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Coded Bias

Coded Bias poster
★ ★ ★ ★ ★
IMDb
6.8
Metascore
73
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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...
Director
Shalini Kantayya
Year
2020
Genre
documentary
Box Office
$10,236
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
Awards
3 wins & 6 nominations
Homepage
https://www.codedbias.com/
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{\an1}- So I've been following what's going on in Hong Kong - Coded Bias 00:13
{\an1}- So I've been following what's going on in ...
[dramatic music] - Coded Bias 00:09
[dramatic music]
{\an8}Laser pointers confuse and disable - Coded Bias 00:10
{\an8}Laser pointers confuse and disable
{\an7}[indistinct shouting] - Coded Bias 00:14
{\an7}[indistinct shouting]
{\an1}- Here on the streets of Hong Kong - Coded Bias 00:09
{\an1}- Here on the streets of Hong Kong
There was just this stark symbol - Coded Bias 00:10
There was just this stark symbol
{\an8}This act showed the people of Hong Kong - Coded Bias 00:09
{\an8}This act showed the people of Hong Kong
{\an7}- [indistinct speech] - Coded Bias 00:17
{\an7}- [indistinct speech]
{\an1}- When you see how facial recognition is being deployed - Coded Bias 00:12
{\an1}- When you see how facial recognition is being deploye...
[bird squawking] - Coded Bias 00:08
[bird squawking]
{\an1}has their face in a facial recognition network - Coded Bias 00:11
{\an1}has their face in a facial recognition network
{\an1}And without safeguards, - Coded Bias 00:12
{\an1}And without safeguards,
People look at what's going on in China - Coded Bias 00:19
People look at what's going on in China
{\an7}AI is being developed along two very, very different tracks. - Coded Bias 00:05
{\an7}AI is being developed along two very, very different t...
{\an1}If a Chinese citizen wants to get Internet service, - Coded Bias 00:08
{\an1}If a Chinese citizen wants to get Internet service,
[cell phone chimes] - Coded Bias 00:08
[cell phone chimes]
Conversely, in the United States, - Coded Bias 00:20
Conversely, in the United States,
[indistinct chatter] - Coded Bias 00:15
[indistinct chatter]
{\an1}- Here at Atlantic Towers, if you do something - Coded Bias 00:11
{\an1}- Here at Atlantic Towers, if you do something
They'll circle you and put your apartment number - Coded Bias 00:07
They'll circle you and put your apartment number
Something about it just doesn't seem right, - Coded Bias 00:07
Something about it just doesn't seem right,
The landlord filed an application last year - Coded Bias 00:11
The landlord filed an application last year
{\an7}- We thought that they wanted to take the key fobs out - Coded Bias 00:07
{\an7}- We thought that they wanted to take the key fobs out
{\an8}I didn't find out until way later on, literally, - Coded Bias 00:10
{\an8}I didn't find out until way later on, literally,
{\an1}- There's this old saw in science fiction - Coded Bias 00:06
{\an1}- There's this old saw in science fiction
{\an8}It's just not evenly distributed, - Coded Bias 00:33
{\an8}It's just not evenly distributed,
{\an7}- Why did Mr. Nelson pick on this building in Brownsville - Coded Bias 00:08
{\an7}- Why did Mr. Nelson pick on this building in Brownsvi...
{\an7}Why didn't you go to your building in Lower Manhattan - Coded Bias 00:07
{\an7}Why didn't you go to your building in Lower Manha...
{\an7}They wrote on people's arms so that they could track them. - Coded Bias 00:05
{\an7}They wrote on people's arms so that they could tr...
{\an1}I feel that I as a human being should not be tracked, okay? - Coded Bias 00:05
{\an1}I feel that I as a human being should not be tracked, ...
{\an1}- My real question is, how can I be of support? - Coded Bias 00:05
{\an1}- My real question is, how can I be of support?
- Mm-hmm. - So I think the goal here - Coded Bias 00:07
- Mm-hmm. - So I think the goal here
[soft music]] - Coded Bias 00:10
[soft music]]
{\an1}We have AI influencing - Coded Bias 00:08
{\an1}We have AI influencing
{\an1}So what you are seeing in your feeds, - Coded Bias 00:12
{\an1}So what you are seeing in your feeds,
{\an1}And so your view of the world - Coded Bias 00:08
{\an1}And so your view of the world
{\an1}- You might use something like Snapchat filters - Coded Bias 00:07
{\an1}- You might use something like Snapchat filters
And then you also have algorithms - Coded Bias 00:10
And then you also have algorithms
{\an1}You can have algorithms that are trying to determine - Coded Bias 00:08
{\an1}You can have algorithms that are trying to determine
{\an7}- One of Apple's cofounders is accusing the company's - Coded Bias 00:07
{\an7}- One of Apple's cofounders is accusing the compa...
{\an7}One tech entrepreneur said - Coded Bias 00:06
{\an7}One tech entrepreneur said
{\an8}- Apple cofounder Steve Wozniak tweeted that - Coded Bias 00:10
{\an8}- Apple cofounder Steve Wozniak tweeted that
{\an8}- Really? - How do we get justice - Coded Bias 00:06
{\an8}- Really? - How do we get justice
{\an1}- Some Amazon engineers decided that they were going to use AI - Coded Bias 00:08
{\an1}- Some Amazon engineers decided that they were going t...
{\an1}- Amazon is learning a tough lesson - Coded Bias 00:05
{\an1}- Amazon is learning a tough lesson
{\an1}The company has now abandoned an AI recruiting tool - Coded Bias 00:10
