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.
All the time, eh? Gonna need a citation on that. And I’m not talking about just one news article that pops up every six months. And nothing that links back to the UCLA’s 2018 misleading “report”.
You assume a lot here. People have this conception that all FR systems are trained blackbox models. This is true for some systems, but not all.
The system I worked with, which ranked near the top of the NIST FRVT reports, did not use a trained AI algorithm for matching.
I’m not doing a bunch of research to prove the point. I’ve been hearing about them being wrong fairly frequently, especially on darker skinned people, for a long time now. It doesn’t matter how often it is. It sounds like you have made up your mind already.
I’m assuming that of apple because it’s been around for a few years longer than the current AI craze has been going on. We’ve been doing facial recognition for decades now, with purpose built algorithms. It’s not mucb of leap to assume that’s what they’re using.
I can guarantee you haven’t. I’ve worked in the FR industry for a decade and I’m up to speed on all the news. There’s a story about a false arrest from FR at most once every 5 or 6 months.
You don’t see any reports from the millions upon millions of correct detections that happen every single day. You just see the one off failure cases that the cops completely mishandled.
No it hasn’t. FR systems have been around a lot longer than Apple devices doing FR. The current AI craze is mostly centered around LLMs, object detection and FR systems have been evolving for more than 2 decades.
Then why would you assume companies doing FR longer than the recent “AI craze” would be doing it with “black boxes”?
At least you proved my point.
Obviously. I don’t have much of an issue with it when it’s working properly (although I do still absolutely have an issue with it still). It being wrong and causing issues fairly frequently, and every 5 or 6 months is frequent (this is a low number, just the frequency of it causing newsworthy issues) with it not being deployed widely yet, is a pretty big issue. Scale that up by several orders of magnitude if it’s widely adopted and the errors will be constant.
You’re repeating what I said. Apples FR tech is a few years older than the machine learning tech that we have now. FR in general is several decades old, and it’s not ML based. It’s not a black box. You can actually know what it’s doing. I specifically said they weren’t doing it with black boxes. I said the AI models are. Please read again before you reply.
You wrongly assuming what I said, which is actually the opposite of what I said, is the reason I’m not putting in the effort. You’ve made up your mind. I’m not going to change it, so I’m not putting in the effort it would take to gather the data, just to throw it into the wind. It sounds like you are already aware of some of it, but somehow think it’s not bad.