Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501 USA
I am a professor at SFI where I also run the Collective Computation Group and serve as Chair of Public Events.
Emergence of Biological Space & Time
I study how nature computes solutions to problems & how these computations are refined over evolutionary and learning time. My research draws on evolutionary theory, cognitive neuroscience and behavior, statistical mechanics, information theory, dynamical systems and theoretical computer science to study the roles of information processing and collective computation in the emergence of robust structure and function in adaptive systems. Goals include identifying the computational principles that allow nature to overcome subjectivity due to information processing to produce ordered states and understanding why adaptive systems typically have many space and timescales. A central idea is noisy information processors construct their macroscopic worlds through collective coarse-graining in evolutionary and/or learning time. In other words, how the appropriate aggregation of information from components making decisions under uncertainty can produce good collective forecasts.
This research has involved development of novel computational techniques (Inductive Game Theory) for extracting strategies (and potentially game structure and payoffs) from time-series data and constructing stochastic strategic circuits that map input to the target macroscopic output. These circuits are predictive but suffer from the deficit of being complicated. We employ biologically principled dimension reduction techniques to simplify the circuits in the service of identifying mechanistically appropriate minimal circuit models. One can think of this approach as embedding complex decision rules in formalisms for connecting microscopic configurations to macroscopic averages. A proximate goal is to uncover circuit logic and work towards an algorithmic theory for the target macroscopic properties. An ultimate goal is to determine whether living systems—composed of noisy, adaptive, heterogeneous components often with multiple goal states—are governed by laws derived from simple microscopic processes or reflect contingent events leading to irreducible complexity.
This work is empirically grounded and often motivated by deep understanding of finite, out of equilibrium, heterogenous, and typically relatively small model systems in which components have only partly overlapping interests and are noisy information processors dealing with noisy signals. We have explored, or are exploring, these ideas in social systems, markets, neural systems, artificial intelligence and gene regulatory systems.
Read a profile in Quanta Magazine.
Ay, N., Krakauer, D.C. and Flack, J.C. Robustness & Causality, Princeton University Press, In prep.
Krakauer, D.C. & Flack, J.C. (edited volume in three part series). Complexity & Inference in Evolution, Princeton University Press
Flack, J.C. Collective Computation in Nature. In development.
Jessica Flack is a professor at the Santa Fe Institute. Flack directs SFI's Collective Computation Group (C4). Flack was formerly founding director of the Center for Complexity and Collective Computation in the Wisconsin Institute for Discovery at the University of Wisconsin, Madison. Flack received her PhD from Emory in 2003, studying cognitive science, animal behavior and evolutionary theory, and BA with honors from Cornell in 1996. Flack's work has been covered by scientists and science journalists in many publications and media outlets, including Quanta Magazine, the BBC, NPR, Nature, Science, The Economist, New Scientist, and Current Biology.
Flack's research focuses on collective computation and its role in the emergence of robust structure and function in nature and society. A central philosophical issue behind this work is how nature overcomes subjectivity inherent in information processing systems to produce collective, ordered states.
Although most of Flack's work now is of a computational nature, Flack has spent thousands of hours collecting large behavioral data sets, including highly resolved time-series, from animal societies, and she conducted the first behavioral knockout study on social systems. In that study, she designed an experiment to disable a critical conflict management function—policing—to quantify its role in social system robustness in an animal society. In addition to peer-reviewed publications, Flack enjoys writing popular science articles and book reviews.
Flack's nonacademic interests include cooking, reading poetry, literature & nonfiction, writing, swimming, surfing, backcountry running & travel, ice skating, conifer gardening, and watching sports like basketball & lacrosse. Flack loves art, a wide range of film and music, and is always learning new things.
A few favorite places include Maui's north shore, Big Sur, the Storm King Art Center in Mountainville, New York, Telluride, the Weminuche Wilderness, the Grand Canyon of the Tuolumne River, the Grand Tetons, Corsica, Chang Mai, Tanzania, Patagonia, Kyoto, Venice, Morocco, and all of the desert southwest—particularly Santa Fe, NM, which Flack considers her home. Flack has two cats, including one Tonkinese cat.
Third photo by Gabriella Marks. Drawing by James Drake.