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{\an7}People couldn't be in certain areas after dark, for instance
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Coded Bias

{\an7}People couldn't be in certainareas after dark, for instance, {\an1}and you could...

{\an7}People couldn't be in certain
areas after dark, for instance, {\an1}and you could always be stopped
by a policeman arbitrarily {\an1}who would, on your appearance,
say, "I want your passport." {\an1}- So instead of having
what you see in the ID books, {\an1}now you have computers
that are going to {\an1}look at an image of a face and try to determine
what your gender is

Full Transcript

00:00:01.000 --> 00:00:04.976
{\an7}People couldn't be in certain areas after dark, for instance,
00:00:05.000 --> 00:00:08.976
{\an1}and you could always be stopped by a policeman arbitrarily
00:00:09.000 --> 00:00:14.000
{\an1}who would, on your appearance, say, "I want your passport."
00:00:15.000 --> 00:00:17.976
{\an1}- So instead of having what you see in the ID books,
00:00:18.000 --> 00:00:19.976
{\an1}now you have computers that are going to
00:00:20.000 --> 00:00:21.976
{\an1}look at an image of a face
00:00:22.000 --> 00:00:23.976
and try to determine what your gender is.
Duration
24 seconds
Views
33
Timestamp in Movie
01:01:41
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}Some of them try to determine what your ethnicity is. - Coded Bias 00:05
{\an1}Some of them try to determine what your ethnicity is.
- And in the work that I've done, - Coded Bias 00:07
- And in the work that I've done,
{\an1}And so that's not just for face classification, - Coded Bias 00:07
{\an1}And so that's not just for face classification,
{\an1}And so people assume, - Coded Bias 00:06
{\an1}And so people assume,
{\an1}- Humans are creating themselves in their own image - Coded Bias 00:05
{\an1}- Humans are creating themselves in their own image
- Absolutely. - Racism is becoming - Coded Bias 00:06
- Absolutely. - Racism is becoming
[dramatic music] - Coded Bias 00:20
[dramatic music]
{\an1}Even if I'm perfectly classified, - Coded Bias 00:06
{\an1}Even if I'm perfectly classified,
{\an8}[foreboding music] - Coded Bias 00:15
{\an8}[foreboding music]
They're sort of explicitly saying, - Coded Bias 00:06
They're sort of explicitly saying,
"Whatever you say about the Communist Party - Coded Bias 00:05
"Whatever you say about the Communist Party
"Also, by the way, it will affect - Coded Bias 00:07
"Also, by the way, it will affect
The government who's building this - Coded Bias 00:09
The government who's building this
[car horns honking] - Coded Bias 00:09
[car horns honking]
{\an8}♪ ♪ - Coded Bias 00:08
{\an8}♪ ♪
- We look at China - Coded Bias 00:16
- We look at China
{\an1}We are all grappling every day with algorithmic determinism. - Coded Bias 00:06
{\an1}We are all grappling every day with algorithmic determ...
{\an1}Somebody's algorithm somewhere has assigned you a score, - Coded Bias 00:09
{\an1}Somebody's algorithm somewhere has assigned you a...
You are being shown better or worse mortgages. - Coded Bias 00:06
You are being shown better or worse mortgages.
{\an1}You are more or less likely to be profiled as a criminal - Coded Bias 00:07
{\an1}You are more or less likely to be profiled as a crimin...