Recent events have made evident the fact that algorithms can be discriminatory, reinforce human prejudices, accelerate the spread of misinformation, and are generally not as objective as they are widely thought to be. In this talk, I will present a vignette from my recent work which tackles the problem of discrimination in housing and employment via online ad platforms. Recent studies show that the audience an ad gets shown to can be discriminatory with respect to socially salient attributes such as gender and race, crossing ethical and legal boundaries. To mitigate this, we propose a constrained optimization framework that allows the platform to control the audience that an online ad auction gives to an advertiser in a manner that avoids discriminatory allocation. Finding the parameters of this optimal auction, however, turns out to be a non-convex problem. We show how we can leverage the structure of the problem to develop a fast algorithm to solve it, resulting in a new auction mechanism that has the potential to alleviate bias in online advertising while simultaneously maintaining good empirical performance with respect to revenue. We will further discuss the hurdles in implementing such an approach, yet the importance of doing so.
Link: Youtube Live
Elisa Celis is an Assistant Professor in the Statistics and Data Science department at Yale University. Her research focuses on problems that arise in the context of the Internet and its societal and economic implications. She approaches these problems by using both experimental and theoretical techniques. Her work spans multiple areas including social and computing crowdsourcing, data and network science, and mechanism design and algorithm with a current emphasis on fairness and diversity in artificial intelligence and machine learning. She has published articles in journals such as IEEE Transactions on Network Science and Engineering, Journal of Applied Network Science, Human Computation Journal, Management Science, SIAM Journal on Computing, among others. Before coming to Yale, she worked at the Ecole Polytechnique Federale de Lausanne as a senior research scientist since June of 2014. Celis holds a Ph.D. in Computer Science and Engineering and an M.Sc. in Mathematics, both from the University of Washington.