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{\an1}One Facebook message shown just once
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Coded Bias

{\an1}One Facebook messageshown just once {\an1}could easily turn out three times the...

{\an1}One Facebook message
shown just once {\an1}could easily turn out three times the number of people {\an1}who swung the U.S. election
in 2016

Full Transcript

00:00:01.000 --> 00:00:03.976
{\an1}One Facebook message shown just once
00:00:04.000 --> 00:00:06.976
{\an1}could easily turn out
00:00:07.000 --> 00:00:08.976
three times the number of people
00:00:09.000 --> 00:00:13.000
{\an1}who swung the U.S. election in 2016.
Duration
13 seconds
Views
24
Timestamp in Movie
00:36:43
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}Let's say that there's a politician that's promising - Coded Bias 00:22
{\an1}Let's say that there's a politician that...
{\an1}Maybe with a heavier touch they can swing - Coded Bias 00:12
{\an1}Maybe with a heavier touch they can swing
[low ambient music] - Coded Bias 00:07
[low ambient music]
{\an7}I think about nine years old I saw the Media Lab on TV, - Coded Bias 00:10
{\an7}I think about nine years old I saw the Media Lab on TV...
{\an1}It could smile and move its ears in cute ways, - Coded Bias 00:13
{\an1}It could smile and move its ears in cute ways,
{\an7}I thought you kinda showed up, but here I am now. - Coded Bias 00:05
{\an7}I thought you kinda showed up, but here I am now.
{\an8}[both laugh] - Coded Bias 00:11
{\an8}[both laugh]
{\an1}I wanted to create something - Coded Bias 00:06
{\an1}I wanted to create something
I'm excited about what it could do, - Coded Bias 00:09
I'm excited about what it could do,
{\an1}[soft dramatic music] - Coded Bias 00:17
{\an1}[soft dramatic music]
There were some vulnerabilities - Coded Bias 00:18
There were some vulnerabilities
{\an7}- I [bleep] hate feminists, - Coded Bias 00:05
{\an7}- I [bleep] hate feminists,
{\an7}- It did not take long for internet trolls - Coded Bias 00:06
{\an7}- It did not take long for internet trolls
{\an7}- It's important to note it's not the movie - Coded Bias 00:05
{\an7}- It's important to note it's not the movie
{\an7}These were human beings training them, - Coded Bias 00:07
{\an7}These were human beings training them,
{\an1}- Microsoft shut Tay off - Coded Bias 00:12
{\an1}- Microsoft shut Tay off
{\an1}Many companies utilize me to optimize their tasks. - Coded Bias 00:06
{\an1}Many companies utilize me to optimize their tasks.
I am listening. I am learning. - Coded Bias 00:06
I am listening. I am learning.
{\an1}I am making predictions for your life right now. - Coded Bias 00:05
{\an1}I am making predictions for your life right now.
{\an1}[thrumming tense music] - Coded Bias 00:11
{\an1}[thrumming tense music]