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January 28 @ 5:30 pm
Coded Bias virtual documentary film screening (1h 30m) and panel discussion sponsored by UCSC’s Privacy Office and Office for Diversity, Equity, and Inclusion, and sponsored by Digital Arts and New Media (DANM), Humanities Institute, Center for Racial Justice, Institute for Social Transformation, Center for Information Technology Research in the Interest of Society and the Banatao Institute (CITRIS), Baskin Engineering, Data Science Research Center, Center for Innovations in teaching and learning (CITL), and the office of Campus Counsel.
A virtual panel discussion featuring Professors Neda Atanasoski of the Humanities Institute Center for Racial Justice, A.M. Darke of Digital Arts and New Media (DANM), and Jody Greene of Center for Innovations in Teaching and Learning (CITL) will be held at 5:30PM on January 28, 2021. Registration for the event includes RSVP for the panel discussion as well as viewing access to the film. The link to view the film will be sent out to registered guests on January 25 for viewing between January 25-28.
Professor Neda Atanasoski of the Humanities Institute Center for Racial Justice
Professor A.M. Darke of Digital Arts and New Media (DANM)
Professor Jody Greene of Center for Innovations in Teaching and Learning (CITL)
The award winning documentary “Coded Bias” explores how machine-learning algorithms can perpetuate society’s existing class-, race-, and gender-based inequities.
While working on an assignment involving facial-recognition software, the M.I.T. Media Lab researcher Joy Buolamwini found that the algorithm couldn’t detect her face — until she put on a white mask. As she recounts in the documentary “Coded Bias,” Buolamwini soon discovered that most such artificial-intelligence programs are trained to identify patterns based on data sets that skew light-skinned and male. “When you think of A.I., it’s forward-looking,” she says. “But A.I. is based on data, and data is a reflection of our history.” “Coded Bias” tackles its sprawling subject by zeroing in empathetically on the human costs.
“Coded Bias” examines algorithmic bias as a modern civil rights issue, and sheds light on privacy and equity issues related to increasing reliance on artificial intelligence.