Popular and academic books and chapters, authored or edited by SFI researchers.
Inequality, social immobility, and political polarization are only a few crucial phenomena driven by the inevitability of social structures. Social structures determine who has power and influence, account for why people fail to assimilate basic facts, and enlarge our understanding of patterns of contagion—from the spread of disease to financial crises. Despite their primary role in shaping our lives, human networks are often overlooked when we try to account for our most important political and economic practices. Matthew O. Jackson brilliantly illuminates the complexity of the social networks in which we are—often unwittingly—positioned and aims to facilitate a deeper appreciation of why we are who we are. Ranging across disciplines—psychology, behavioral economics, sociology, and business—and rich with historical analogies and anecdotes, The Human Network provides a galvanizing account of what can drive success or failure in life.
Santa Fe, October 1984. Many of the most accomplished creative minds in science—including four Nobel laureates—gather to create an institution unlike any other: where unconventional thinking flourishes and disciplinary boundaries fall away.
From this meeting emerged some of the most generative research programs of the last three decades, including the physics of living systems, the mathematics of society, quantitative archaeology, the nature of mind, fundamentals of complex systems theory—and the implications of all of these on the future. The original vision of a boundary-spanning research center became what Nature has called “that mecca of multidisciplinary complexity studies”: the Santa Fe Institute. This republished volume includes chapters from the scientific talks given at the founding meetings as well as never-before-published transcripts of the roundtable discussions.
Over the last three decades, the Santa Fe Institute and its network of researchers have been pursuing a revolution in science. This volume collects essays from the past thirty years of research, in which contributors explain in clear and accessible language many of the deepest challenges and insights of complexity science.
Explore the evolution of complex systems science with chapters from Nobel Laureates Murray Gell-Mann and Kenneth Arrow, as well as numerous pioneering complexity researchers, including John Holland, Brian Arthur, Robert May, Richard Lewontin, Jennifer Dunne, and Geoffrey West.
Like many other sciences, archaeology is experiencing a data deluge. The recent accumulation of accessible data on early urban societies, coupled with the re-emergence of comparative studies, puts modern scholars in a position to make significant theoretical advances concerning the key episode of human social organization that provided the foundations of the contemporary world: the formation of the state.
A complex systems approach—pioneered at the Santa Fe Institute—involves fully interdisciplinary explorations of long-debated questions. Can basic quantitative analysis of human social evolution reveal macrocultural processes? Can we understand social cohesion by way of cultural genotypes? And does the emergence of social complexity involve the creation of new potential or the realization of latent human capabilities?
In this volume, many of the foremost experts in quantitative archaeology and anthropology leverage innovative methodologies—including agent-based modeling, network analysis, and theoretical applications of evolutionary biology—to push the field in new directions.
This book is concerned with computing in materio: that is, unconventional computing performed by directly harnessing the physical properties of materials. It offers an overview of the field, covering four main areas of interest: theory, practice, applications and implications. Each chapter synthesizes current understanding by deliberately bringing together researchers across a collection of related research projects.
The book is useful for graduate students, researchers in the field, and the general scientific reader who is interested in inherently interdisciplinary research at the intersections of computer science, biology, chemistry, physics, engineering and mathematics.
The EvoEvo project was a 2013–2017 FP7 European project aiming at developing new evolutionary approaches in information science and producing novel algorithms based on the current understanding of molecular and evolutionary biology, with the ultimate goals of addressing open-ended problems in which the specifications are either unknown or too complicated to express, and of producing software able to operate even in unpredictable, varying conditions. Here we present the main rationals of the EvoEvo project and propose a set of design rules to evolve adaptive software systems.
- A self-contained introduction, providing comprehensive coverage of the field
- Tackles the vast terrain of complex systems, by mapping them onto a simple framework
From the stock market to genomics laboratories, census figures to marketing email blasts, we are awash with data. But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren’t enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models–from linear regression to random walks and far beyond–that can turn anyone into a genius. At the core of the book is Page’s “many-model paradigm,” which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.
