News + Events

In a new paper in Trends in Cognitive Sciences, SFI's Mirta Galesic and Henrik Olsson explore the benefits — and potential pitfalls — of several common analogies used to model belief dynamics. 

Getting individuals to act in the best interest of society can be a tricky balancing act, one that often walks a fine line between trying to convince people to act of their own volition, versus passing laws and regulations that make these actions compulsory. A new paper in PNAS Nexus presents a mathematical model and an agent-based model that shows the effectiveness of influencers who convince others to make decisions in the best interest of society.

For a billion years, single-celled eukaryotes ruled the planet. Then around 700 million years ago during Snowball Earth — a geologic era when glaciers may have stretched as far as the equator — a new creature burst into existence: the multicellular organism. Why did multicellularity arise? Solving that mystery may help pinpoint life on other planets and explain the vast diversity and complexity seen on Earth today, from sea sponges to redwoods to human society.

Times of crisis often call for strong and rapid action, but in polarized societies, strong top-down policies can backfire. In a paper published on June 17, 2024, in Environmental Research Letters, SFI Applied Complexity Fellow Saverio Perri, SFI Science Board Fellow Simon Levin (Princeton University), and colleagues present a conceptual model of how these dynamics could play out in efforts to decarbonize our energy supply.

A a June 10–14 workshop meets to develop a new poll for the Database of Religious History to help researchers interested in quantifying the role of music and ritual in religious practices around the world. 

Most organizations operate under command hierarchies: workers, who know the ground reality, report to managers, who know the big picture. In a recent paper, three researchers use an agent-based model to explore how the performance of hierarchical groups varies with changing environments.

Health-science research could benefit from pairing two unique methods of study, argue SFI External Professor Ross Hammond and Sharin Barkin in a May 15 perspective in PNAS. When used together, traditional trials and computational models “offer powerful synergy,” write the authors.

A recent study finds that exposure to conservation programs encourages future participation, even when the early programs fail.

In a paper published in Physical Review X on May 13, a quartet of physicists and computer scientists expand the modern theory of the thermodynamics of computation. By combining approaches from statistical physics and computer science, the researchers introduce mathematical equations that reveal the minimum and maximum predicted energy cost of computational processes that depend on randomness, which is a powerful tool in modern computers. 

Will a certain tritium atom decay by a certain time? According to our current science, this question concerning physical phenomena should be answered by sampling from a probability distribution, a process not unlike spinning a roulette wheel or rolling dice. However, a paper in Foundations of Physics suggests that the same could be true of a question concerning mathematical phenomena, even one as prosaic as “what is 2+2?” 

Researchers who study Earth’s biosphere tend to operate from one of three scientific cultures, each with distinct ways of conducting science, and which have been operating mostly independently from one another, find the authors of a Perspective published in PNAS. Three SFI researchers identify and explain the three cultures, and suggest that reconnecting them could help accelerate biosphere science.

The journal Perspectives on Psychological Science, one of the flagship publications of the Association for Psychological Science, has published two new special issues, both edited by SFI researchers and both taking an unusual approach for disciplinary journals: featuring research from a range of disciplines to address two especially timely topics. One of the special issues dives into the power and perils of human collectives, while the other takes on the rapid advances in AI.

There are many things we don’t know about how history unfolds. The process might be impersonal, even inevitable, as some social scientists have suggested; human societies might be doomed to decline. Or, individual actions and environmental conditions might influence our communities’ trajectories. Social scientists have struggled to find a consensus on such fundamental issues. A new framework by SFI faculty and others suggests a way to unify these perspectives.

Randomness in an environment can make predictions difficult to model, but a new approach helps streamline the process.

Networks can represent changing systems, like the spread of an epidemic or the growth of groups in a population of people. But the structure of these networks can change, too, as links appear or vanish over time. In a new paper, a trio of SFI-affiliated researchers describe a novel way to aggregate static snapshots into smaller clusters of networks while still preserving the dynamic nature of the system.

New simulation model shows that the evolution of sustainable institutions critically depends on clearly defined and enforced access rights.

In a new paper, SFI External Professor Ricard Solé and co-authors propose an experimental setup that will test James Lovelock and Lynn Margulis's hypothesis of planetary self-regulation.

A new study in Nature Communications presents data and a mathematical model to explain why there is more unconscious, or implicit, racial bias in some cities than others. The study, which brings together the math of cities with the psychology of how individuals develop unconscious racial biases, suggests that a city's level of implicit bias depends on how populous, diverse, and segregated that city is.

Researchers introduce a mathematical model that connects innovation and obsolescence to unify insights across diverse fields, from economics and biology, to science itself.

The AI that can write sentences or compose news articles can also accurately predict the unfolding of individual human lives. A new tool called life2vec can predict outcomes, including early death, by leveraging similarities between how sequences of events progress in human lives and sequences of words progress in language, according to a recent study in Nature.