In The Ethical Algorithm: The Science of Socially Aware Algorithm Design, SFI External Professor Michael Kearns and his University of Pennsylvania colleague Aaron Roth offer a set of principled solutions based on the emerging science of socially aware algorithm design.
Melanie Mitchell presented an SFI Community Lecture on artificial intelligence at The Lensic Performing Arts Center on November 12.
On October 18, a group of ten computer scientists, social scientists, and legal scholars from the Santa Fe Institute and The University of New Mexico submitted a formal response to the U.S. Department of Housing and Urban Development’s (HUD) proposal to dramatically revise the Fair Housing Act.
External Professor Allison Stanger’s book Whistleblowers: Honesty in America from Washington to Trump is garnering significant media attention.
SFI’s “social reactor” kicked into overdrive this summer, welcoming 163 undergraduates, graduate students, and professionals. Intensive summer programs form the core of the Institute’s educational programming, bringing future complexity scholars to Santa Fe to train with leading scientists. This year, the Graduate Workshop in Computational Social Science and Complexity (GWCSS) celebrated its 25th anniversary with programming for alumni as well as a new cohort of advanced graduate students.
During Earth’s last glacial period, temperatures on the planet periodically spiked dramatically and rapidly. A new paper in the journal Chaos by SFI's Joshua Garland, Liz Bradley, and coauthors suggests that mathematics from information theory could offer a powerful tool for analyzing and understanding them.
Ashley Teufel and Luis Zaman's working group, “The Point of No Return,” seeks to identify the underlying properties driving entrenchment, a phenomenon in which a single event can have a widespread effect on an entire system, and find ways to infer, predict or even control it.
Artificial Intelligence: A Guide for Thinking Humans is a solid history of how we got from pocket calculators to facial recognition and self-driving cars, a lucid tour of how these systems operate, and a measured warning against placing more trust in these systems than they deserve.
The Neolithic Agricultural Revolution is one of the most thoroughly-studied episodes in prehistory. But a new paper by Sam Bowles and Jung-Kyoo Choi shows that most explanations for it don’t agree with the evidence, and offers a new interpretation.
Jessica Flack presents an SFI Community Lecture on collective computation at The Lensic Performing Arts Center on October 22.
External Professor Raissa D’Souza has won the Network Science Society’s inaugural Euler award for her influential work in "the discovery and study of explosive percolation in networks and the insights it provided to explosive synchronization and network optimization.”
SFI External Professor W. Brian Arthur has been selected as a 2019 Citation Laureate by the Web of Science group “for research revealing network effects in economic systems that produce increasing returns."
A television production written and hosted by SFI Professor Cris Moore won a 2019 Rocky Mountain Emmy Award in the instructional/informational category.
Seven thousand years ago, societies across Eurasia began to show signs of lasting divisions between haves and have-nots. In new research published in the journal Antiquity, scientists chart the precipitous surge of prehistoric inequality and trace its economic origins back to the adoption of ox-drawn plows.
Why it is that only some crimes supercharge from city size is explained in a new paper published this week in Physical Review E. According to Complexity Postdoctoral Fellow Vicky Chuqiao Yang and her coauthors, the same underlying mechanism that boosts urban innovation and startup businesses can also explain why certain types of crimes thrive in a larger population.
Infectious disease outbreaks often emerge when and where we are least equipped to detect and control them. In a series of two lectures, SFI External Professor Lauren Ancel Meyers discusses how network-based mathematical models data accelerate the detection and containment of outbreaks.