News + Events

A new study in Science Advances proposes a model for examining the interplay of epidemiology and economics that could give policymakers guidelines when we face novel outbreaks in the future.

In a paper in Scientific Reports, former SFI Postdoctoral Fellow Gizem Bacaksizlar Turbic and SFI Professor Mirta Galesic tested compared the network structure of comments in four publications with varying political persuasions to test theories about the potential influence of a small group of voices. 

ChatGPT knows how to use the word “tickle” in a sentence but it cannot feel the sensation. Can it then be said to understand the meaning of the word tickle the same way we humans do? In a paper for PNAS, SFI researchers Melanie Mitchell and David C. Krakauer survey the ongoing debate in which AI researchers are teasing apart whether Large Language Models like ChatGPT and Google’s PaLM understand language in any humanlike sense.

In the last 50 years, economic theory has come to be based almost solely on mathematics. This brings logical precision, but according to a new paper by SFI economist Brian Arthur, it restricts what economics can easily talk about.

Does a diversity of species protect ecological communities from invasion? Recent work by SFI External Professor Andreas Wagner takes up this long-standing question for complexity science, at a microscopic scale.

In November, Brian Enquist, Mary O’Connor, and Chris Kempes organized a workshop to take stock of advances in biological scaling theory since the publication of a seminal book for the field.

For at least 200,000 years, humans have been trying to understand their environments and adapt to them. At times, we have succeeded; often, we have not. In a new study, SFI's Stefani Crabtree, Jennifer Dunne, and others analyze how information flows from ecosystems to the societies inhabiting them.

Two recent papers by CU Boulder and SFI co-authors explore the socioeconomic makeup and the educational backgrounds of tenure-track faculty across the U.S. 

A new dataset, WikiArtVectors, aims to make computational data approaches available to art historians and cultural analysts, to help discover and understand patterns of cultural evolution.

If you think clean energy is expensive, try fossil fuels. A new report in the journal Joule shows that a rapid transition to renewable energy sources by 2050 could save the global economy trillions of dollars compared to both a gradual transition and to no transition at all.

Friendships in childhood influence incomes in adulthood, and may play an important role in stimulating economic mobility, according to research published across two new papers in Nature.

Research jams are among the highlights of the biannual JSMF–SFI Postdocs in Complexity Conference. This fall, two micro-working groups met in the week leading up to the conference to make progress on conversations they began at the meeting last spring. 

The October 13–14 workshop "Coding the Past: The Challenges and Promise of Large-Scale Cultural Databases" meets to train a group of researchers to use the new online Database of Religious History.

At the crossroads of computer science and computational science, the emerging field of scientific machine learning focuses on harnessing new ideas in machine learning together with predictive physics-based models to solve complex, real-world problems. On October 10–12, a group met to collaborate on new ideas about using scientific machine learning in complex fields.

SFI Professor David Wolpert grapples with the limits of human intelligence in a new essay for Aeon magazine.

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. 

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.

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. 

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.