A big biometric security company in the UK, Facewatch, is in hot water after their facial recognition system caused a major snafu - the system wrongly identified a 19-year-old girl as a shoplifter.
A big biometric security company in the UK, Facewatch, is in hot water after their facial recognition system caused a major snafu - the system wrongly identified a 19-year-old girl as a shoplifter.
Would you kindly link some studies backing up your claims, then? Because nothing I’ve seen online has similar numbers to what you’re claiming
https://pages.nist.gov/frvt/reports/1N/frvt_1N_report.pdf
It’s a
481443 page report directly from the body that does the testing.Edit: mistyped the number of pages
Edit 2: as I mentioned in another comment. I’ve read through this document many times. We even paid a 3rd party to verify our interpretations.
It saddens me that you are being downvoted for providing a detailed factual report from an authoritative source. I apologise in the name of all Lemmy for these ignorant people
Ya, most upvotes and downvotes are entirely emotionally driven. I knew I would get downvoted for posting all this. It happens on every forum, Reddit post, and Lemmy post. But downvotes don’t make the info I share wrong.
Thanks! Appreciate it, will take a look when I have time
Np.
As someone else pointed out in another comment. I’ve been saying the x% accuracy number incorrectly. It’s just a colloquial way of conveying the accuracy. The truth is that no one in the industry uses “percent accuracy” and instead use FMR (false match rate) and FNMR (false non-match rate) as well as some other metrics.