I had the honor of being invited by the department of African American Studies to give the 2022 James Baldwin lecture. The series celebrates the work of a Princeton faculty member and invites them to reflect on the issue of race and democracy. The lectures also honor the work of the late essayist James Baldwin, one of America’s most powerful cultural critics.
The invitation mentioned the book on fairness and machine learning that I coauthored, and suggested that the lecture would be an opportunity for greater exchange between African American Studies and statistics/machine learning. After some soul searching, I decided that the lecture would reflect my disillusionment with quantitative methods that arose in large part through my work on the book. Many of the points in the lecture appear in the book, but in a more muted form. The lecture ends on a constructive note.
Citation: Narayanan, Arvind. "The limits of the quantitative approach to discrimination." James Baldwin lecture [transcript], Princeton University (2022).
Bibtex:
@misc{narayanan2022limits,
title={The limits of the quantitative approach to discrimination},
author={Narayanan, Arvind},
year={2022},
howpublished={{James Baldwin Lecture [transcript], Princeton University}}
}