अपनी भाषा में प्लॉट जोड़ेंWhen 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... सभी पढ़ेंWhen 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.
- पुरस्कार
- 3 जीत और कुल 6 नामांकन
- 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.)
The execution of this documentary, however, is very underwhelming, to say the least. There are the usuals: catchy montages, TED-style interviews, news soundbites, and the most annoying of all - artificially created (pun intended) graphics of AI scanning data in a stereotypical digital font paired with silly sound effects which, unless the primary audience of this documentary is fifth graders, I don't understand why it's necessary to incessantly rehash them. And then there's the unimaginative 'robotic voice.' It's just puerile.
Maybe the producers are wary that people still won't get the danger of unregulated AI without these gimmicks. But I'd argue that people would be more alarmed to learn how AI has been infiltrating and affecting our lives in the least expected ways. If the documentary can clearly point out the potential harms as a consequence, I think people will naturally find the lack of regulation disturbing, no silly visuals and sound effects are needed. Sometimes I think they actually undermine the severity of potential danger at hand. For example, the scene where a teenager is mistakenly stopped by plainclothes police, instead of being accompanied with yet another piece of cheesy soundtrack meant to suggest danger, it would be so much more powerful if everything is just eerily silent.
And the interviews and info - yes, AI is like a black box even to the programmers, but can you explain it in layman's terms so that people get it? - could be a lot more insightful. Even some short Vox-style Youtube clips have explored these issues in greater depth.
The themes explored are a bit all over the place too. I get it this domain is relatively new, so the vocabulary and focus aren't that streamlined yet, still... Sometimes the documentary brings up issues of obvious biases, which is consistent with the title, but sometimes we don't even know what the problem is, it's simply an issue of things being completely nontransparent and/or unverified by a third party. The China parts are also a little disjointed from the rest of the documentary and the country itself is painted in broad strokes - it's as if we can't do good until we can identify the bad guy to feel good about ourselves.
- MeadtheMan
- 4 अप्रैल 2021
- परमालिंक
कहानी
क्या आपको पता है
- भाव
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.
- कनेक्शनFeatured in Jeremy Vine: एपिसोड #4.95 (2021)
टॉप पसंद
- How long is Coded Bias?Alexa द्वारा संचालित
विवरण
- रिलीज़ की तारीख़
- कंट्री ऑफ़ ओरिजिन
- आधिकारिक साइटें
- भाषा
- इस रूप में भी जाना जाता है
- Kodlanmış Önyargı
- फ़िल्माने की जगहें
- उत्पादन कंपनियां
- IMDbPro पर और कंपनी क्रेडिट देखें
बॉक्स ऑफ़िस
- US और कनाडा में सकल
- $10,236
- US और कनाडा में पहले सप्ताह में कुल कमाई
- $10,236
- 15 नव॰ 2020
- दुनिया भर में सकल
- $10,236
- चलने की अवधि1 घंटा 26 मिनट
- रंग