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Coded Bias

There were some vulnerabilities {\an1}and holes in the code, {\an1}and so within a very...

There were some vulnerabilities {\an1}and holes in the code, {\an1}and so within a very few hours, Tay was learning
from this ecosystem, {\an1}and Tay learned how to be
a racist, misogynistic [bleep]

Full Transcript

00:00:01.000 --> 00:00:01.977
There were some vulnerabilities
00:00:02.989 --> 00:00:03.976
{\an1}and holes in the code,
00:00:04.000 --> 00:00:06.976
{\an1}and so within a very few hours,
00:00:07.000 --> 00:00:12.976
Tay was learning from this ecosystem,
00:00:13.000 --> 00:00:18.000
{\an1}and Tay learned how to be a racist, misogynistic [bleep].
Duration
18 seconds
Views
30
Timestamp in Movie
00:39:39
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...
{\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]
Turns out Amazon, like all of its peers, - Coded Bias 00:10
Turns out Amazon, like all of its peers,
- Introducing Amazon Rekognition Video, - Coded Bias 00:11
- Introducing Amazon Rekognition Video,
{\an1}Recognize and track persons of interest - Coded Bias 00:07
{\an1}Recognize and track persons of interest
{\an1}- When our research came out, "The New York Times" - Coded Bias 00:07
{\an1}- When our research came out, "The New York Times...
{\an1}And the headline reads, - Coded Bias 00:25
{\an1}And the headline reads,
- People were like, "How did you even, like, - Coded Bias 00:07
- People were like, "How did you even, like,
{\an1}Like, I did... I wasn't able to use a lot of, like, - Coded Bias 00:15
{\an1}Like, I did... I wasn't able to use a lot of, lik...
{\an1}The lead author of the paper, who is somebody that I mentor, - Coded Bias 00:09
{\an1}The lead author of the paper, who is somebody that I m...
[dramatic music] - Coded Bias 00:10
[dramatic music]
{\an1}Amazon has been under fire for the use of - Coded Bias 00:12
{\an1}Amazon has been under fire for the use of
{\an1}So Amazon trialing their AI technology with the FBI. - Coded Bias 00:05
{\an1}So Amazon trialing their AI technology with the FBI.