Ad delivery algorithms play an important role in shaping access to information and economic opportunities. However, the opaque nature of these algorithms to both users and advertisers has raised societal concerns about bias and discrimination. These concerns have led to increased scrutiny through research, civil rights audits, and regulation. In this talk, we present findings from our black-box audit of ad delivery algorithms that reveal bias in the delivery of ads for employment and education opportunities. We then discuss steps that platforms have taken to mitigate bias in response to academic and legal scrutiny. We conclude with open questions surrounding these efforts and paths forward for future research.

Bio:

Basileal Imana’s research interests broadly lie in studying privacy and algorithmic fairness properties of real-world systems on the Internet. He focuses on developing novel methods for auditing the fairness of algorithms used to deliver content on social media platforms without introducing new privacy risks to platforms or users.

Imana received his Ph.D. in computer science from the University of Southern California. Prior to USC, he received his BSc in 2017, also in CS, from Trinity College Connecticut, where he worked on solving computationally difficult problems using high-performance computing.

In-person attendance is open to Princeton University faculty, staff and students. This seminar will not be livestreamed, the recording will be available upon request.

If you need an accommodation for a disability please contact Jean Butcher at butcher@princeton.edu at least one week before the event.

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