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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. 

Previous Events

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May 13, 2019, 4:00 pm to 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.
Eric Horvitz
Mar 20, 2019, 3:30 pm to 5:00 pm
Eric Horvitz is a technical fellow and director at Microsoft Research.
Hoyt Long
Feb 27, 2019, 4:10 pm to 5:30 pm
Machine learning algorithms are not neutral observers of the world, but see what they are trained to see.
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Nov 29, 2018, 4:00 pm to 5:30 pm
The impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America.
Issa Kohler-Hausmann
Oct 31, 2018, 4:10 pm to 5:30 pm
Issa Kohler-Hausmann studies the methodological and theoretical issues in stating and proving discrimination claims.
Christian Sandvig
Apr 30, 2018, 4:10 pm to 5:30 pm
What to do when software algorithms are designed for statistical fairness or legal compliance, but still seem unfair.
Jon Kleinberg
Mar 19, 2018, 4:10 pm to 5:30 pm
What does it mean for algorithmic classification to be fair, and how can we promote algorithmic fairness?
Angèle Christin
Feb 26, 2018, 4:10 pm to 5:30 pm
Angèle Christin documents a gap between the intended and actual effects of algorithms in two professions.
Dawn Nafus
Dec 4, 2017, 4:10 pm to 5:30 pm
Dawn Nafus is a senior research scientist at Intel Labs, where she researches cultures of quantification and health and environmental sensing.