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Joined 1 year ago
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Cake day: July 2nd, 2023

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  • I got that advice as well – the explanation given to me was that it’s almost always used incorrectly, so just be safe and don’t. However, I like the way it makes writing more closely resemble natural speech; we usually talk in conjoined clauses rather than complete sentences.







  • Thanks for the response! It sounds like you had access to a higher quality system than the worst, to be sure. Based on your comments I feel that you’re projecting the confidence in that system onto the broader topic of facial recognition in general; you’re looking at a good example and people here are (perhaps cynically) pointing at the worst ones. Can you offer any perspective from your career experience that might bridge the gap? Why shouldn’t we treat all facial recognition implementations as unacceptable if only the best – and presumably most expensive – ones are?

    A rhetorical question aside from that: is determining one’s identity an application where anything below the unachievable success rate of 100% is acceptable?


  • Can you please start linking studies? I think that might actually turn the conversation in your favor. I found a NIST study (pdf link), on page 32, in the discussion portion of 4.2 “False match rates under demographic pairing”:

    The results above show that false match rates for imposter pairings in likely real-world scenarios are much higher than those from measured when imposters are paired with zero-effort.

    This seems to say that the false match rate gets higher and higher as the subjects are more demographically similar; the highest error rate on the heat map below that is roughly 0.02.

    Something else no one here has talked about yet – no one is actively trying to get identified as someone else by facial recognition algorithms yet. This study was done on public mugshots, so no effort to fool the algorithm, and the error rates between similar demographics is atrocious.

    And my opinion: Entities using facial recognition are going to choose the lowest bidder for their system unless there’s a higher security need than, say, a grocery store. So, we have to look at the weakest performing algorithms.