4 ms·
In my experience, when face recognition gives you a false positive, it's because there is a high likeness in the first place, and a human would likely have made
by cm2187 2y ago
In my experience, when face recognition gives you a false positive, it's because there is a high likeness in the first place, and a human would likely have made the same mistake.
How different is it from a police officer stopping someone in the street based on some photo on his most wanted cheat sheet? Or a shopkeeper denying entry to a customer based on the likeness to a list of mugshots held under the counter. Those are faillible processes too.
Where face recognition is really useful is where it can match faces that would have otherwise fooled the human eye, just because it focuses on specific traits and ignores others like hairstyle.
- Macha 2y agoThe difference is scale. "You look a bit like a shoplifter from across the country" is not a productive use of a police officer's time, so will basically never happen. Whereas the people in this article are going to get challenged, if not outright refused or arrested, in an increasing number of stores as this tech spreads.
- bsenftner 2y agoThe problem is the dumb ass users of FR think an FR Match has authority, AND the industry does not discourage that attitude, not at all.
- BLKNSLVR 2y agoAnd there's a lack of, for want of a better word, punishment for false positives for all of: the law enforcement officers, the software publishers, the policy makers.
- JohnFen 2y ago> How different is it from a police officer stopping someone in the street based on some photo on his most wanted cheat sheet? There's a big difference. The cop knows that the resemblance could be coincidental and will (usually) do further investigation before actually harming the suspect. If an automated system fingers someone, the assumption is that the system is correct and innocent people caught up will suffer harm.