AI and Human Values: A Lecture on Fairness in Algorithmic Services

About This Event

Algorithmically guided decisions are becoming increasingly prevalent and, if left unchecked, can amplify pre-existing societal biases. In this talk, I use modern computational tools to examine the equity of decision-making in three complex systems: automated speech recognition, online advertising, and recommendation systems. Furthermore, I will propose processes to ameliorate demographic-based disparate impact arising from decisions made by online platforms. First, I demonstrate large racial disparities in the performance of popular commercial speech-to-text systems developed by big tech companies, a pattern likely stemming from a lack of diversity in the data used to train the systems. Second, I present a methodological framework for online advertisers to determine a demographically equitable allocation of individuals being shown ads for SNAP (food stamp) benefits. In particular, I discuss how to formulate fair decisions considering budget-constrained trade-offs between English-speak

Featured Guests

Allison Koenecke - Cornell University

Co-sponsors

Goergen Institute for Data Science, Department of Philosophy