complexity by Santa Fe Institute

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Episode Title and Show Notes:

One way of looking at the world reveals it as an interference pattern of dynamic, ever-changing links — relationships that grow and break in nested groups of multilayer networks. Identity can be defined by informational exchange between one cluster of relationships and any other. A kind of music starts to make itself apparent in the avalanche of data and new analytical approaches that a century of innovation has availed us. But just as with new music genres, it requires a trained ear to attune to unfamiliar order…what can we learn from network science and related general, abstract mathematical approaches to discovering this order in a flood of numbers?

For centuries, Medieval life in Europe meant a world determined and prescribed by church and royalty. The social sphere was very much a pyramid, and everybody had to answer to and fit within the schemes of those on top. And then, on wings of reason, Modern selves emerged to scrutinize these systems and at great cost swap them for others that more evenly distribute power and authority. Cosmic forces preordained one’s role within a transcendental order…but then, across quick decades of upheaval, philosophy and politics started celebrating self-determination and free will. Art and science blossomed as they wove together. Nothing was ever the same.

How do we get a handle on complex systems thinking? What are the implications of this science for philosophy, and where does philosophical tradition foreshadow findings from the scientific frontier?

And now for something completely different!  Last October, The Santa Fe Institute held its third InterPlanetary Festival at SITE Santa Fe, celebrating the immensely long time horizon, deep scientific and philosophical questions, psychological challenges, and engineering problems involved in humankind’s Great Work to extend its understanding and presence into outer space. For our third edition, we turned our attention to visionary projects living generations will likely not live to see completed — interstellar travel, off-world cities, radical new ways of understanding spacetime — as an invitation to engage in science as not merely interesting but deeply fun. For our first panel, we decided to inquire: What is time, really? How has science fiction changed  the way we track and measure, speak about, and live in time? And how do physics and complex systems science pose and answer these most fundamental questions?

There are maps, and there are territories, and humans frequently confuse the two. No matter how insistently this point has been made by cognitive neuroscience, epistemology, economics, and a score of other disciplines, one common human error is to act as if we know what we should measure, and that what we measure is what matters. But what we value doesn’t even always have a metric. And even reasonable proxies can distort our understanding of and behavior in the world we want to navigate. Even carefully collected biometric data can occlude the other factors that determine health, or can oversimplify a nuanced conversation on the plural and contextual dimensions of health, transforming goals like functional fitness into something easier to quantify but far less useful. This philosophical conundrum magnifies when we consider governance at scales beyond those at which Homo sapiens evolved to grasp intuitively: What should we count to wisely operate a nation-state? How do we practice social science in a way that can inform new, smarter species of   political economy? And how can we escape the seductive but false clarity of systems that rain information but do not enhance collective wisdom?

This is a podcast by and for the curious — and yet, in over three years, we have pointed curiosity at nearly every topic but itself. What is it, anyway? Are there worse and better frames for understanding how desire and wonder, exploration and discovery play out in both the brain and in society? How is scientific research like an amble through the woods? What juicy insights bubble up where neuroscientists, historians, philosophers, and mathematicians meet to answer questions like these? And how long of a path must we traverse to get there?

Humans have an unusually long childhood — and an unusually long elderhood past the age of reproductive activity. Why do we spend so much time playing and exploring, caregiving and reflecting, learning and transmitting? What were the evolutionary circumstances that led to our unique life history among the primates? What use is the undisciplined child brain with its tendencies to drift, scatter, and explore in a world that adults understand in such very different terms? And what can we transpose from the study of human cognition as a developmental, stage-      wise process to the refinement and application of machine learning technologies?

What does it mean to think? What are the traits of thinking systems that we could use to identify them? Different environmental variables call for different strategies in individual and collective cognition — what defines the threshold at which so-called “solid” brains transition into “liquids”? And how might we apply these and related lessons from ecology and evolution to help steward a diverse and thriving future with technology, and keep the biosphere afloat?

In his foundational 1972 paper “More Is Different,” physicist Phil Anderson made the case that reducing the objects of scientific study to their smallest components does not allow researchers to predict the behaviors of those systems upon reconstruction. Another way of putting this is that different disciplines reveal different truths at different scales. Contrary to long-held convictions that there would one day be one great unifying theory to explain it all, fundamental research in this century looks more like a bouquet of complementary approaches. This pluralistic thinking hearkens back to the work of 19th century psychologist William James and looks forward into the growing popularity of evidence-based approaches that cultivate diversity in team-building, governance, and ecological systems. Context-dependent theory and practice calls for choirs of voices…so how do we encourage this? New systems must emerge to handle the complexity of digital society…what might they look like?

What makes us human?  Over the last several decades, the once-vast island of human exceptionalism has lost significant ground to wave upon wave of research revealing cognition, emotion, problem-solving, and tool-use in other organisms. But there remains a clear sense that humans stand apart — evidenced by our unique capacity to overrun the planet and remake it in our image. What is unique about the human mind, and how might we engage this question rigorously through the lens of neuroscience? How are our gifts of simulation and imagination different from those of other animals? And what, if anything, can we know of the “curiosity” of even larger systems in which we’re embedded — the social superorganisms, ecosystems, technospheres within which we exist like neurons in the brain?