Is wealth inequality a universal feature of human societies, or did early peoples live an egalitarian existence? How did inequality develop before the modern era? Did inequalities in wealth increase as people settled into a way of life dominated by farming and herding? Why in general do such disparities increase, and how recent are the high levels of wealth inequality now experienced in many developed nations? How can archaeologists tell?
Ten Thousand Years of Inequality addresses these and other questions by presenting the first set of consistent quantitative measurements of ancient wealth inequality. The authors are archaeologists who have adapted the Gini index, a statistical measure of wealth distribution often used by economists to measure contemporary inequality, and applied it to house-size distributions over time and around the world. Clear descriptions of methods and assumptions serve as a model for other archaeologists and historians who want to document past patterns of wealth disparity.
The chapters cover a variety of ancient cases, including early hunter-gatherers, farmer villages, and agrarian states and empires. The final chapter synthesizes and compares the results. Among the new and notable outcomes, the authors report a systematic difference between higher levels of inequality in ancient Old World societies and lower levels in their New World counterparts.
For the first time, archaeology allows humanity’s deep past to provide an account of the early manifestations of wealth inequality around the world.
Nicholas Ames, Alleen Betzenhauser, Amy Bogaard, Samuel Bowles, Meredith S. Chesson, Abhijit Dandekar, Timothy J. Dennehy,
Robert D. Drennan, Laura J. Ellyson, Deniz Enverova, Ronald K. Faulseit, Gary M. Feinman, Mattia Fochesato, Thomas A. Foor,
Vishwas D. Gogte, Timothy A. Kohler, Ian Kuijt, Chapurukha M. Kusimba, Mary-Margaret Murphy, Linda M. Nicholas, Rahul C. Oka,
Matthew Pailes, Christian E. Peterson, Anna Marie Prentiss, Michael E. Smith, Elizabeth C. Stone, Amy Styring, Jade Whitlam
The study of networks, including computer networks, social networks, and biological networks, has attracted enormous interest in the last few years. The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on an unprecedented scale, and the development of new theoretical tools has allowed us to extract knowledge from networks of many different kinds. The study of networks is broadly interdisciplinary and central developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas.
Topics covered include the measurement of networks; methods for analyzing network data, including methods developed in physics, statistics, and sociology; fundamentals of graph theory; computer algorithms; mathematical models of networks, including random graph models and generative models; and theories of dynamical processes taking place on networks.
Scale; the universal laws of growth, innovation, sustainability, and the pace of life in organisms, cities, economies, and companies
Visionary physicist Geoffrey West is a pioneer in the field of complexity science, the science of emergent systems and networks. The term “complexity” can be misleading, however, because what makes West’s discoveries so beautiful is that he has found an underlying simplicity that unites the seemingly complex and diverse phenomena of living systems, including our bodies, our cities and our businesses.
Fascinated by aging and mortality, West applied the rigor of a physicist to the biological question of why we live as long as we do and no longer. The result was astonishing, and changed science: West found that despite the riotous diversity in mammals, they are all, to a large degree, scaled versions of each other. If you know the size of a mammal, you can use scaling laws to learn everything from how much food it eats per day, what its heart-rate is, how long it will take to mature, its lifespan, and so on. Furthermore, the efficiency of the mammal’s circulatory systems scales up precisely based on weight: if you compare a mouse, a human and an elephant on a logarithmic graph, you find with every doubling of average weight, a species gets 25% more efficient—and lives 25% longer. Fundamentally, he has proven, the issue has to do with the fractal geometry of the networks that supply energy and remove waste from the organism’s body.
West’s work has been game-changing for biologists, but then he made the even bolder move of exploring his work’s applicability. Cities, too, are constellations of networks and laws of scalability relate with eerie precision to them. Recently, West has applied his revolutionary work to the business world. This investigation has led to powerful insights into why some companies thrive while others fail. The implications of these discoveries are far-reaching, and are just beginning to be explored. Scale is a thrilling scientific adventure story about the elemental natural laws that bind us together in simple but profound ways. Through the brilliant mind of Geoffrey West, we can envision how cities, companies and biological life alike are dancing to the same simple, powerful tune.