{\an1}The company has now abandoned an AI recruiting tool
{\an1}- This model rejected all résumés from women. - Coded Bias 00:06
{\an1}- This model rejected all résumés from women.
{\an1}Anybody who had a women's college on their résumé, - Coded Bias 00:12
{\an1}Anybody who had a women's college on their résumé...
{\an1}There are very, very few women - Coded Bias 00:12
{\an1}There are very, very few women
{\an1}The machine was simply - Coded Bias 00:11
{\an1}The machine was simply
{\an1}They're only making decisions that are mathematical. - Coded Bias 00:05
{\an1}They're only making decisions that are mathematic...
If we use machine learning models - Coded Bias 00:09
If we use machine learning models
{\an1}It's one of the latest examples - Coded Bias 00:08
{\an1}It's one of the latest examples
[soft music] - Coded Bias 00:11
[soft music]
{\an1}The progress that was made in the Civil Rights era - Coded Bias 00:09
{\an1}The progress that was made in the Civil Rights era
[indistinct chatter] - Coded Bias 00:09
[indistinct chatter]
{\an1}Right now we have an algorithm - Coded Bias 00:07
{\an1}Right now we have an algorithm
{\an1}If we're not checking, that algorithm could actually - Coded Bias 00:11
{\an1}If we're not checking, that algorithm could actua...
{\an8}[Claude Debussy's "Clair de lune"] - Coded Bias 00:14
{\an8}[Claude Debussy's "Clair de lune"]
{\an1}So the name of our organization is Big Brother Watch, - Coded Bias 00:11
{\an1}So the name of our organization is Big Brother Watch,
{\an1}"You had to live... did live, - Coded Bias 00:07
{\an1}"You had to live... did live,
{\an1}"in the assumption that every sound you made was overheard, - Coded Bias 00:09
{\an1}"in the assumption that every sound you made was ...
{\an1}"The poster with the enormous face gazed from the wall. - Coded Bias 00:05
{\an1}"The poster with the enormous face gazed from the...
{\an1}"It was one of those pictures which is so contrived - Coded Bias 00:06
{\an1}"It was one of those pictures which is so contriv...
{\an1}'Big Brother is watching you, ' the caption beneath it ran." - Coded Bias 00:09
{\an1}'Big Brother is watching you, ' the caption ...
{\an1}It could never have been true, and now it's completely true, - Coded Bias 00:10
{\an1}It could never have been true, and now it's compl...
Everything we do on the Internet, - Coded Bias 00:12
Everything we do on the Internet,
{\an1}We are now living in the awareness of being watched, - Coded Bias 00:09
{\an1}We are now living in the awareness of being watched,
[soft music] - Coded Bias 00:17
[soft music]
Internet advertising as data scientists - Coded Bias 00:24
Internet advertising as data scientists
{\an1}We can get rid of the viscerally horrible things - Coded Bias 00:11
{\an1}We can get rid of the viscerally horrible things
{\an1}But the cameras that we can't see on the Internet - Coded Bias 00:13
{\an1}But the cameras that we can't see on the Internet
[gentle music] - Coded Bias 00:13
[gentle music]
{\an1}That's just the way we act as a society, - Coded Bias 00:08
{\an1}That's just the way we act as a society,
{\an1}On internet advertising, as data scientists, - Coded Bias 00:11
{\an1}On internet advertising, as data scientists,
So payday lenders or for-profit colleges - Coded Bias 00:06
So payday lenders or for-profit colleges
We have a practice on the Internet - Coded Bias 00:08
We have a practice on the Internet
[dramatic music] - Coded Bias 00:10
[dramatic music]
When you start to piece together - Coded Bias 00:10
When you start to piece together
{\an7}It's that idea that a company - Coded Bias 00:07
{\an7}It's that idea that a company
{\an7}States have tried for years - Coded Bias 00:10
{\an7}States have tried for years
{\an7}We have to think about how this might be used - Coded Bias 00:05
{\an7}We have to think about how this might be used
{\an1}- John Anderton, you could use a Guinness right about now. - Coded Bias 00:06
{\an1}- John Anderton, you could use a Guinness right about ...
- Our computers, our machine intelligence - Coded Bias 00:06
- Our computers, our machine intelligence
Machine learning is developing very rapidly, - Coded Bias 00:12
Machine learning is developing very rapidly,
[tense music] - Coded Bias 00:14
[tense music]
Maybe you have set of compulsive gamblers, - Coded Bias 00:16
Maybe you have set of compulsive gamblers,
{\an1}In the online world, - Coded Bias 00:12
{\an1}In the online world,
{\an1}Machine learning can find that person by person. - Coded Bias 00:05
{\an1}Machine learning can find that person by person.
In 2010, - Coded Bias 00:08
In 2010,
PrevPage of 5Next
Coded Bias poster
★ ★ ★ ★ ★
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...

User Rating: 0.0 (0 ratings)
Director: Shalini Kantayya
Writer: Christopher Seward, Paul Rachman, Kurt Engfehr
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
Genre: documentary
Year: 2020
MetaScore: 73/100
ImdbRating: 6.8
BoxOffice: $10,236
Released: 11 Nov 2020
Awards: 3 wins & 6 nominations
Homepage: https://www.codedbias.com/
Also watch: Joji, Canadian Bacon, The Year Earth Changed, Mr. Harrigan's Phone, The Fundamentals of Caring, Transporter 3, Scooby Doo, Nobody, Interstellar, Black Panther: Wakanda Forever, Oppenheimer, Me Before You, Evil Dead Rise, Joker, Thor: Ragnarok, Avatar: The Way of Water, Poor Things

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