The brain is arguably one of the most complex objects known to science. How best to understand it? That is a trick question: brains are organized at many levels and attempts to grasp them all through one approach — be it micro, macro, anatomical, behavioral — are destined to leave out crucial insights. What more, thinking “vertically” across scales, one might miss important angles from another discipline along the “horizontal” axis. For inquiries too big to sit within one field of knowledge, maybe it is time we resurrected the salon: a mode of scientific exploration that levels hierarchies of expertise and optimizes for more complementary and high-dimensional, egalitarian, communal discourse. As with the Jainist philosophic principle anekantavada — how many blind people does it take to grok an elephant? — neuroscience is perhaps best practiced as innately and intensely multiperspectival…

Communication is a physical process. It’s common sense that sending and receiving intelligible messages takes work…but how much work? The question of the relationship between energy, information, and matter is one of the deepest known to science. There appear to be limits to the rate at which communication between two systems can happen…but the search for a fundamental relationship between speed, error, and energy (among other things) promises insights far deeper than merely whether we can keep making faster internet devices. Strap in (and consider slowing down) for a broad and deep discussion on the bounds within which our entire universe must play…

What does it mean to be alive? Our origins are the horizon of our understanding, and as with the physical horizon, our approach brings us no closer. The more we learn, the more mysterious it all becomes. What if we’re asking the wrong questions? Maybe life did not begin at all, but rather coalesced piecemeal, a set of properties contingent and convergent, plural, more than once? Maybe the origin of life is happening right now, just over the horizon, forming something new anew. Let’s get into the weeds and see if we can find a continuity between biology and physics.

One way to frame the science of complexity is as a revelation of the hidden order under seemingly separate phenomena — a teasing-out of music from the noise of history and nature. This effort follows centuries of work to find the rules that structure language, music, and society. How strictly analogous are the patterns governing a symphony and those that describe a social transformation? Math and music are old friends, but new statistical and computational techniques afford the possibility of going even deeper. What fundamental insights — and what sounds — emerge by bringing physicists, composers, social scientists, data artists, and biologists together?

As the old nut goes, “To the victor goes the spoils.” But if each round of play consolidates the spoils into fewer hands, eventually it comes to pass that wealthy special interests twist the rules so much it undermines the game itself. When economic power overtakes the processes of democratic governance, growth stagnates, and the rift between the rich and poor becomes abyssal. Desperate times and desperate measures jeopardize the fabric of society. How might nonpartisan approaches to this wicked problem help us walk the system back into a healthy balance?

Chances are you’re listening to this on an advanced computer that fits in your pocket, but is really just one tentacle tip of a giant, planet-spanning architecture for the gathering and processing of data. A common sentiment among the smartphone-enabled human population is that we not only don’t own our data, but our data owns us — or, at least, the pressure of responsibility to keep providing data to the Internet and its devices (and the wider project of human knowledge construction) implicates us in the evolution of a vast, mysterious, largely ineffable self-organizing system that has grabbed the reins of our economies and cultures. This is, in some sense, hardly new: since humankind first started writing down our memories to pass them down through time, we have participated in the “dataome” — a structure and a process that transcends, and transforms, our individuality. Fast-forward to the modern era, when the rapidly-evolving aggregation of all human knowledge tips the scales in favor of the dataome’s emergent agency and its demands on us…

Human beings are distinctly weird. We live for a very long time after we stop reproducing, move completely differently than all of our closest relatives, lack the power of chimpanzees and other primates but completely outdo most other terrestrial mammals in a contest of endurance. If we think about bodies as hypotheses about the stable features of their ancestral environments, what do the features of our unusual physiology say about what humans ARE, where we come from, the details of our origin story as a profoundly successful species? And what can we learn by telescoping that story forward to explain some of the most persistent puzzles and paradoxes about our health, the way we age, our need for physical exercise, and our nearly ubiquitous aversion to habits that are good for us?

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?

What is life, and where does it come from? These are two of the deepest, most vexing, and persistent questions in science, and their enduring mystery and allure is complicated by the fact that scientists approach them from a myriad of different angles, hard to reconcile. Whatever else one might identify as universal features of all living systems, most scholars would agree life is a physical phenomenon unfolding in time. And yet current physics is notorious for its inadequacy with respect to time. Life appears to hinge on information transfer — but, again, what do we mean by “information,” and what it is relationship to energy and matter? If humankind can’t settle fundamental issues with these theoretical investigations, we might be missing other kinds of life (and mind) — not just in outer space, but here on Earth, right beneath our noses. But new models that suggest a vastly wider definition of life offer hope that we might — soon! — not only learn to recognize the biospheres and technospheres of other living worlds, but notice other “aliens” at home, and even find our place amidst a living cosmos.

Math and music share their mystery and magic. Three notes, played together, make a chord whose properties could not be predicted from those of the separate notes. In the West, music theory and mathematics have common origins and a rich history of shaping and informing one another’s field of inquiry. And, curiously, Western composition has evolved over several hundred years in much the same way economies and agents in long-running simulations have: becoming measurably more complex; encoding more and more environmental structure. (But then, sometimes collapses happen, and everything gets simpler.) Music theorists, like the alchemists that came before them, are engaged in a centuries-long project of deciphering the invisible geometry of these relationships. What is the hidden grammar that connects The Beatles to Johann Sebastian Bach — and how similar is it to the hidden order disclosed by complex systems science? In other words, what makes for “good” music, and what does it have to do with the coherence of the natural world?

We lead our lives largely unaware of the immense effort required to support them. All of us grew up inside the so-called “Grid” — actually one of many interconnected regional power grids that electrify our modern world. The physical infrastructure and the regulatory intricacies required to keep the lights on: both have grown organically, piecemeal, in complex networks that nobody seems to fully understand. And yet, we must. Compared to life 150 years ago, we are all utterly dependent on the power grid, and learning how it operates — how tiny failures cause cascading crises, and how tense webs of collaborators make decisions on the way that electricity is priced and served — matters now more than ever.

As our world knits together, economic interdependencies change in both shape and nature. Supply chains, finance, labor, technological innovation, and geography interact in puzzling nonlinear ways. Can we step back far enough and see clearly enough to make sense of these interactions? Can we map the landscape of capability across scales? And what insights emerge by layering networks of people, firms, states, markets, regions? We’re all riding a bucking horse; what questions can we ask to make sure that we can stay in the saddle?