What is history anyway? Most people would say it’s what happened in the past, but how far back does the past extend? To the first written sources? To what other forms of evidence reveal about pre-literate civilizations? What does that term mean—an empire, a nation, a city, a village, a family, a lonely hermit somewhere? Why stop with people: shouldn’t history also comprise the environment in which they exist, and if so on what scale and how far back? And as long as we’re headed in that direction, why stop with the earth and the solar system? Why not go all the way back to the Big Bang itself?
There’s obviously no consensus on how to answer these questions, but even asking them raises another set of questions about history: who should be doing it? Traditionally trained historians, for whom archives are the only significant source? Historians willing to go beyond archives, who must therefore rely on, and to some extent themselves become, psychologists, sociologists, anthropologists, archeologists? But if they’re also going to take environments into account, don’t they also have to know something about climatology, biology, paleontology, geology, and even astronomy? And how can they do that without knowing some basic physics, chemistry, and mathematics?
This inaugural volume of the SFI Press (the new publishing arm of the Santa Fe Institute) attempts to address these questions via thoughtful essays on history written by distinguished scholars—including Nobel laureate Murray Gell-Mann—from across a wide range of fields.
One of America’s foremost philosophers offers a major new account of the origins of the conscious mind.
How did we come to have minds?
For centuries, this question has intrigued psychologists, physicists, poets, and philosophers, who have wondered how the human mind developed its unrivaled ability to create, imagine, and explain. Disciples of Darwin have long aspired to explain how consciousness, language, and culture could have appeared through natural selection, blazing promising trails that tend, however, to end in confusion and controversy. Even though our understanding of the inner workings of proteins, neurons, and DNA is deeper than ever before, the matter of how our minds came to be has largely remained a mystery.
That is now changing, says Daniel C. Dennett. In From Bacteria to Bach and Back, his most comprehensive exploration of evolutionary thinking yet, he builds on ideas from computer science and biology to show how a comprehending mind could in fact have arisen from a mindless process of natural selection. Part philosophical whodunit, part bold scientific conjecture, this landmark work enlarges themes that have sustained Dennett’s legendary career at the forefront of philosophical thought.
In his inimitable style―laced with wit and arresting thought experiments―Dennett explains that a crucial shift occurred when humans developed the ability to share memes, or ways of doing things not based in genetic instinct. Language, itself composed of memes, turbocharged this interplay. Competition among memes―a form of natural selection―produced thinking tools so well-designed that they gave us the power to design our own memes. The result, a mind that not only perceives and controls but can create and comprehend, was thus largely shaped by the process of cultural evolution.
How do people living in small groups without money, markets, police and rigid social classes develop norms of economic and social cooperation that are sustainable over time? This book addresses this fundamental question and explains the origin, structure and spread of stateless societies. Using insights from game theory, ethnography and archaeology, Stanish shows how ritual - broadly defined - is the key. Ritual practices encode elaborate rules of behavior and are ingenious mechanisms of organizing society in the absence of coercive states. As well as asking why and how people choose to co-operate, Stanish also provides the theoretical framework to understand this collective action problem. He goes on to highlight the evolution of cooperation with ethnographic and archaeological data from around of the world. Merging evolutionary game theory concepts with cultural evolutionary theory, this book will appeal to those seeking a transdisciplinary approach to one of the greatest problems in human evolution.
What if workforce diversity is more than simply the right thing to do in order to make society more integrated and just? What if diversity can also improve the bottom line of businesses and other organizations facing complex challenges in the knowledge economy? It can. And The Diversity Bonus shows how and why.
