Jessica's research focuses on coarse-graining and collective computation in nature and their role in the evolution and development of new levels of biological and social organization and kinds of individuality. The approach is very mechanistic and empirical but makes use of tools and concepts from statistical physics, information theory, and theoretical computer science to build empirically-grounded stochastic social circuits that map the micro to the macro. Once the (usually very complicated) stochastic circuits are obtained, the goal is to build an algorithmic theory that compactly encodes the collective computation producing the functionally important aggregate properties of the system.
To build these theories we use coarse-graining, optimization, and dimension reduction techniques to reduce circuit complexity. Because our aim is to capture how the system's components compute and how these computations collectively result in new levels of organization, we, when choosing among alternative dimension reduction and optimization techniques, take into account their computational burden, the information processing capacities of the components, and the quality of the data to which components are exposed. In other words, we want to identify the effective theories components have for their worlds, and use this information to construct the algorithmic theory encoding the collective computation.
The reason we are after a theory that captures how the system itself computes, rather than one that efficiently predicts by our standards, is because of the character of biological systems. Biological (to include social) systems are composed of heterogeneous components with different information processing capacities and only partly aligned interests, so a natural question is how the components in these systems estimate and control the regularity in their environments to optimally tune their strategies. Jessica is exploring the possibility that components reduce uncertainty by manipulating space and time—producing multi-scale structure—and creating order locally. The increased correlation facilitates collective tuning of the coupling across scales and allows biological systems to manage trade-offs between robustness and adaptability.
Algorithmic theories for biological systems will tell us how tunable and controllable the important macroscopic properties are, help us understand how social systems, and the dynamics producing them, evolve, and move us towards a science of social engineering.
Ultimately, of course, we seek common algorithmic principles underlying the emergence of novel, functionally significant spatial and temporal scales, and ultimately new kinds of collectives and individuality. To this end, we study a wide range of aggregates, from societies of cells to societies of individuals.
Jessica's research has involved development of novel computational techniques (Inductive Game Theory) for extracting strategic decision-making rules from time-series data and using the extracted strategies to construct causal networks or adaptive, stochastic, social circuits that map microscopic dynamics to tunable, functionally important macroscopic states. Using information about biological and cognitive constraints, Jessica and her collaborators reduce the complexity of these circuits (which describe the system’s microscopic behavior) using coarse-graining and dimension reduction techniques to uncover circuit logic and work towards an effective theory for the target macroscopic features.
Keywords: computation in nature, complexity, multi-scale, stochastic circuits, robustness, signaling, consensus, coarse-graining, collective behavior and cognition, conflict management, emergence, individuality, information processing, uncertainty reduction, mutual information, criticality, major transitions, causality, social evolution, niche construction
You can read more about this work here.
With two colleagues--David Krakauer and Nihat Ay, Jessica is writing a book on robustness, causal networks, and experimental design that will be published by Princeton University Press.
Jessica Flack is Co-Director of the Center for Complexity and Collective Computation in the Wisconsin Institute for Discovery at the University of Wisconsin, Madison and External Professor at the Santa Fe Institute. Jessica received her BA with honors from Cornell University in 1996, studying anthropology, evolutionary theory, and biology. She received her PhD from Emory University in 2004, studying animal behavior, cognitive science, and evolutionary theory. For the next eight years she was in residence at the Santa Fe Institute, first as a Postdoctoral Fellow and then as Research Professor, and finally as Professor. She moved to the University of Wisconsin, Madison in 2011. Jessica’s research has empirical and theoretical components and sits at the interface of evolutionary theory, pattern formation, behavior, cognitive science, computer science, information theory, and statistical mechanics. Although most of her work now is of a computational nature, she 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, Jessica enjoys writing popular science articles and book reviews. Her work has been covered by other scientists and science journalists in many publications and media outlets, including the BBC, NPR, Nature, Science, The Economist, New Scientist, and Current Biology.
Jessica's nonacademic interests include swimming, surfing, backcountry travel, cooking (chiles and super-spicy food, gnocchi recipes, curries, moles, pastries, sabayon and custards, 'wealthy' apple & fennel pollen pie, pan nero, anything with medjool dates…), gardens and parks, ornamental grasses, conifers (especially those with weeping and irregular forms like Picea pungens weeping blue, Pinus mugo jacobsen, Picea abies cobra, Pinus parviflora tani mano uki, and any Cedrus deodara), tall bearded iris, orchids (esp. Phragmipedium caudatum) art (a diverse bunch, here drawn kind of at random: James Turell, Bruegel, Andrew Wyeth, Eric Fischl, James Drake, Cindy Sherman, Rick Owens, Joseph Cornell, African art, Walton Ford, Aboriginal art, Balthus, Klee, Klimt, Lucien Freud, Odd Nerdrum, Giovanni Bellini, Marcel Dzama, Roberto Matta, Brancusi, etc.. ), all kinds of film (e.g. Alien, Duck You Sucker, Bebette's Feast, The Blind Swordsman: Zatoichi, Seven Samurai, 2001: A Space Odyssey, Blade Runner, The Lives of Others, Terminator, The Royal Tenenbaums, Godzilla and Mothra: The Battle for Earth, Tom Ford's A Single Man, Die Hard, Bottle Rocket, Gosford Park, The Big Gun Down, True Grit--the original and the new one, The Great Beauty (La Grande Belleza)), science fiction, literature (e.g., Tropic of Cancer, Blood Meridian, Suttree, Absalom Absalom!, Sebald's The Rings of Saturn, all of Borges, Sleepless Nights by Elizabeth Hardwick, Ellison's Invisible Man, Gravity's Rainbow, The Recognitions, Lolita, Moby Dick, Carpentier's The Kingdom of this World and Explosion in a Cathedral, Donoso's Obscene Bird of Night, The Mars Trilogy, Tolkien, Hurston's Their Eyes Were Watching God, Baldwin's Tell Me How Long the Train's Been Gone, Beckett's Trilogy), fashion (Rick Owens, futuristic Marni, fully floral Dolce & Gabbana…), and people who are naturally empathic and observant.
A few of her favorite places are Paia and Maui's north shore, Big Sur, maybe parts of East Berlin in the summer, 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, Venice, Morocco, and all of the desert southwest, --particularly Santa Fe, NM, which she considers her home. She lives with David Krakauer, three cats, including one Tonkinese cat, and a dog, who are best buddies. She would have one Tonkinese cat for each harpooner and mate in Moby Dick, but for some reason David does not think this is a good idea. . .
Center for Complexity & Collective Computation
Wisconsin Institute for Discovery
330 N. Orchard Street
Madison, WI 53715