In the digital era, data is practically the air we breathe. So why does everybody treat it like a product to be hoarded and sold at profit? How would our world change if Big Tech operated on assumptions and incentives more aligned with the needs of a healthy society? Are more data — or are bigger models — really better? As human beings scamper around like prehistoric mammals under the proverbial feet of the new enormous digital monopolies that have emerged due to the Web’s economies of scale, how might we tip the scales back to a world governed wisely by human judgment and networks of trust? Would Facebook and Twitter be more beneficial for society if they were public services like the BBC? And how do we settle on the social norms that help ensure the ethical deployment of A.I.? These and many other questions grow from the boundary-challenging developments of rapid innovation that define our century — a world in which the familiar dyads of state and market, public and private, individual and institutional are all called into question.

The world is unfair — but how much of that unfairness is inevitable, and how much is just contingency? After centuries of efforts to arrive at formal theories of history, society, and economics, most of us still believe and act on what amounts to myth. Our predecessors can’t be faulted for their lack of data, but in 2022 we have superior resources we’re only starting to appreciate and use. In honor of the Santa Fe Institute’s new role as the hub of an international research network exploring Emergent Political Economies, we dedicate this new sub-series of Complexity Podcast to conversations on money, power, governance, and justice. Subscribe for a new stream of dialogues and trialogues between SFI’s own diverse scholastic community and other acclaimed political economists, historians, and authors of speculative fiction.

Context is king: whether in language, ecology, culture, history, economics, or chemistry. One of the core teachings of complexity science is that nothing exists in isolation — especially when it comes to systems in which learning, memory, or emergent behaviors play a part. Even though this (paradoxically) limits the universality of scientific claims, it also lets us draw analogies between the context-dependency of one phenomenon and others: how protein folding shapes HIV evolution is meaningfully like the way that growing up in a specific neighborhood shapes educational and economic opportunity; the paths through a space of all possible four-letter words are constrained in ways very similar to how interactions between microbes impact gut health; how we make sense both depends on how we’ve learned and places bounds on what we’re capable of seeing.

As fictional Santa Fe Institute chaos mathematician Ian Malcolm famously put it, “Life finds a way” — and this is perhaps nowhere better demonstrated than by roots: seeking out every opportunity, improving in their ability to access and harness nutrients as they’ve evolved over the last 400 million years. Roots also exemplify another maxim for living systems: “What doesn’t kill you makes you stronger.” As the Earth’s climate has transformed, the plants and fungi have transformed along with it, reaching into harsh and unstable environments and proving themselves in a crucible of evolutionary innovation that has reshaped the biosphere. Dig deep enough and you’ll find that life, like roots, trends toward the ever-finer, more adaptable, more intertwined…we all live in and on Charles Darwin’s “tangled bank”, whether we recognize it in our farms, our markets, or our minds.

Autonomous vehicles hardly live up to their name. The goal of true “driverlessness” was originally hyped in the 1930s but keeps getting kicked further and further into the future as the true complexity of driving comes into ever-sharper and more daunting focus. In 2022, even the most capable robotic cars aren’t self-determining agents but linked into swarms and acting as the tips of a vast and hidden web of design, programming, legislation, and commercial interest. Infrastructure is more than the streets and signs but includes licensing requirements, road rules, principles of product liability, and many other features that form the landscape to which driverless cars continue to adapt, and which they will increasingly alter.

Irrespective of your values, if you’re listening to this, you live in a pecking order. Dominance hierarchies, as they’re called by animal behaviorists, define the lives of social creatures. The society itself is a kind of individual that gathers information and adapts to its surroundings by encoding stable environmental features in the power relationships between its members. But what works for the society at large often results in violence and inequity for its members; as the founder of this field of research put it, “A grave seriousness lies over the chicken yard.” Over the last hundred years, the science of dominance hierarchies has bloomed faster than a saloon brawl — branching out for deeper understanding of the lives of everything from fish to insects, apes to parakeets. Today, amidst clashing national and corporate titans, systemic economic inequality, and legitimacy crises in the institutions that once served to maintain (admittedly unfair) order, the time is ripe to turn to and learn from what science has discovered about the fundamental mechanisms that underly both human nature and the rest of it: who loses and who wins, and why, and at what cost?

As a careful study of the world, science is reflective and reactive — it constrains our flights of fancy, anchors us in hard-won fact. By contrast, science fiction is a speculative world-building exercise that guides imagination and foresight by marrying the known with the unknown. The field is vast; some sci-fi writers pay less tribute to the line between the possible and the impossible. Others, though, adopt a far more sober tactic and write “hard” sci fi that does its best to stay within the limits of our current paradigm while rooting visions of the future that can grow beyond and beckon us into a bigger, more adventurous reality.

COVID has exposed and possibly amplified the polarization of society. What can we learn from taking a multiscale approach to crisis response? There are latencies in economies of scale, inequality of access and supply chain problems. The virus evolves faster than peer review. Science is politicized. But thinking across scales offers answers, insights, better questions…

Some people say we’re all in the same boat; others say no, but we’re all in the same storm. Wherever you choose to focus the granularity of your inquiry, one thing is certain: we are all embedded in, acting on, and being acted upon by the same nested networks. Our fates are intertwined, but our destinies diverge like weather forecasts, hingeing on small variations in contingency: the circumstances of our birth, the changing contexts of our lives. Seen through a complex systems science lens, the problem of unfairness — in economic opportunity, in health care access, in susceptibility to a pandemic — stays wicked. But the insights therein could steer society toward a much better future, or at least help mitigate the worst of what we’re left to deal with now. This is where the rubber meets the road — where quantitative models of the lung could inform economic policy, and research into how we make decisions influences who survives the complex crises of this decade.

