Algorithmic Fairness & Opacity Lecture Series

The Algorithmic Fairness & Opacity lecture series hosts speakers from industry and academia to engage in cross-disciplinary conversations related to fairness and opacity in algorithms. Lectures are sponsored by the Berkeley Algorithmic Fairness & Opacity Working Group (AFOG).

Previous events

Monday, May 13, 2019, 4:00 pm - 6:00 pm

A conversation about “humans in the loop” who invisibly deliver on-demand task-based services and the lives of the people paid to train artificial intelligence.

Wednesday, March 20, 2019, 3:30 pm - 5:00 pm

Eric Horvitz is a technical fellow and director at Microsoft Research.

Wednesday, February 27, 2019, 4:10 pm - 5:30 pm

Machine learning algorithms are not neutral observers of the world, but see what they are trained to see.

Thursday, November 29, 2018, 4:00 pm - 5:30 pm

The impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America.

Wednesday, October 31, 2018, 4:10 pm - 5:30 pm

Issa Kohler-Hausmann studies the methodological and theoretical issues in stating and proving discrimination claims.

Monday, April 30, 2018, 4:10 pm - 5:30 pm

What to do when software algorithms are designed for statistical fairness or legal compliance, but still seem unfair.

Monday, March 19, 2018, 4:10 pm - 5:30 pm

What does it mean for algorithmic classification to be fair, and how can we promote algorithmic fairness?

Monday, February 26, 2018, 4:10 pm - 5:30 pm

Angèle Christin documents a gap between the intended and actual effects of algorithms in two professions.

Monday, December 4, 2017, 4:10 pm - 5:30 pm

Dawn Nafus is a senior research scientist at Intel Labs, where she researches cultures of quantification and health and environmental sensing.