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When I was 14, I went to a math camp
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Coded Bias

When I was 14,I went to a math camp {\an1}and learned how to solvea Rubik's Cube, and I...

When I was 14,
I went to a math camp {\an1}and learned how to solve
a Rubik's Cube, and I was like,
"That's freaking cool." {\an1}Like, for a nerd, you know, {\an1}something that you're good at {\an1}and that doesn't have
any sort of ambiguity, {\an1}it was, like, a really...
A magical thing

Full Transcript

00:00:01.000 --> 00:00:02.976
- When I was 14, I went to a math camp
00:00:03.000 --> 00:00:04.976
{\an1}and learned how to solve a Rubik's Cube,
00:00:05.000 --> 00:00:07.976
and I was like, "That's freaking cool."
00:00:08.000 --> 00:00:10.976
{\an1}Like, for a nerd, you know,
00:00:11.000 --> 00:00:11.977
{\an1}something that you're good at
00:00:12.945 --> 00:00:15.976
{\an1}and that doesn't have any sort of ambiguity,
00:00:16.000 --> 00:00:18.976
{\an1}it was, like, a really... A magical thing.
Duration
19 seconds
Views
26
Timestamp in Movie
00:46:54
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}Like, I remember being told - Coded Bias 00:23
{\an1}Like, I remember being told
{\an8}It was 2006, - Coded Bias 00:08
{\an8}It was 2006,
{\an1}I didn't know anything about programming - Coded Bias 00:06
{\an1}I didn't know anything about programming
{\an1}When I first got there, I kind of drank the Kool-Aid. - Coded Bias 00:05
{\an1}When I first got there, I kind of drank the Kool-Aid.
I, at that moment, did not realize - Coded Bias 00:07
I, at that moment, did not realize
{\an1}For example, when Americans are bet against - Coded Bias 00:11
{\an1}For example, when Americans are bet against
{\an1}So it's, like, looking for a particular profile of people - Coded Bias 00:13
{\an1}So it's, like, looking for a particular profile o...
{\an1}That was an algorithmic game that came out of Wall Street. - Coded Bias 00:05
{\an1}That was an algorithmic game that came out of Wall Str...
{\an1}The tyranny of these types of practices of discrimination - Coded Bias 00:09
{\an1}The tyranny of these types of practices of discriminat...
{\an8}- There was a world of suffering - Coded Bias 00:06
{\an8}- There was a world of suffering
{\an7}After a couple years there, I was like, - Coded Bias 00:11
{\an7}After a couple years there, I was like,
{\an7}This is 15 times... 7. - Coded Bias 00:08
{\an7}This is 15 times... 7.
I use data to make automated decisions - Coded Bias 00:10
I use data to make automated decisions
{\an1}Sometimes you don't even know - Coded Bias 00:05
{\an1}Sometimes you don't even know
I am called mathematical model, - Coded Bias 00:11
I am called mathematical model,
I am a black box. - Coded Bias 00:05
I am a black box.
[indistinct chatter] - Coded Bias 00:11
[indistinct chatter]
I got wind of it because my good friend - Coded Bias 00:07
I got wind of it because my good friend
- Hey, guys. - We knew each other - Coded Bias 00:05
- Hey, guys. - We knew each other
- And their scores through this algorithm - Coded Bias 00:08
- And their scores through this algorithm