If you’re honest with yourself, you’re likely asking of the last two years: What happened? The COVID-19 pandemic is a prism through which our stories and predictions have refracted…or perhaps it’s a kaleidoscope, through which we can infer relationships and causes, but the pieces all keep shifting. One way to think about humankind’s response to COVID is as a collision between predictive power and understanding, highlighting how far the evolution of our comprehension has trailed behind the evolution of our tools. Another way of looking at it is in terms of bottlenecks and reservoirs — whether it’s N95 mask distribution, log-jammed shipping lanes, or everybody looking up to Tony Fauci, superspreader events or narrative rupture, COVID is a global crash course in how things flow through networks. Ultimately, the effects go even deeper: How has COVID changed our understanding of individuality — the self and its relationship to other selves?

Democracy is a quintessential complex system: citizens’ decisions shape each other’s in nonlinear and often unpredictable ways; the emergent institutions exert top-down regulation on the individuals and orgs that live together in a polity; feedback loops and tipping points abound. And so perhaps it comes as no surprise in our times of turbulence and risk that democratic processes are under extraordinary pressure from the unanticipated influences of digital communications media, rapidly evolving economic forces, and the algorithms we’ve let loose into society.

What makes a satisfying explanation? Understanding and prediction are two different goals at odds with one another — think fundamental physics versus artificial neural networks — and even what defines a “simple” explanation varies from one person to another. Held in a kind of ecosystemic balance, these diverse approaches to seeking knowledge keep each other honest…but the use of one kind of knowledge to the exclusion of all others leads to disastrous results. And in the 21st Century, the difference between good and bad explanations determines how society adapts as rapid change transforms the world most people took for granted — and sends humankind into the epistemic wilds  to find new stories that will help us navigate this brave new world.

Where does cultural innovation come from? Histories often simplify the complex, shared work of creation into tales of Great Men and their visionary genius — but ideas have precedents, and moments, and it takes two different kinds of person to have and to hype them. The popularity of “influencers” past and present obscures the collaborative social processes by which ideas are born and spread. What can new tools for the study of historical literature tell us about how languages evolve…and what might a formal understanding of innovation change about the ways we work together?

When British scientist and novelist C.P. Snow described the sciences and humanities as “two cultures” in 1959, it wasn’t a statement of what could or should be, but a lament over the sorry state of western society’s fractured intellectual life. Over sixty years later the costs of this fragmentation are even more pronounced and dangerous. But advances in computing now make it possible for historians and engineers to speak in one another’s languages, catalyzing novel insights in each other’s home domains. And doing so, the academics working at these intersections have illuminated hidden veins in history: the unsung influence and cultural significance of those who didn’t write the victors’ stories. Their lives and work come into focus when we view them with the aid of analytic tools, which change our understanding of the stories we’ve inherited and the shape of power in our institutions. One strain of the digital humanities called data feminism helps bring much-needed rigor to textual study at the same time it reintroduces something crucial to a deeper reconciliation of the disciplines: a human “who” and “how” to complement the “what” we have inherited as fact.

Can you write a novel using only nouns? Well, maybe…but it won’t be very good, nor easy, nor will it tell a story. Verbs link events, allow for narrative, communicate becoming. So why, in telling stories of our economic lives, have people settled into using algebraic theory ill-suited to the task of capturing the fundamentally uncertain, open and evolving processes of innovation and exchange?

What is the economy?  People used to tell stories about the exchange of goods and services in terms of flows and processes — but over the last few hundred years, economic theory veered toward measuring discrete amounts of objects.  Why?  The change has less to do with the objective nature of economies and more to do with what tools theorists had available.  And scientific instruments — be they material technologies or concepts — don’t just make new things visible, but also hide things in new blind spots.  For instance, algebra does very well with ratios and quantities…but fails to properly address what markets do: how innovation works, where value comes from, and how economic actors navigate (and change) a fundamentally uncertain shifting landscape.  With the advent of computers, new opportunities emerge to study that which cannot be contained in an equation. Using algorithms, scientists can formalize complex behaviors – and thinking economics in both nouns and verbs provides a more complete and useful stereoscopic view of what we are and do.

Whether in an ecosystem, an economy, a jazz ensemble, or a lone scholar thinking through a problem, critical transitions — breakdowns and breakthroughs — appear to follow universal patterns. Creative leaps that take place in how mathematicians “think out loud” with body, chalk, and board look much like changes in the movement through “music-space” traced by groups of improvisers. Society itself appears to have an “aha moment” when a meme goes viral or a new word emerges in the popular vocabulary. How do collectives at all scales — be they neurons, research groups, or a society at large — suddenly change shape…and what early warning signs portend a pending bolt of inspiration?

We are all investors: we all make choices, all the time, about our allocation of time, calories, attention… Even our bodies, our behavior and anatomy, represent investment in specific strategies for navigating an evolving world. And yet most people treat the world of finance as if it is somehow separate from the rest of life — including people who design the tools of finance, or who come up with economic theories. Many of the human world’s problems can be traced back to this fundamental error, and, by extension, many of the problems we create for other life-forms on this planet. What changes when we take the time to pause, and listen, and reflect on how the biosphere already works? How do we balance innovation with sustainability, or growth with resource distribution? Could a careful study of nature not only lead to better business outcomes but also help us heal the living world?

The popular conception of ants is that “anatomy is destiny”: an ant’s body type determines its role in the colony, for once and ever. But this is not the case; rather than forming rigid castes, ants act like a distributed computer in which tasks are re-allocated as the situation changes. “Division of labor” implies a constant “assembly line” environment, not fluid adaptation to evolving conditions. But ants do not just “graduate” from one task to another as they age; they pivot to accept the work required by their colony in any given moment. In this “agile” and dynamic process, ants act more like verbs than nouns — light on specialization and identity, heavy on collaboration and responsiveness. 

