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{\an1}[talking over each other]
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Coded Bias

{\an1} {\an1}- It was in about 2012 {\an1}when somebody suggested to me {\an1}that I...

{\an1}[talking over each other] {\an1}- It was in about 2012 {\an1}when somebody suggested to me {\an1}that I should find out
if I had files kept on me by the police
or the security services, {\an1}and so when I applied, I found {\an1}that I was on the watch list
for domestic extremists

Full Transcript

00:00:01.000 --> 00:00:01.975
{\an1}[talking over each other]
00:00:02.000 --> 00:00:02.975
{\an1}- It was in about 2012
00:00:03.000 --> 00:00:03.977
{\an1}when somebody suggested to me
00:00:04.003 --> 00:00:07.975
{\an1}that I should find out if I had files kept on me
00:00:08.000 --> 00:00:09.975
by the police or the security services,
00:00:10.000 --> 00:00:11.975
{\an1}and so when I applied, I found
00:00:12.000 --> 00:00:14.975
{\an1}that I was on the watch list for domestic extremists.
Duration
15 seconds
Views
20
Timestamp in Movie
01:08:55
Uploaded
May 26, 2025
Genres
documentary
Production
7th Empire Media,Independent Lens,ITVS,JustFilms / Ford Foundation,Chicken & Egg Films,Women Make Movies,The Alfred P. Sloan Foundation Production Grant,Sundance Institute

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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...
{\an1}I felt if they can do it to me - Coded Bias 00:17
{\an1}I felt if they can do it to me
- You know this is the first challenge - Coded Bias 00:14
- You know this is the first challenge
[laughs] - Coded Bias 00:16
[laughs]
{\an7}It says that the individuals have a right - Coded Bias 00:09
{\an7}It says that the individuals have a right
Comparatively, it's the wild west in America, - Coded Bias 00:10
Comparatively, it's the wild west in America,
{\an1}American citizens are profiled and targeted in a way - Coded Bias 00:12
{\an1}American citizens are profiled and targeted in a way
{\an1}[indistinct shouting] - Coded Bias 00:32
{\an1}[indistinct shouting]
{\an1}So it's not, "What will AI do to us on its own?" - Coded Bias 00:18
{\an1}So it's not, "What will AI do to us on its o...
{\an1}In a letter to Amazon, - Coded Bias 00:06
{\an1}In a letter to Amazon,
{\an1}- This comes after the ACLU - Coded Bias 00:15
{\an1}- This comes after the ACLU
Some lawmakers have - Coded Bias 00:07
Some lawmakers have
{\an1}This is a boarding call for - Coded Bias 00:08
{\an1}This is a boarding call for
- Tomorrow I have the opportunity to testify - Coded Bias 00:10
- Tomorrow I have the opportunity to testify
{\an1}[soft ambient music] - Coded Bias 00:15
{\an1}[soft ambient music]
{\an1}Like, actually advising on legislation, that's a first. - Coded Bias 00:05
{\an1}Like, actually advising on legislation, that's a ...
What are some of the major goals - Coded Bias 00:06
What are some of the major goals
{\an8}- So first of all, - Coded Bias 00:11
{\an8}- So first of all,
{\an8}- Right. - And so, you know, - Coded Bias 00:10
{\an8}- Right. - And so, you know,
- And so part of... If I were you, - Coded Bias 00:15
- And so part of... If I were you,
[indistinct chatter] - Coded Bias 00:24
[indistinct chatter]