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{\an8}I started looking
at the data sets themselves, {\an1}and what I discovered
is many of these data sets {\an1}contained majority men and majority
lighter-skinned individuals, {\an1}so the systems weren't as
familiar with faces like mine
at the data sets themselves, {\an1}and what I discovered
is many of these data sets {\an1}contained majority men and majority
lighter-skinned individuals, {\an1}so the systems weren't as
familiar with faces like mine
Full Transcript
00:00:01.000 --> 00:00:03.976
{\an8}I started looking
at the data sets themselves,
00:00:04.000 --> 00:00:06.976
{\an1}and what I discovered
is many of these data sets
00:00:07.000 --> 00:00:08.976
{\an1}contained majority men
00:00:09.000 --> 00:00:10.976
and majority
lighter-skinned individuals,
00:00:11.000 --> 00:00:15.976
{\an1}so the systems weren't as
familiar with faces like mine.
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Movie Summary
When MIT Media Lab researcher Joy Buolamwini discovers that facial recognition does not see dark-skinned faces accurately, she embarks on a journey to push for the first-ever U.S. legislation against bias in algorithms that impact...