- Computational Social Science
- Critical Data Studies
- Data Science
- Economics and Information
- Education Technology
- Ethics, Law and Policy
- Human-Computer Interaction
- Human-Robot Interaction
- Incentives and Computation
- Infrastructure Studies
- Interface Design and Ubiquitous Computing
- Natural Language Processing
- Network Science
- Social Computing and Computer-supported Cooperative Work
- Technology and Equity
Please join us for the Information Science Colloquium and co-sponsored by the Computer Science, Economics, and Sociology Departments with guest, Duncan Watts, Cornell University Andrew Dickson White Professor-at-Large and Principal Research Scientist at Microsoft Research Lab in New York City.
Talk Title: Long-run Learning in Games of Cooperation
Abstract: Cooperation in repeated games has been widely studied in experimental settings; however, the duration over which players participate in such experiments is typically confined to at most hours, and often to a single game. Given that in real world settings people may have years of experience, it is natural to ask how behavior in cooperative games evolves over the long run. Here we analyze behavioral data from three distinct games involving over 500 individual experiments conducted over a two-year interval. First, in the case of a standard linear public goods game we show that as players gain experience, they become less generous both on average and in particular towards the end of each game. Second, we analyze a multiplayer prisoner's dilemma where players are also allowed to make and break ties with their neighbors, finding that experienced players show an increase in cooperativeness early on in the game, but exhibit sharper ``endgame'' effects. Third, and finally, we analyze a collaborative search game in which players can choose to act selfishly or cooperatively, finding again that experienced players exhibit more cooperative behavior up to an endgame effect. Together these results show consistent evidence of long-run learning, but also highlight directions for future theoretical work that may account for the observed direction and magnitude of the effects.
Bio: Duncan Watts (2013-2019)—is considered to be among the vanguard in the area of network theory. Currently, he is Principal Researcher and founding member of Microsoft Research Lab in Manhattan. Prior to this assignment, he moved to Yahoo Research in 2007 where he directed the Human Social Dynamics Group and before that he taught sociology at Columbia University (2000-2007) where he received a full professorship (2007-2009).
He has reshaped the scientific understanding of the dynamics of social influence, challenging the conventional wisdom that focused on the attributes of “influencers” and pointing instead to the structural factors—as well as accidents—that affect the spread of new ideas, technical innovations, and even disease. He was one of the first to recognize and utilize the opportunities in web-enabled platforms through controlled experiments, allowing for larger and more diverse populations than would be possible under traditional settings. One innovative study, which examined downloads of music in multiple “worlds,” revealed that highly predictable outcomes based on social influence lead us to place too much confidence in “common sense” meanings we attribute to patterns. In fact, these are far less predictable in any particular world.
His PhD dissertation, The Structure and Dynamics of Small-World Systems illustrated how a very small number of random ties can give even highly clustered networks the connectivity of a completely random network. This seemingly technical discovery was a game changer that launched the evolution of “the new science of networks.” This explained the concept of the “six degrees of separation,” which had puzzled scientists for over 50 years following the 1929 publication of Hungarian author, Frigyes Karinthy’s short story “Chain-Links” that appeared in the collection Everything is Different. This inspired the title of Watt’s most recent trade book Everything is Obvious: How Common Sense Fails Us.
His scientific papers have appeared in leading journals, including Nature, Science, PNAS, Physical Review Letters, the Journal of Personality and Social Psychology, and the American Journal of Sociology, on topics spanning a wide range of disciplines including physics, math, sociology, computer science, economics, management, information science, epidemiology, molecular biology and neuroscience. Two of his books Six Degrees: The Science of a Connected Age (2004), and Small Worlds: The Structure of Dynamics of Networks between Order and Randomness (2003), have been widely credited for sparking the public fascination with networks.
Professor Watts’ innovative applications of network analysis and online data to the study of human behavior and social interaction has led him to become one of the most prominent and respected network scientists in the world. He holds a PhD from Cornell University in Theoretical and Applied Mechanics (1997)