Seventy thousand years ago, humans migrated on foot across the ancient continent of Sahul — the landmass that has since split up into  Australia and New Guinea. Mapping the journeys of these ancient voyagers is no small task: previous efforts to understand prehistoric migrations relied on coarse estimates based on genomic studies or on spotty records of recovered artifacts.

This week we conclude our two-part discussion with ecologist Mark Ritchie of Syracuse University on how he and his SFI collaborators are starting to rethink the intersections of thermodynamics and biology to better fit our scientific models to the patterns we observe in nature. Most of what we know about the enzymatic processes of plant and animal metabolisms comes from test tube experiments, not studies in the context of a living organism. What changes when we zoom out and think about life’s manufacturing and distribution in situ?

Deep inside your cells, the chemistry of life is hard at work to make the raw materials and channel the energy required for growth, maintenance, and reproduction. Few systems are as intricate or as mysterious. For this reason, how a cell does what it does remains a frontier for research — and, consequently, theory often grows unchecked by solid data. Most of what we know about the enzymatic processes of plant and animal metabolisms comes from test tube experiments, not studies in the context of a living organism. How much has this necessarily reductionist approach misled us, and what changes when we zoom out and think about life’s manufacturing and distribution in situ?

The 19th Century saw many transformations: the origins of ecology and modern climatology, new unifying theories of the living world, the first Big Science projects, revolutions in the Spanish colonies, new information systems for the storage and representation of data… Many of these can be traced back to the influence of one singular explorer, Alexander von Humboldt. Humboldt was one of the last true polymathic individuals in whom the sum of human knowledge could be seated. As the known world grew, he leaned increasingly upon the work and minds of his collaborators — a kind of human bridge between the age of solitary pioneers before him and the age of international, interdisciplinary research he helped usher into being.

When you hear the word “nature,” what comes to mind? Chances are, if you are listening to this in the 21st Century, the image is one of a vast, interconnected, living network — one in which you and your fellow human beings play a complicated part. And yet, this is a relatively recent way of thinking for the modern West. It takes a special kind of thinker — and a special kind of life — to find and recognize the patterns that connect different environments around the planet. Until the pioneering research of 19th-Century explorer Alexander von Humboldt, no one had ever noticed global similarities between the climates and creatures at a given altitude, on different continents. His legendary work popularized not only a new portrait of the world and its complex inter-relatedness, but innovated vastly influential ways of doing and communicating science — including novel data visualization and interdisciplinary international collaboration methods. 

Complexity is all around us: in the paths we walk through pathless woods, the strategies we use to park our cars, the dynamics of an elevator as it cycles up and down a building. Zoom out far enough and the phenomena of everyday existence start revealing hidden links, suggesting underlying universal patterns. At great theoretic heights, it all yields to statistical analysis: winning streaks and traffic jams, card games and elevators. Boiling down complicated real-world situations into elegant toy models, physicists derive mathematical descriptions that transcend mundane particulars — helping us see daily life with fresh new eyes.

“More than the sum of its parts” is practically the slogan of systems thinking. One canonical example is a beehive: individually, a honeybee is not that clever, but together they can function like shapeshifting metamaterials or mesh networks — some of humankind’s most sophisticated innovations. Emergent collective behavior is common in the insect world — and not just among superstar collaborators like bees, ants, and termites. One firefly, alone, blinks randomly; together, fireflies effect an awe-inspiring synchrony in large, coordinated light shows scientists are only starting to explain. It turns out that diversity is key, even in a swarm; variety improves the “computations” that these swarms perform as they adapt to their surroundings. Watch them self-organize for long enough and you might ask, “Is this what people do? What hidden patterns and emergent genius do we all participate in unawares?” If bees and fireflies inspire that kind of question in you, you’ll find yourself at home in this week’s episode…

Human relationships are often described in the language of “chemistry” — does that make the beliefs and attitudes of individuals a kind of “physics”? It is, at least, a fascinating avenue of inquiry. In particular, the field of statistical mechanics offers potent tools for understanding how exactly people form their views and change their minds. From this perspective, everyone is a dynamic network of opinions and values, in a tense and ever-changing balance both with others and ourselves. The “chemistry” of social life, then, arises from multilevel interactions in our noisy minds and how they influence each other.

Once upon a time at UC Santa Cruz, a group of renegade grad students started mixing physics with math and computers, determined to discover underlying patterns in the seeming-randomness of systems like the weather and roulette. Their research led to major insights in the emerging field of chaos theory, and eventually to the new discipline of complexity economics — which brings models from ecology and physics, cognitive science and biology together to improve our understanding of how value flows through networks, how people make decisions, and how new technologies evolve. As the human world weaves new global economic systems and sustainability looms ever-larger in importance, it is finally time to heed the warnings — and the promises — of this new paradigm of economics.

In the 21st Century, science is a team sport played by humans and computers, both. Social science in particular is in the midst of a transition from the qualitative study of small groups of people to the quantitative and computer-aided study of enormous data sets created by the interactions of machines and people. In this new ecology, wanting AI to act human makes no sense, but growing “alien” intelligences offers useful difference — and human beings find ourselves empowered to identify new questions no one thought to ask. We can direct our scientific inquiry into the blind spots that our algorithms find for us, and optimize for teams diverse enough to answer them. The cost is the conceit that complex systems can be fully understood and thus controlled — and this demands we move into a paradigm of care for both the artificial Others we create and human Others we engage as partners in discovery. This is the dawn of Social Computing: an age of daunting risks and dazzling rewards that promises to challenge what we think we know about what can be known, and how…

Art history is a lot like archaeology — we here in the present day get artifacts and records, but the gaps between them are enormous, and the questions that they beg loom large. Historians need to be able to investigate and interpret, to unpack the meanings and the methods of a given work of art — but even for the best, the act of reconstruction is a trying test. Can we program computers to decipher the backstory of a painting — analyzing light and shadow to guess at how a piece was made? And, even more ambitiously, can AI learn to see and tell the stories rendered in an image’s symbolic content? Recent innovations yield surprising insights and suggest a cyborg future for art scholarship, in which we teach machines to not just recognize a set of objects, but to grok their context and relationships — shining light on messages and narratives once lost to time, and deepening our study of the world of signs.

