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Madeleine Clare Elish

Post written by: Zoe Kahn and Emma Lurie  On February 24th, the Algorithmic Fairness and Opacity Working Group (AFOG) hosted Madeleine Clare Elish, who leads the AI on the Ground Initiative at Data and Society. Elish shared two papers, “The Read more…

By admin, 5 yearsJune 17, 2020 ago
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Sava Saheli Singh

Post Written By: Shazeda Ahmed  On February 10th, the Algorithmic Fairness and Opacity Working Group (AFOG) hosted Sava Saheli Singh, a Postdoctoral Fellow in the Department of Criminology at the University of Ottawa. Saheli Singh screened three short fictional films she and Read more…

By admin, 5 yearsFebruary 21, 2020 ago
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Report from the first AFOG Summer Workshop

Click here for full report as PDF In June of 2018, the Algorithmic Fairness and Opacity Working Group (AFOG) held a summer workshop with the theme “Algorithms are Opaque and Unfair: Now What?.” The event was organized by Berkeley I Read more…

By Jenna Burrell, 7 yearsAugust 13, 2018 ago
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Explainable Machine Learning for Public Policy

NOTE: this reports on an AFOG relevant ISchool final project for the Master of Information Management and Systems (MIMS) program. The project was developed by a student team composed of Samuel Meyer, Shrestha Mohanty, Sung Joo Son, and Monicah Wambugu. Read more…

By Jenna Burrell, 7 yearsJune 4, 2018 ago
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How might the history of AI help us think about and critique Wang and Kosinsky’s “gaydar” study?

Note: The following is a re-post of AFOG member Shreeharsh Kelkar’s September 25, 2017 post on Scatterplot responding to the controversy over Wang and Kosinski’s (2018) paper about using deep neural networks to recognize “gay” or “straight” faces. At the Read more…

By , 7 years ago
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Seeing Through the Fog

Welcome to the AFOG Blog! We will use this space to post what we hope are accessible and provocative think pieces and reactions to academic research and news stories. Posts about what? Allow us to use this initial blog post Read more…

By , 7 yearsMarch 19, 2018 ago
Recent Posts
  • Madeleine Clare Elish
  • Sava Saheli Singh
  • Report from the first AFOG Summer Workshop
  • Explainable Machine Learning for Public Policy
  • How might the history of AI help us think about and critique Wang and Kosinsky’s “gaydar” study?
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The Algorithmic Fairness and Opacity Working Group
is located within the School of Information at UC Berkeley, and is funded by a research gift from Google to support cross-disciplinary academic research and conversations between industry and academia to explore and address issues related to fairness and opacity in algorithms.

Website designed and developed by Rohit Raghavan.

RECENT POSTS
  • Madeleine Clare Elish
  • Sava Saheli Singh
  • Report from the first AFOG Summer Workshop
  • Explainable Machine Learning for Public Policy
  • How might the history of AI help us think about and critique Wang and Kosinsky’s “gaydar” study?
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