this post was submitted on 21 Aug 2023
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The AI just "identifying" offenses is the easy part. It would be interesting to know whether the AI indeed correctly identified 300 offenses or if the person reviewing the AI's images acted on 300 offenses. That's potentially a huge difference and would have been the relevant part of the news.
The system we use in NL is called “monocam”. A few years ago it caught 95% of all offenders.
This means that AI had at most 5% false negatives.
I wonder if they have improved the system in the mean time.
https://nos.nl/artikel/2481555-nieuwe-slimme-camera-s-aangeschaft-om-appende-bestuurders-te-betrappen
How do they know that they caught 95% of all offenders if they didn't catch the remaining 5%? Wouldn't that be unknowable?
Welcome to the world of training datasets.
There are many ways to go about it, but for a limited number they'd probably use human analysts.
But in general, they'd put a lot more effort into a chunk of data and use that as the truth. It's not a perfect method but it's good enough.