The consequence of living in a complex world: one tiny tweak can lead to massive transformation. Set the stage a slightly different way, and the entire play might unfold differently. This path-dependency shows up in both the science fiction premise and the hypothesis of scientific research: What can we learn about the hidden order of our cosmos by adjusting just a single variable?

Most maps of the world render landscapes in 2D — yet wherever we observe ecosystems, they stratify into a third dimension. The same geometries that describe the dizzying diversity of species in the canopies of forests also govern life in other  living systems, from the oceans to the linings of our mouths. Behind the many forms, a hidden order shapes how organisms live in and on each other — and this emerging discipline of “canopy biology”  may yield important insights into modern urban life. Human societies, like gigantic swarms of ants, are elaborately coordinated super-organisms. In these enormous in-groups, one key feature is the anonymity of members. By studying a treetop world where organisms never see the ground that humans take for granted, structural ecologists glean lessons for the denizens of concrete jungles.

It’s tempting to believe that people can outsource decisions to machines — that algorithms are objective, and it’s easier and fairer to dump the burden on them. But convenience conceals the complicated truth: when lives are made or broken by AI, we need transparency about the way we ask computers questions, and we need to understand what kinds of problems they’re not suited for. Sometimes we may be using the wrong models, and sometimes even great models fail when fed sparse or noisy data. Applying physics insights to the practical concerns of what an algorithm can and cannot do, scientists find points at which questions suddenly become unanswerable. Even with access to great data, not everything’s an optimization problem: there may be more than one right answer. Ultimately, it is crucial that we understand the limits of the technology we leverage to help us navigate our complex world — and the values that (often invisibly) determine how we use it.

COVID-19 hasn’t just disrupted the “normal” of everyone’s social practices in what we take for granted as “daily life.” The pandemic has also, more granularly, changed the way scientists research and publish; it has changed the way science interfaces with institutions as varied as local governments and cell phone companies; it has changed the way we host and produce this podcast. This episode, for instance, with SFI External Professor Sam Scarpino and Resident Professor Michael Lachmann was recorded live over a year-end Donor Appreciation Zoom call, for those who both contributed to SFI in 2020 and could handle yet one more group video chat. In it, we discuss their lessons from the “front lines” of network epidemiology this year: what has surprised them, what has stayed with them, and what they expect it all to mean in the years to come…

Matter, energy, and information: the holy trinity of physics. Understanding the relations between these measures of our world are one of the big questions of complex systems science.

"There are decades where nothing happens; and there are weeks where decades happen.”

The modern world has a way of distancing itself from everything that came before it…and yet the evidence from archaeology supports a different story. While industrial societies tend to praise markets and advanced technologies as the main drivers of the last few centuries of change, a careful study of civilizations as distinct as Ancient Rome, Peru, and Central Mexico reveals an underlying uniformity. Consistent patterns have played out in human settlements across millennia and continents, regardless of the economic systems we’ve employed or the inventions on which we’ve relied. These patterns, furthermore, look just like those that govern and delimit evolutionary change; the scaling laws determining the growth of cities are, apparently, the same that led to cities in the first place, or to human social groups, or complex animals. Human settlements act as social reactors, by facilitating interactions — in other words, the functional relationships within communities drive history, and this century has more in common with the distant past than commonly believed.

Organisms aren’t the only products of the evolutionary process. Cultural products such as writing, art, and music also undergo change over time, subject to both the constraints of the physical environment and the psychologies of those who make them. In recent years, the study of cultural evolution has exploded with new insights — revelations into the dynamics of how culture is transmitted, how it mutates under different pressures, and why some forms are remarkably resilient and stable across time and space. Just as in biology, patterns in the structures of our artifacts converge on universals and diverge to meet the needs of their distinct environments. Certain forces ratchet up complexity in culture, whereas others act like gravity and draw the works of different societies into shared basins of attraction. Finding the fundamentals behind both the unity and the diversity of cultures, and what cultural evolution does and doesn’t have in common with biological evolution, is a field of rich mystery. New research into structural and cognitive constraints on culture leads us into some of the most fertile questions known to science…

On the one hand, we have math: a world of forms and patterns, a priori logic, timeless and consistent. On the other, we have physics: messy and embodied interactions, context-dependent and contingent on a changing world. And yet, many people get the two confused, including physicists and mathematicians. Where the two meet, and the nature of the boundary between them, is a matter of debate — one of the greatest puzzles known to science and philosophy — but some things can be said for sure about what can and cannot be accomplished in the search for ever-better models of our world. One is that every model must contain assumptions, and that there’s no way to prove a given strategy will outperform all others in all possible scenarios. This insight, captured in the legendary No Free Lunch theorems by SFI’s David Wolpert and William Macready, has enormous implications for the way think about intelligence, computers, and the living world.  In the twenty-plus years since its publication, No Free Lunch has sparked intense debate about the kinds of claims we are, and are not, justified in making…

Whether you live in the USA or have just been watching the circus from afar, chances are that you agree: “polarization” dominates descriptions of the social landscape. Judging from the news alone, one might think the States have never been so painfully divided…yet nuanced public polls, and new behavioral models, suggest another narrative: the United States is largely moderate, and people have much more in common with each other than they think. There’s no denying our predicament: cognitive biases lead us to “out-group” one another even when we might be allies, and the game of politics drives a two-party system into ever-more-intense division, until something has to give. But the same evidence from social science offers hope, that we might find a way to harness our collective thinking processes for the sake of everyone and row together toward a future big enough to hold our disagreements.