Scott Page, a leading thinker, writer, and speaker whose ideas and advice are sought after by corporations, nonprofits, universities, and governments around the world, makes a clear and compellingly pragmatic case for diversity and inclusion. He presents overwhelming evidence that teams that include different kinds of thinkers outperform homogenous groups on complex tasks, producing what he calls “diversity bonuses.” These bonuses include improved problem solving, increased innovation, and more accurate predictions—all of which lead to better performance and results.
Page shows that various types of cognitive diversity—differences in how people perceive, encode, analyze, and organize the same information and experiences—are linked to better outcomes. He then describes how these cognitive differences are influenced by other kinds of diversity, including racial and gender differences—in other words, identity diversity. Identity diversity, therefore, can also produce bonuses.
Drawing on research in economics, psychology, computer science, and many other fields, The Diversity Bonus also tells the stories of people and organizations that have tapped the power of diversity to solve complex problems. And the book includes a challenging response from Katherine Phillips of the Columbia Business School.
The result changes the way we think about diversity in the workplace—and far beyond it.
What constitutes the study of philosophy or physics? What exactly does an anthropologist do, or a geologist or historian? In short, what are the arts and sciences? While many of us have been to college and many aspire to go, we may still wonder just what the various disciplines represent and how they interact. What are their origins, methods, applications, and unique challenges? What kind of people elect to go into each of these fields, and what are the big issues that motivate them? Curious to explore these questions himself, Dartmouth College professor and mathematician Dan Rockmore asked his colleagues to explain their fields and what it is that they do. The result is an accessible, entertaining, and enlightening survey of the ideas and subjects that contribute to a liberal education. The book offers a doorway to the arts and sciences for anyone intrigued by the vast world of ideas.
The book provides a comprehensive introduction and a novel mathematical foundation of the field of information geometry with complete proofs and detailed background material on measure theory, Riemannian geometry and Banach space theory. Parametrised measure models are defined as fundamental geometric objects, which can be both finite or infinite dimensional. Based on these models, canonical tensor fields are introduced and further studied, including the Fisher metric and the Amari-Chentsov tensor, and embeddings of statistical manifolds are investigated.
This novel foundation then leads to application highlights, such as generalizations and extensions of the classical uniqueness result of Chentsov or the Cramér-Rao inequality. Additionally, several new application fields of information geometry are highlighted, for instance hierarchical and graphical models, complexity theory, population genetics, or Markov Chain Monte Carlo.
The book will be of interest to mathematicians who are interested in geometry, information theory, or the foundations of statistics, to statisticians as well as to scientists interested in the mathematical foundations of complex systems.
Info-metrics is the science of modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. The Foundations of Info-Metrics examines the theoretical underpinning of info-metrics and provides extensive interdisciplinary applications.
A top expert explains why a social and economic understanding of complex systems will help society to anticipate and confront our biggest challenges
Imagine trying to understand a stained glass window by breaking it into pieces and examining it one shard at a time. While you could probably learn a lot about each piece, you would have no idea about what the entire picture looks like. This is reductionism--the idea that to understand the world we only need to study its pieces--and it is how most social scientists approach their work.
In A Crude Look at the Whole, social scientist and economist John H. Miller shows why we need to start looking at whole pictures. For one thing, whether we are talking about stock markets, computer networks, or biological organisms, individual parts only make sense when we remember that they are part of larger wholes. And perhaps more importantly, those wholes can take on behaviors that are strikingly different from that of their pieces.
Miller, a leading expert in the computational study of complex adaptive systems, reveals astounding global patterns linking the organization of otherwise radically different structures: It might seem crude, but a beehive's temperature control system can help predict market fluctuations and a mammal's heartbeat can help us understand the "heartbeat" of a city and adapt urban planning accordingly. From enduring racial segregation to sudden stock market disasters, once we start drawing links between complex systems, we can start solving what otherwise might be totally intractable problems.
Thanks to this revolutionary perspective, we can finally transcend the limits of reductionism and discover crucial new ideas. Scientifically founded and beautifully written, A Crude Look at the Whole is a powerful exploration of the challenges that we face as a society. As it reveals, taking the crude look might be the only way to truly see.