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So for algorithms
that have the potential {\an1}to ruin people's lives
or sharply reduce their options
with their liberty, their livelihood,
or their finances, {\an1}we need an FDA for algorithms
that says, {\an1}"Hey, show me evidence
that it's going to work {\an1}"not just to make your...
You money, {\an1}"but it's gonna work
for society
that have the potential {\an1}to ruin people's lives
or sharply reduce their options
with their liberty, their livelihood,
or their finances, {\an1}we need an FDA for algorithms
that says, {\an1}"Hey, show me evidence
that it's going to work {\an1}"not just to make your...
You money, {\an1}"but it's gonna work
for society
Full Transcript
00:00:01.000 --> 00:00:02.976
So for algorithms
that have the potential
00:00:03.000 --> 00:00:05.976
{\an1}to ruin people's lives
or sharply reduce
00:00:06.000 --> 00:00:07.976
their options
with their liberty,
00:00:08.000 --> 00:00:09.976
their livelihood,
or their finances,
00:00:10.000 --> 00:00:11.976
{\an1}we need an FDA for algorithms
that says,
00:00:12.000 --> 00:00:14.976
{\an1}"Hey, show me evidence
that it's going to work
00:00:15.000 --> 00:00:16.976
{\an1}"not just to make your...
You money,
00:00:17.000 --> 00:00:19.976
{\an1}"but it's gonna work
for society.
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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...