How do the regulatory systems of governments change as they grow? Do bigger governments require more or fewer bureaucrats per capita? Are more efficient bureaucracies possible? Program Postdoctoral Fellow James Holehouse is fascinated by how complex systems, from governments to cells, change over time.
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.
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.
In biology, hierarchies are everywhere, from Linnaean taxonomy — the system we use to classify living things — to the social organization within a pod of gorillas. Biological hierarchies are often explained by the Major Evolutionary Transitions (MET) framework, which holds that evolutionary processes gave rise to life’s hierarchies. But this framework has some missing pieces, Complexity Postdoctoral Fellow Pedro Márquez-Zacarías suggests.
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.
This October 22 & 23, SFI will reprise the InterPlanetary Festival. In partnership with SITE Santa Fe, this year’s festival offers an intimate setting with limited seating, and content simulcast to multiple screens in Santa Fe's Railyard Park and streamed online.
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.
Imagine a bookshelf that stretches far into the distance, laden with genre fiction: potboilers, romances, thrillers. Farther down, we glimpse the royal blue of a Fitzcarraldo edition. The catch? Every book has the same author: E. Machina. They’ve all been written by AI. To SFI External Professor Dan Rockmore (Dartmouth College), we’re closer than we think to the world of that bookstore. The working group “The Anxiety of the Computational” explores questions about how AI-written literature might impact the humanities.