Alex Peysakhovich


game theory, AI, behavioral economics, market design, applied machine learning, data science

alex.peys (at) gmail.com // alex_peys // Google Scholar


I am a senior research scientist at Facebook Artificial Intelligence research. My work includes both basic and applied research at the intersection of behavioral science, economics, game theory, and artificial intelligence. I hold a PhD in Behavioral Economics from Harvard.

My recent research involves exporting insights from behavioral economics and mechanism design to the design of smart artificial agents. I am also interested in trade going the other way: constructing new machine learning tools to improve the way we do behavioral/social science and market design. See my publication list (below) for more details.

At Facebook I have worked on many machine learning/data science projects including detecting clickbait, building large scale embedding systems, implementing advanced experimentation techniques, understanding network effects, and improving the way we measure hard to measure outcomes. Changes to Facebook resulting from some of these projects have been significant enough to appear in the popular press (Slate, NYT, Forbes). See my professional resume for more details.

I have found that applied product work is actually a neat way to find good basic research questions. These three papers are great examples.

I was once profiled in Pacific Standard. The article makes me seem much more interesting than I am.

I also like photography (mostly film). Check out my : alexpeys

Academic Research

Work in Progress

"Maintaining cooperation in complex social dilemmas using deep reinforcement learning" (with Adam Lerer)
[Under review] [pdf]

"Learning existing social conventions in Markov games" (with Adam Lerer)
[Under review] [pdf]

"In-Group favoritism caused by Pokemon Go and the use of machine learning for principled investigation of potential moderators" (with David Rand)
[Revise and Resubmit Nature Scientific Reports] [pdf]

"Improving pairwise comparison models using Empirical Bayes" (with Stephen Ragain, Johan Ugander)
[Under review] [pdf]

"Backplay: 'Man Muss Immer Umkeheren'" (with Cinjon Resnick, Roberta Raileanu, Sanyan Kapoor, Kyunghyun Cho, Joan Bruna)
[Under review] [pdf]

"Paying (for) Attention: The Impact of Information Processing Costs on Bayesian Inference" (with Xiaosheng Mu, Scott Kominers)
[Under review] [pdf]

2018 Publications

"Prosocial learning agents solve generalized Stag Hunts better than selfish ones" (with Adam Lerer)
[AAMAS2018] [pdf]

"Consequentialist conditional cooperation in social dilemmas with imperfect information" (with Adam Lerer)
[ICLR2018] [pdf]

"Learning causal effects from many randomized experiments using regularized instrumental variables" (with Dean Eckles)
[WWW2018] [pdf]

"Towards AI that can solve social dilemmas" (with Adam Lerer)
[AAAI2018 Spring Symposium Series] [Proceedings]

2017 Publications

Multi-Agent Cooperation and the Emergence of (Natural) Language" (with Angeliki Lazaridou and Marco Baroni)
[ICLR2017] [pdf]

"Using methods from machine learning to evaluate models of human choice under uncertainty" (with Jeff Naecker)
[Journal of Economic Behavior and Organization] [pdf]

"Detecting heterogeneous treatment effects by combining observational and experimental data" (with Akos Lada)
[CODE@MIT] [pdf]

2016 Publications

"The Good, the Bad, and the Unflinchingly Selfish: Cooperative Decision-Making Can Be Predicted with High Accuracy Using Only Three Behavioral Types" (with Ziv Epstein and Dave Rand)
[EC2016] [pdf]

"Recency, Records and Recaps: Learning and Non-equilibrium Behavior in a Simple Decision Problem" (with Drew Fudenberg)
[EC2014, Transactions on Economics and Computation 2016] [pdf]

2015 Publications

"When Punishment Doesn't Pay: 'Cold Glow' and Decisions to Punish" (with Aurelie Ouss)
[Journal of Law and Economics] [pdf]

"Asymmetric Impacts of Favorable and Unfavorable Information on Decisions Under Ambiguity" (with Uma Karmarkar)
[Management Science] [pdf] [Journal Version] [Data and Code]

"Habits of Virtue: creating norms of cooperation and defection in the laboratory" (with David Rand)
[Management Science] [pdf] [Journal Version] [Data and Code]

2014 Publications

"Cooperating with the future" (with Oliver Hauser, David Rand and Martin Nowak) [Nature] [Published Version] [Data and Code] [Nature video summary]

"Humans display a 'cooperative phenotype' that is domain general and temporally stable" (with Martin Nowak and David Rand)
[Nature Comms] [pdf] [Journal Version] [Data and Code]

"Why We Cooperate" (with Jillian Jordan and David Rand)
[Chapter in “The Moral Brain: Multidisciplinary Perspectives”] [pdf]

"Social Heuristics Shape Intuitive Cooperation" (with David Rand, Gordon Kraft-Todd, George Newman, Owen Wurzbacher, Martin Nowak and Joshua Greene)
[Nature Comms] [pdf] [Journal Version] [Data and Code]

"How to Commit (If You Must): Commitment Contracts and the Dual-Self Model"
[Journal of Economic Behavior and Organization] [pdf] [Journal Version]

2012 Publications

"A Note on Proper Scoring Rules and Risk Aversion" (with Mikkel Plagborg-Moller)
[Economics Letters] [pdf] [Journal Version]

Popular Writing

"How Not To Drown In Numbers" (with Seth Stephens-Davidowitz)
[New York Times Op-Ed] [Web]

"Games Head to the Lab" (with David Rand)
[WIRED UK "The World in 2014"][pdf]

"Small is Good When It Comes to Data Creation" (with David Rand)
[WIRED UK "The World in 2013"] [pdf]

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