Date: Wednesday, October 26th, 2022
9:00 am – 10:00 am Pacific Time
12:00 pm – 1:00 pm Eastern Time
Location: Weekly Seminar, Zoom
Title: Information Discrepancy in Strategic Learning
Abstract:
We initiate the study of the effects of non-transparency in decision rules on individuals’ ability to improve in strategic learning settings. Inspired by real-life settings, such as loan approvals and college admissions, we remove the assumption typically made in the strategic learning literature, that the decision rule is fully known to individuals, and focus instead on settings where it is inaccessible. In their lack of knowledge, individuals try to infer this rule by learning from their peers (e.g., friends and acquaintances who previously applied for a loan), naturally forming groups in the population, each with possibly different type and level of information regarding the decision rule. We show that, in equilibrium, the principal’s decision rule optimizing welfare across subpopulations may cause a strong negative externality: the true quality of some of the groups can actually deteriorate. On the positive side, we show that, in many natural cases, optimal improvement can be guaranteed simultaneously for all sub-populations. We further introduce a measure we term information overlap proxy, and demonstrate its usefulness in characterizing the disparity in improvements across sub-populations. Finally, we identify a natural condition under which improvement can be guaranteed for all sub-populations while maintaining high predictive accuracy. We complement our theoretical analysis with experiments on real-world datasets.
Bio:
Chara Podimata is currently a FODSI postdoctoral fellow at UC Berkeley and is joining MIT Sloan as an Assistant Professor of OR/Stat in Fall 2023. She received her PhD from Harvard, advised by Yiling Chen. She is interested in social aspects of computing and more specifically, the effects of humans adapting to machine learning algorithms used for consequential decision making. During her PhD, she interned at MSR and Google and her research was supported by a Microsoft Dissertation Grant and a Siebel Scholarship. Outside of research, she spends her time adventuring with her pup, Terra.