Now, maybe more than ever before, it is time to learn the art of skepticism.  Amidst compounded complex crises, humankind must also navigate a swelling tidal wave of outright lies, clever misdirections, and well-meant but dangerous mistaken claims….in other words, bullshit. Why is the 21st Century such a hotbed of fake news? How can we structure our networks and their incentives to mitigate disinformation and encourage speaking truth to power? And whose responsibility is it to inform the public and other experts about scientific research, when those insights require training to understand?

Is there life on Mars? Or Titan? What are we even looking for? Without a formal definition, inquiries into the stars just echo noise. But then, perhaps, the noise contains a signal… To find life elsewhere in the universe requires us to wager a defined biology, to come to terms with what it means to be alive. Looking out is looking in, to ask the hardest question ever: How do we find something we might not recognize as what we’re seeking?

One of the defining characteristics of complex systems science is the shift in emphasis from objects to relationships and processes. How is information related to matter and energy, and how do the distinct formulations of different scientific lineages braid together in a unifying pattern? This search for a more fundamental understanding drives directly into some of the biggest questions science has to ask about the living world — namely, what is life, what is alive, and when did life begin? The Santa Fe Institute has drawn from the deep wells of these questions since the 1980s. In our second episode, Complexity Podcast dove in to explore the origins of life, but even that in-depth conversation left a lot unsaid.

Since the 1940s, scientists have puzzled over a curious finding: armed conflict data reveals that human battles obey a power-law distribution, like avalanches and epidemics.  Just like the fractal surfaces of mountains and cauliflowers, the shape of violence looks the same at any level of magnification. Beyond the particulars of why we fight, this pattern suggests a deep hidden order in the physical laws governing society.  And, digging into new analyses of data from both armed conflicts and voting patterns, complex systems researchers have started to identify the so-called “pivotal components” — the straw that breaks the camel’s back, the spark that sets a forest fire, the influential (but not always famous) figures that shape history.  Can science find a universal theory that predicts the size of conflicts from their initial conditions, or identifies key players whose “knobs” turn society in one direction or another?

The magnitude of interlocking “wicked problems” we humans face today is daunting…and made all the worse by the widening schisms in our public discourse, the growing prominence of hate speech and prejudicial violence. How can we collaborate at scale if it’s not even safe to act as citizens, to participate in a sufficiently diverse society, without becoming targets? The World Wide Web has made it easier than ever for hate groups to organize…but also grants new power to those willing to oppose the hateful. New tactics such as “counter speech” have sprung up to depolarize society. But do they work? Can organized nonviolent interventions restore civility and save our public spaces? Or does the ensuing arms race only bring our fora closer to collapse?

Each of us at some point in our lives will face traumatizing hardship — abuse or injury, lack or loss. And all of us must weather the planetwide effects of this pandemic, economic instability, systemic inequality, and social unrest…and find a way to live on with their consequences. Trauma isn’t evenly distributed. But it IS ubiquitous, and learning how to get on with our lives is one of our main tasks as human beings. 

Cities define the modern world. They characterize the human era and its impacts on our planet. By bringing us together, these "social reactors" amplify the best in us: our creativity, efficiency, wealth, and communal ethos. But they also amplify our worst: the incidence of social crimes, the span of inequality, our vulnerability to epidemics. And built into the physics of the city is an accelerating cycle of crisis and innovation that now drives our global economy and ecosystems closer to the edge of existential peril. 

We’re living through a unique moment in history. The interlocking crises of a global pandemic, widespread unemployment, social unrest, and climate change, show us just how far human civilization has traveled along a path that leads to collapse. It is more crucial than ever to seek a deeper understanding of the systems that sustain us, and the thin layer of life on the surface of our planet. What are the underlying laws that govern how we live together and as individuals? How do our economies and cities grow? How are the human and non-human worlds related? And can we solve the problems we’ve created when we’re quarantined from one another?

Mathematical models of the world — be they in physics, economics, epidemiology — capture only details that researchers notice and deem salient. Rather than objective claims about reality, they encode (and thus enact) our blind spots. And the externalities created by those models — microscopic pathogens invisible to the naked eye, or differences in the social network structures of two neighborhoods, or food webs disrupted by urban development — have a way of biting back when we ignore them. Structural inequality created by an insufficient model jeopardizes not just the ones left off the map, but the entire systems in which they participate. Science fiction author Philip K. Dick put it well when we said that “Reality is that which, when you stop believing in it, doesn’t go away.” Ultimately, ecological and social justice is dependent on our rigorous empiricism and our dedication to describing all the relevant dimensions of our complex world.

Humans, like any other organism, occupy a niche — a “Goldilocks Zone” for which our biology is suited, relatively to the extreme diversity of habitats on Earth. But to understand the natural habitat of human beings we would first have to perform a comprehensive survey of human settlements throughout history and prehistory, looking for patterns in the climate data. No one did this research until very recently, and what they found surprised them. Human life, especially the outdoor work like farming on which our societies depend, is suited only to a very narrow band of temperature and moisture levels, a tiny area on Earth’s large surface. The implications are severe and ominous when held in light of climate forecasts for the coming decades: a major and unprecedented set of challenges that will test ability to innovate, adapt, and migrate as the world around us changes.

If COVID-19 has made anything obvious to everyone, it might be how the very small can force the transformation of the very large. Disrupt the right place in a network and exponential changes ripple outward: a virus causes a disease that leads to economic shocks and other social impacts that, in turn, re-open urban spaces to nonhuman animals and change the course of evolution.

