jm + face-recognition   2

London police’s use of AFR facial recognition falls flat on its face
A “top-of-the-line” automated facial recognition (AFR) system trialled for the second year in a row at London’s Notting Hill Carnival couldn’t even tell the difference between a young woman and a balding man, according to a rights group worker invited to view it in action. Because yes, of course they did it again: London’s Met police used controversial, inaccurate, largely unregulated automated facial recognition (AFR) technology to spot troublemakers. And once again, it did more harm than good.

Last year, it proved useless. This year, it proved worse than useless: it blew up in their faces, with 35 false matches and one wrongful arrest of somebody erroneously tagged as being wanted on a warrant for a rioting offense.

[...] During a recent, scathing US House oversight committee hearing on the FBI’s use of the technology, it emerged that 80% of the people in the FBI database don’t have any sort of arrest record. Yet the system’s recognition algorithm inaccurately identifies them during criminal searches 15% of the time, with black women most often being misidentified.
face-recognition  afr  london  notting-hill-carnival  police  liberty  met-police  privacy  data-privacy  algorithms 
september 2017 by jm
Schneier on Automatic Face Recognition and Surveillance
When we talk about surveillance, we tend to concentrate on the problems of data collection: CCTV cameras, tagged photos, purchasing habits, our writings on sites like Facebook and Twitter. We think much less about data analysis. But effective and pervasive surveillance is just as much about analysis. It's sustained by a combination of cheap and ubiquitous cameras, tagged photo databases, commercial databases of our actions that reveal our habits and personalities, and ­-- most of all ­-- fast and accurate face recognition software.

Don't expect to have access to this technology for yourself anytime soon. This is not facial recognition for all. It's just for those who can either demand or pay for access to the required technologies ­-- most importantly, the tagged photo databases. And while we can easily imagine how this might be misused in a totalitarian country, there are dangers in free societies as well. Without meaningful regulation, we're moving into a world where governments and corporations will be able to identify people both in real time and backwards in time, remotely and in secret, without consent or recourse.

Despite protests from industry, we need to regulate this budding industry. We need limitations on how our images can be collected without our knowledge or consent, and on how they can be used. The technologies aren't going away, and we can't uninvent these capabilities. But we can ensure that they're used ethically and responsibly, and not just as a mechanism to increase police and corporate power over us.
privacy  regulation  surveillance  bruce-schneier  faces  face-recognition  machine-learning  ai  cctv  photos 
october 2015 by jm

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