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June 2018

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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. Students from the team participated in the AFOG lunch working Read more…

By Jenna Burrell, 7 yearsJune 4, 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.

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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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