It takes effort to embrace complexity. Simple models, simple narratives seem easier up front, their consequences only obvious in retrospect. When we talk about COVID-19 transmission rates, we’re using averages that do not offer crucial insights into how those rates may vary. When we target complex ailments with silver-bullet pharmaceuticals, we don’t address the underlying systems-level problems. Radical uncertainty resists attempts at easy answers, forcing changes in the pace at which we take shots in the dark. Sometimes, as with infection testing, we can’t seem to take shots fast enough.

COVID-19 has delivered an extraordinary shock to our assumptions, be they in how we practice education, business, research, or governance. When we base forecasts on bad data, even solid logic gives us unreliable results. Centralized authority is good for organized coherent action but isn’t agile or fine-grained enough to deal with local variance and rapidly evolving novel challenges. Surveillance can save lives but also threatens privacy upon which a diverse society depends. A longer memory might cost more to maintain, but also save more by preventing even larger economic burdens down the road.

Our histories constrain what opportunities we notice and can take in life. The genes you have define the shape your body can grow into, in concert with environmental influences. But the cards you’re dealt don’t tell you how to play your hand; for that, you have to know which game you’re playing.  Natural selection acts through the relationships between an organism and ecology, a business and economy.  What works in one environment may fail in others. The rub is that the rules are set by the collective action of all players, so the game keeps changing as the players change: disruptions shift the so-called “fitness landscape,” opening new possibilities, reallocating fortune.

For this special mini-series covering the COVID19 pandemic, we will bring you into conversation with the scientists studying the bigger picture of this crisis, so you can learn their cutting-edge approaches and what sense they make of our evolving global situation.

In several key respects, COVID-19 reveals how crucial timing is for human life. The lens of complex systems science helps us understand the central role of time in coordinating across scales, and how synchrony or misalignment leads to major consequences—whether it’s in how the metabolic differences between bats and humans can create an opportunity for interspecies epidemics, or in how the timing of society’s return to work could either help reboot or help destroy the world economy. Network research shows us early warning signs of an impending social crisis, the fossils of a vast collective computation as we struggle to adapt to periods of rapid change…and even the analogies we use to talk about these times bely a nested and embodied structure in how we encode the details of reality. These are complex times, indeed—and how civilization mutates to adapt to this pandemic will have everything to do with our ability to think and act at multiple timescales, simultaneously.

The coronavirus pandemic is in one sense a kind of prism: it reveals the many interlocking systems that, until disrupted, formed the mostly invisible backdrop of modern life, challenging the economy and our models of the world at the same time that it threatens individual and social health. The virus acts on, and invites new understanding through, the complexity we only take for granted at our peril. 

“We should not have a strategy that involves killing a sizable percentage of the population. But, even if you were going to get over that ethical hurdle, [herd immunity for Covid-19] still isn't going to work.”

Chances are, if you are listening to this around the time it was released, you’re listening alone. Right now the human species is conducting one of the most sweeping synchronized experiments of all time: physical isolation, restricted travel, shuttered businesses, our social lives moved online. Many people wonder whether all of this is truly necessary to halt the spread of COVID-19—or do not understand what differences there are between closed borders and closed schools and businesses, how epidemiologists derive the interventions they advise, and why it matters that we all stay home right now.

Pandemics like the current novel coronavirus disease outbreak provide a powerful incentive to study the dynamics of complex adaptive systems. They also make it obvious, as new information streams in and our forecasts change in real-time, how hard emergent behaviors are to model and predict. For this special mini-series covering the COVID-19 crisis, we will bring you into conversation with scientists in the Santa Fe Institute’s global research network who study epidemics so you can learn their cutting-edge approaches and what sense they make of our evolving global situation.

One feature common to nonlinear phenomena is how they challenge intuitions. Maybe nowhere is this more apparent than in studying the evolutionary process, and organisms in which not just genes but learned behaviors reproduce themselves provide a fountain of reliable surprises. Teasing out the intricate dynamics of gene-culture co-evolution is no easy feat. The dance of language, tools, and rituals together with anatomy reveals a deeper hidden order in how information spreads, and offers clues to why some strategies for innovation repeat themselves across the tree of life.

Since the term was coined in 1956, artificial intelligence has been a kind of mirror that tells us more about our theories of intelligence, and our hopes and fears about technology, than about whether we can make computers think. AI requires us to formulate and specify: what do we mean by computation and cognition, intelligence and thought? It is a topic rife with hype and strong opinions, driven more by funding and commercial goals than almost any other field of science...with the curious effect of making massive, world-changing technological advancements even as we lack a unifying theoretical framework to explain and guide the change. So-called machine intelligences are more and more a part of everyday human life, but we still don’t know if it is possible to make computers think, because we have no universal, satisfying definition of what thinking is. Meanwhile, we deploy technologies that we don’t fully understand to make decisions for us, sometimes with tragic consequences. To build machines with common sense, we have to answer fundamental questions such as, “How do humans learn?” “What is innate and what is taught?” “How much do sociality and evolution play a part in our intelligence, and are they necessary for AI?”

Over one hundred years ago, Sir Francis Galton asked 787 villagers to guess an ox’s weight. None of them got it right, but averaging the answers led to a near-perfect estimate. This is a textbook case of the so-called “wisdom of crowds,” in which we’re smarter as collectives than we are as individuals. But the story of why evolution sometimes favors sociality is not so simple — everyone can call up cases in which larger groups make worse decisions. More nuanced scientific research is required for a deeper understanding of the origins and fitness benefits of collective computation — how the complexity of an environment or problem, or the structure of a group, provides the evolutionary pressures that have shaped the landscape of wild and civilized societies alike. Not every group deploys the same rules for decision-making; some decide by a majority, some by consensus. Some groups break up into smaller sub-groups and evaluate things in a hierarchy of modular decisions. Some crowds are wise and some are dumber than their parts, and understanding how and when and why the living world adopts a vast diversity of different strategies for sociality yields potent insights into how to tackle the most wicked problems of our time.