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.
You know what overfitting is, right?
Other than that, if this system of yours makes 1 error in a million scans, that’s still not very good, if that’s treated as “virtually no errors” as in no talking to manager, no showing ID as a fallback, so on. Say, if it were employed in Moscow subway, that’d mean a few unpleasant errors preventing people from getting where they need every day.
As you reply to someone who spent a decade in the AI industry.
This has nothing to do with overfitting. Particularly because our matching algorithm isn’t trained on data.
The face detection portion is, but that’s simply finding the face in an image.
The system I worked with used a threshold value that equates to an FMR of 1e-07. And it wasn’t used in places like subways or city streets. The point I’m making is that in the few years of real world operation (before I left for another job) we didn’t see a single false detection. In fact, one of the facility owners asked us to lower the threshold temporarily to verify the system was actually working properly.
Good to know.
So you are saying yourself that your argument has nothing to do with what’s in the article?..
OP said “reliability standards with a lot of nines have to be met”. All I’m saying is that we’re already there.
Well, the place you worked at is already there. Those stores - possibly not.
Also I said that about new and shiny stuff like what they call “AI”.