News + Events

Novelist Tom McCarthy has been named a Miller Scholar at the Santa Fe Institute for 2022–2025.

SFI Professor Sam Bowles and External Professor Herb Gintis have been selected as 2022 Citation Laureates by Clarivate "for providing evidence and models that broaden our understanding of economic behavior to include not only self-interest but also reciprocity, altruism, and other forms of social cooperation.”

Microeconomics: Competition, Conflict, and Coordination, a new textbook by SFI Professor Samuel Bowles and Simon Halliday, upends the conventional content of economics texts and allows a new, more engaging, way of teaching the subject.

SFI welcomes Complexity Postdoctoral Fellow Daniel Muratore, whose research focuses on multiple aspects of the knowledge-generating process from theory and simulation to data analysis to classical oceanographic fieldwork.

In late May, SFI's postdocs gathered for 72 Hours of Science — two nights and three days of collaborative, generative science — to see how far they could develop a research question in a limited time. 

SFI welcomes new Program Postdoctoral Fellow Arseny Moskvichev, who is fascinated by how people use language and abstraction to communicate and share knowledge.

SFI welcomes Complexity Postdoctoral Fellow Kelle Dhein, who hopes to shed new light on the debate about what information is by exploring how particular concepts of information influence present-day research in the behavioral sciences.

The climate and biodiversity crises are stressing wildlife species around the world in unprecedented ways. A species’ evolutionary past, however, can help shed light on its fate in the face of future environmental change. Helping to fill in these crucial data gaps is the focus of Complexity Postdoctoral Fellow Jack Shaw’s work at SFI. 

In a new paper, SFI Complexity Fellow Stefani Crabtree and Jennifer Dunne, SFI’s Vice President for Science, lay out the first comprehensive definition of archaeoecology, an emerging field that can fill a knowledge gap about important questions of how humans and nature interacted and shaped each other across different places and through time. 

Many researchers at SFI are driven by a curiosity to understand the laws that underlie various forms of life. Work spearheaded more than two decades ago by SFI’s Geoffrey West, Brian Enquist, and Jim Brown has illustrated that organisms’ biological functions are governed by scaling laws. Other researchers have gone on to discover that human social life, from cities to organizations, follows similar rules. “These laws apply, with their own specificities, across domains,” says Veronica Cappelli, an SFI Applied Complexity Postdoctoral Fellow.

A new kind of predictive network model could help determine which people will change their minds about contentious scientific issues when presented with evidence-based information. A new study in Science Advances presents a framework to accurately predict whether a person will change their opinion about a certain topic. The approach estimates the amount of dissonance, or mental discomfort, a person has from holding conflicting beliefs about a topic. 

Heatwaves are triggering wildfires and killing people around the globe. The climate emergency and the planet’s sixth mass extinction event have already begun. A special themed issue in Philosophical Transactions of the Royal Society B: Biological Sciences addresses what actions have led us to this point and what we can do from here.

At present, the global economy is experiencing structural changes that often seem unprecedented. Rapid technological evolution, climate migration, demographic shifts, and deepening inequality all contribute to the current flux of economic systems. The threat of economic reconfiguration also appears to be fueling political polarization around the globe. In light of the current patterns that researchers are observing, many seek new methods to understand the mechanisms that shape the new landscape. An August 8-12 working group explores “How Can Complexity Economics Give More Insight into Political Economy?” 

Imagine that we rewound life’s tape to a distant past and let evolution play out again. Which species and traits would succeed the second time? Which characteristics would emerge over and over again, invariant to random chance? Aviv Bergman of the Albert Einstein Institute of Medicine is spending his sabbatical at the Santa Fe Institute, developing computational models designed to answer those questions.

SFI welcomes nine new members to our External Faculty and one rejoining member. 

SFI Research Development Director Susan Carter has received a 2022 Mentoring Award from the National Organization of Research Development Professionals (NORDP). 

To address climate change and other societal challenges like rising inequality, human migration, and biodiversity loss, humanity must consider the ecological, economic, and political constraints of our planetary systems. In late July, the International Centre for Theoretical Physics (ICTP) in Trieste, Italy, hosted a workshop to discuss these considerations and foster collaboration across research communities. SFI co-hosted the workshop in partnership with ICTP and the Fondazione Internazionale Trieste. 

A general theory describing how life depends on temperature has been lacking — until now. In a recent paper in the Proceedings of the National Academy of Sciences, research led by José Ignacio Arroyo, an SFI Postdoctoral Fellow, introduces a simple framework that rigorously predicts how temperature affects living things, at all scales. 

After two years of online-only and postponed events, SFI's summer education programs are back in person. June brought students from around the world to participate in the Undergraduate Complexity Research, Complex Systems Summer School, Graduate Workshop in Computational Social Science, and Advanced Graduate Workshop programs. 

By taking another look at the complex relationship between crime and society, researchers at the University of Chicago, including SFI External Professor James Evans, have developed an algorithm that can predict urban crime one week in advance with 90% accuracy. The study, published in Nature Human Behavior, analyzed eight cities — Chicago, Atlanta, Austin, Detroit, Los Angeles, Philadelphia, Portland, and San Francisco — and found consistent results.