Events
Data Science Distinguished Lecture Series | Nicole Immorlica
Information Provision in Markets
Tech-mediated markets give individuals an unprecedented number of opportunities. Students no longer need to attend their neighborhood school; through school choice programs they can apply to any school in their city. Tourists no longer need to wander streets looking for restaurants; they can select among them on an app from the comfort of their hotel rooms. Theoretically, this increased access improves outcomes. However, realizing these potential gains requires individuals to be able to navigate their options and make informed decisions. In this talk, we explore how markets can help guide individuals through this process by providing relevant information. We first discuss a school choice market where students must exert costly effort to learn their preferences. We show that posting exam score cutoffs breaks information deadlocks allowing students to efficiently evaluate their options. We next study a recommendation app which can selectively reveal past reviews to users. We show that it’s possible to facilitate learning across users by creating a hierarchical network structure in which early users explore and late users exploit the results of this exploration.
Speaker Bio
Nicole Immorlica received her PhD in 2005 from MIT, joined Northwestern University as a professor in 2008, and joined Microsoft Research New England (MSR NE) in 2012 where she currently leads the economics and computation group. She is the recipient of a number of fellowships and awards including the Sloan Fellowship, the Microsoft Faculty Fellowship and the NSF CAREER Award. She has been on several boards including SIGecom, SIGACT, the Game Theory Society, and OneChronos; is an associate editor of Operations Research, Games and Economic Behavior and Transactions on Economics and Computation; and was program committee member and chair for several ACM, IEEE and INFORMS conferences in her area. In her research, Nicole uses tools and modeling concepts from computer science and economics to explain, predict, and shape behavioral patterns in various online and offline markets. She is known for her work on mechanism design, market design and social networks.