Ajouter une intrigue dans votre langueWhen 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. legislatio... Tout lireWhen 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 us all.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 us all.
- Réalisation
- Scénario
- Casting principal
- Récompenses
- 3 victoires et 6 nominations au total
- Self - Author, Weapons of Math Destruction
- (as Cathy O'Neil Ph.D.)
- Self - Author, Twitter and Tear Gas
- (as Zeynep Tufekci Ph.D.)
- Self - Author, Automating Inequality
- (as Virginia Eubanks Ph.D.)
- Self - Technical Co-Lead, Ethical A.I. Team at Google
- (as Timnit Gebru Ph.D.)
- Self - Author, Algorithms of Oppression
- (as Safiya Umoja Noble Ph.D.)
Avis à la une
There´s little focus but very hyperbolic interpertation of the data when it came to racial profiling by the AI... just a whiff of "wokeness" that was digestible to me, but also caused the polarization on this review section.
The rest of the documentary is well produced, informative, and seriously eye opening and you should see it because any of the negatives at least for me dont even come close to the deeper understandig you get from practical examples you see around the world that are very scary.
.
It's minor, but wasn't sure why some interviewees were framed with so much headroom. Then again, Mr Robot did that and I never understood it there, and given that that was also concerned with themes of technology and surveillance, maybe there's some shared symbolism I'm not picking up on.
Some of the segments with the AI saying menacing things were a little cheesy, but overall brief at least.
There's also a sense that the documentary may cover a little too much in its 85-minute runtime. While I can admire its ambition in covering so many aspects of facial recognition software, its racial biases, algorithm discrimination, and so on, it does make for a documentary that jumps around a fair bit and not always smoothly... at least all the topics are interesting on their own.
But in the end, it covers important topics and presents compelling arguments about particular flaws and biases in technology. It does warn that this is something that if unchecked could become a serious problem, so I like the attempt to bring awareness to this issue before it completely spirals out of control.
It's well edited, features interesting interviewees and subjects, and ends on a little more hope than I was anticipating, which was a nice surprise. Overall, it's one of the better Netflix documentaries I've watched in a while.
Fact: The darker ones complexation is the LESS likely that there is usable video or photos for investigators or prosecutors.
The makers of this film claim the opposite is the case, they claim there is a bias against persons with darker complexions -- when in fact that is not at all what the peer reviewed research shows.
The second argument of what if our government becomes like China is flawed as well. The face recognition AIs are going going to get better even if we do not work on them here someone will. Anything useful can also be used as a weapon. So if the government does want to use face recognition they will just get it. Probably better to have a known working system than one bought hasily and rushed into place.
It is odd to they barely mention any AI or ML outside of face recognition despite face recognition being a small part of what is out there.
All in all might be good to get you to started on research of your own but mostly misdirected furry.
Le saviez-vous
- Citations
Self - Author, Weapons of Math Destruction: On internet advertising as data scientists, we are competing for eyeballs on one hand, but really we're competing for eyeballs of rich people. And then, the poor people, who's competing for their eyeballs? Predatory industries. So payday lenders, or for-profit colleges, or Caesars Palace. Like, really predatory crap.
- ConnexionsFeatured in Jeremy Vine: Épisode #4.95 (2021)
Meilleurs choix
- How long is Coded Bias?Alimenté par Alexa
Détails
- Date de sortie
- Pays d’origine
- Sites officiels
- Langue
- Aussi connu sous le nom de
- Kodlanmış Önyargı
- Lieux de tournage
- Sociétés de production
- Voir plus de crédits d'entreprise sur IMDbPro
Box-office
- Montant brut aux États-Unis et au Canada
- 10 236 $US
- Week-end de sortie aux États-Unis et au Canada
- 10 236 $US
- 15 nov. 2020
- Montant brut mondial
- 10 236 $US
- Durée1 heure 26 minutes
- Couleur