local property called rattling predicts which states are favored, at least for a broad class of nonequilibrium systems. In this seminar, I will present a simple theory of rattling that explains when and why it works, and I will demonstrate its application to systems across scientific domains. Surprisingly, the core idea of rattling is so general as to apply to equilibrium and nonequilibrium systems alike. (Joint work with Dana Randall.) Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video> <video> Nature of Intelligence, Episode 3: What kind of intelligence is an LLM? Description: Large language models, like ChatGPT and Claude, have remarkably coherent communication skills. Yet, what this says about their “intelligence” isn’t clear. Is it possible that they could arrive at the same level of intelligence as humans without taking the same evolutionary or learning path to get there? Or, if they’re not on a path to human-level intelligence, where are they now and where will they end up? In this episode, with guests Tomer Ullman and Murray Shanahan, we look at how large language models function and examine differing views on how sophisticated they are and where they might be going. Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video> <video> Nature of Intelligence, Ep. 6: AI’s changing seasons Description: In the final episode of the season, Abha sits down with Melanie to hear her perspective. They chat about Melanie’s career and research with Douglas Hofstadter, the author of Gödel, Escher, Bach. They also discuss her opinions on LLMs’ current capabilities, what she thinks of existential questions like the alignment problem, how sustainable the industry is, the difficulty of making claims about concepts like “intelligence” and “understanding,” and what she thinks future technological development should focus on. Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video> <video> Micro-crowdsourcing: How Swarming Bacteria Integrate Signals During Collective Migration Description: Karine A. Gibbs, University of California, Berkeley Collective behaviors, like those of ants, birds, and bacteria, inspire us with the promise of more immense achievements with fewer resources, and understanding these behaviors is vital in comprehending the world around us. Further, bacterial communities are dynamic societies where microbes communicate cooperatively and antagonistically with siblings and non-siblings. Individual bacteria must navigate the complexities of these interactions even as the whole population expands. In this seminar, I will discuss how bacteria use a local sense of identity to assemble and move as a community. Our model organism, Proteus mirabilis, lives in human and animal intestines and the environment and can cause disease after moving to the bladder. Individual cells move on the scale of micrometers per second; populations swarm on the order of millimeters per hour. Our data shows how P. mirabilis communicates identity between cells and how this identity-based signaling regulates cell development and population-wide swarming. Our research addresses how an organism's identity, communication, and local environment influence collective behaviors. Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video> <video> Nature of Intelligence, Episode 4: Babies vs Machines Description: There’s an argument to be made that if we train AI systems to learn the way babies do, we’ll get them closer to human-like intelligence. But how our own learning development functions in babyhood is still a mystery that researchers are untangling. We know that the information babies absorb is very different from how an LLM learns, and in today’s episode, with guests Linda Smith and Michael Frank we’ll attempt to look at the world through an infant’s eyes and examine why they’re able to do more with, seemingly, less information. Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video> <video> Competing Social Influence in Contested Diffusion: Contention and the Spread of Early Reformation Description: Steven Pfaff, Chapman University The spread of radical institutional change does not often result from one-sided pro-innovation influence; countervailing influence networks in support of the status quo can suppress adoption. We develop a model of multiplex and competing network diffusion to describe how rival actors compete through multiple types of networks. Specifically, we hypothesize three types of contested diffusion: market competition, inoculation, and firefighting. To apply the contested-diffusion model to real data, we look at the contest between Martin Luther and Desiderius Erasmus, the two most influential intellectuals of early 16th-century Europe. Whereas Luther championed a radical reform of the Western Church that broke with Rome, Erasmus opposed him, stressing the unity of the Church. In the early phase of the Reformation, these two figures utilized influence networks, affecting which cities in the Holy Roman Empire adopted reform. Using newly digitalized data on both leaders correspondence networks, their travels, the dispersion of their followers, and parallel processes of exchange among places through trade routes, we employ empirical tests of our theoretical model. We find that although Luther s network is strongly associated with the spread of the Reformation, Erasmus s network is associated with the stifling of the Reformation. This is consistent with a "firefighting" mechanism of contested diffusion, whereby the countervailing force suppresses innovations only after they have begun to spread. Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video> <video> Hidden Differences Subjective Experience and the (Dis)unity of Human Cognition Description: Gary Lupyan, University of Wisconsin, Madison Many differences among people are easy to observe. Others, such as those concerning the quality of one s subjective experiences, tend to remain hidden. As a result, we often tend to underestimate them, assuming that the subjective experiences of others mirror our own. For example, people who lack visual imagery, tend to assume that using the 'mind's eye' is just a figure of speech. I will give a brief overview of the search for these hidden differences a case of unknown unknowns and discuss some of their behavioral consequences and the ways they can act as stress tests for theories of cognition. I will also draw curious parallels between hidden differences in subjective experience and work on cryptic genetic variation. Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video> <video> Nature of Intelligence, Ep. 2: The relationship between language and thought Description: Complex language is unique to the human species. It’s part of how we evolved, the backbone of our societies, and one of the primary ways we judge others’ intellect. Is it our intelligence that leads to our language abilities, or conversely, does our ability for language enhance our intelligence, or both? How do language and thinking interact? And can one exist without the other? Guests: Evelina Federenko, Steve Piantadosi, and Gary Lupyan. Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video> <video> Real world Walk Processes on Networks Description: Carolina Mattsson, CENTAI Institute What do (association) football passes and financial transactions have in common? In both cases, the basis for record-keeping is that these events move something tangible from what we can call one node in a network to another. Ball sports and the circulation of money are two examples of walk processes found in the wild, and the notion of a real-world walk process helps to conceptualize, analyze, and model the corresponding systems. This talk will introduce this topic in general and then dive into specific analyses that turned out especially interesting: transforming passes into passing sequences uncovers intriguing dynamics of play, and tracing e-money across transactions lets us characterize usage patterns of mobile money and visualize e-money flows. Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video> <video> A Complex Return to Eden? Description: Penny Sackett, ANU Institute for Climate In the blink of a geological eye, self-christened Homo Sapiens has existentially fouled the life support system of the spaceship it shares with a dwindling number of extra-species co-inhabitants. As the anthroposphere transgresses Planetary Boundaries that have protected the rise of modern civilisations, humanity is shockingly close to losing agency over its future. Can complex systems science provide understanding of the anthroposphere-ecosphere interactions that have brought us to this brink? More crucially, can it assist us in stepping back from the abyss? This seminar will provide no answers to those questions. Rather, with an emphasis on anthropogenic climate disruption, this novice with a Beginner's Mind will explore with the audience whether the human interactions responsible for this planetary crisis can be modelled meaningfully using complex systems science. Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video> <video> Modeling Psychological Systems with Ternary Spin Models Description: Han van der Maas, University of Amsterdam, SFI In previous work in psychology, we have introduced network models as alternatives to traditional common cause models, such as the g-theory of general intelligence. For major depressive disorder and attitudinal change, we used variants of the Ising model, providing new explanations for phenomena such as sudden relapse and polarization. These theoretical insights were supported by extensive empirical research, demonstrating the successful application of network models to psychological data. However, the binary nature of the nodes in these models is a limitation, as many data sets include questions with a neutral or intermediate category (e.g., "don't know" or "not relevant"). In addition, the behavior of the Ising model is somewhat limited. Ternary spin models, such as the Blume-Capel model, offer a solution by introducing richer dynamics, including tricritical behavior, which is more consistent with various phenomena observed in clinical research, attitude studies, and intelligence research. We also discuss equivalence with existing statistical approaches (multidimensional nominal response model, IRT trees) for these data types. Finally, we present new R packages for fitting the Blume Capel model to psychological data. Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video> <video> Nature of Intelligence, Episode 5: How do we assess intelligence? Description: When it comes to assessing intelligence, people have all kinds of tests — the SAT, IQ tests, and so on. There’s controversy over how fairly these tests really measure human intelligence, but at the very least, we know that they correlate with some general reasoning skills when people take them. That assumption breaks down when we try to assess intelligence in non-humans. What does it mean when a large language model passes an intelligence test meant for humans? Does it actually have the same reasoning skills that a human does, or is it doing something else? In today’s episode, with guests Erica Cartmill and Ellie Pavlick, we investigate the best ways to assess intelligence in non-humans, whether animals or machines. Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video> <video> Complexity and Criticality of Geterogeneous or Anisotropic Spreading Models Description: Laurent Hébert-Dufresne, University of Vermont Models of how things spread often assume that transmission mechanisms are fixed over space and time. However, the transmission of infectious diseases can depend on local human behaviour or quality of the surrounding infrastructure. Likewise, social contagions like the spread of ideas, beliefs, and innovations depend on local norms or culture, and they can lose or gain in momentum as they spread. Diseases mutate and find subpopulations where they can thrive, just as ideas can get reinforced, beliefs strengthened, and products refined. We study the impacts of these mechanisms in spreading and cascade dynamics. Using different modelling tools, we find that complexity and criticality are the norm: Superlinear relationships between exposure and transmission can emerge from linear interactions and power-law distributions can be observed away from any critical point. Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video> <video> The Big Myth: How American Business Taught Us to Loathe Government and Love the Free Market Description: Naomi Oreskes, Harvard University Throughout the 19th century, the U.S. government played a major role in economic life, promoting economic development through infrastructure and education and regulating many markets. In the late century, Americans realized that an even larger hand was needed to address the failures of laissez-faire capitalism, from slavery and child labor to anti-union violence and monopolistic practices. But then something changed. Americans started to reject "big government" and to believe in the "magic of the marketplace." Why? How did so many Americans come to have so much faith in markets and so little faith in government? The short answer: a longue-durée propaganda campaign, organized by American business leaders. In the 1910s and '20s, businessmen bristled at efforts to make life better through government action, particularly regulation. Trade associations, wealthy powerbrokers, and media allies worked to build a new orthodoxy, insisting that government regulation was both economically unproductive and a threat to liberty. Before World War II, their efforts included initiatives to rewrite textbooks, re-shape and create academic curricula, combat unions, defend child labor, and fight the New Deal. After the war, they promoted the work of neoliberal economists Ludwig von Mises and Friedrich von Hayek, arranging for them to come to the United States and paying for them to teach at New York University and the University of Chicago. At Chicago, they supported "The Free Market Project," where George Stigler reframed Adam Smith as an anti-government extremist and Milton Friedman reframed Hayek for an American mass audience. They also worked to promote market fundamentalism in popular culture, through children s books, radio, film, and television, including a General Electric company -sponsored television show that beamed free-market doctrine (and the young Ronald Reagan) to millions, and launched Reagan s political career. By the 1980s, this crusade had succeeded. It was not merely that Reagan--with heavy support from General Electric and other American corporations had become President. It was that the ideology of "limited government" would define the next half-century across Republican and Democratic administrations, giving us a housing crisis, the opioid scourge, climate destruction, and a baleful response to the Covid-19 pandemic. Learn more, follow us on social media and check out our podcasts: https://linktr.ee/sfiscience </video>

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Our researchers endeavor to understand and unify the underlying, shared patterns in complex physical, biological, social, cultural, technological, and even possible astrobiological worlds. Our global research network of scholars spans borders, departments, and disciplines, unifying curious minds steeped in rigorous logical, mathematical, and computational reasoning. As we reveal the unseen mechanisms and processes that shape these evolving worlds, we seek to use this understanding to promote the well-being of humankind and of life on earth.

Learn more at https://santafe.edu

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