UK Police Say 92 Percent False Positive Facial Recognition Is No Big Deal (arstechnica.com)
An anonymous reader quotes a report from Ars Technica: A British police agency is defending its use of facial recognition technology at the June 2017 Champions League soccer final in Cardiff, Wales -- among several other instances -- saying that despite the system having a 92-percent false positive rate, "no one" has ever been arrested due to such an error. New data about the South Wales Police's use of the technology obtained by Wired UK and The Guardian through a public records request shows that of the 2,470 alerts from the facial recognition system, 2,297 were false positives. In other words, nine out of 10 times, the system erroneously flagged someone as being suspicious or worthy of arrest.
In a public statement, the SWP said that it has arrested "over 450" people as a result of its facial recognition efforts over the last nine months. "Of course, no facial recognition system is 100 percent accurate under all conditions. Technical issues are normal to all face recognition systems, which means false positives will continue to be a common problem for the foreseeable future," the police wrote. "However, since we introduced the facial recognition technology, no individual has been arrested where a false positive alert has led to an intervention and no members of the public have complained." The agency added that it is "very cognizant of concerns about privacy, and we have built in checks and balances into our methodology to make sure our approach is justified and balanced."
In a public statement, the SWP said that it has arrested "over 450" people as a result of its facial recognition efforts over the last nine months. "Of course, no facial recognition system is 100 percent accurate under all conditions. Technical issues are normal to all face recognition systems, which means false positives will continue to be a common problem for the foreseeable future," the police wrote. "However, since we introduced the facial recognition technology, no individual has been arrested where a false positive alert has led to an intervention and no members of the public have complained." The agency added that it is "very cognizant of concerns about privacy, and we have built in checks and balances into our methodology to make sure our approach is justified and balanced."
Rate of 8% successful, meaning almost 1 in 10 people are correctly identified. Not that bad.
Slashdot, fix the reply notifications... You won't get away with it...
despite the system having a 92-percent false positive rate, "no one" has ever been arrested due to such an error
I may have concerns about the civil liberty impact of broad-net surveillance systems in general, but the algorithmic deficiencies of this particular system are portrayed incorrectly in this article. I.e., the front-end of the system (the facial recognition system) has a 92% false positive rate, but together with the post-processing in the back-end, the total system has a false-positive rate of 0%. This is similar to saying that the object detection failure probabilities for a ADAS system need to be viewed in the context of the entire system, and it's the performance of the total system that is significant.
I'd rather err on the side of false positives than false negatives (which let them slip away). A minor inconvenience is worth the extra security by far.
Exactly!
A few innocent lives may be lost, but that's a small price to pay for my peace of mind.
2,470 alerts - 2,297 false positives = 173 true positives.
>450 people arrested from "facial recognition efforts".
Either that means there were >277 false arrests due to facial recognition, or they are counting arrests due to "facial recognition efforts" as also including the results of things they found when the searched people based on those false positives.
Since they claim "no one has ever been arrested due to such an error", so this means that both that the number of successful arrests has been inflated to make the system look more useful, and that the system's primary function is to justify illegal searches.
Sure. But I am talking Benjaman Franklin, not Benjamin Franklin.
Catching criminals is a side effect. The main purpose is to create justification to investigate anyone they want.
A percentage, without the context of use, is meaningless.
They might be using them for screening, to focus human evaluation. If so, that means that it is ultimately the cop that makes the decision, not the system. This is how today's AI is meant to be used - as a cognitive aid.
It is fairly common for screening tests in medicine to have high false positive rates. That is OK. They are just meant to narrow down the search space for more expensive/invasive confirmatory tests. Given that the incidence of criminal targets will always be a tiny percent of the corpus, it is very difficult to have tests with high true positive rate. That is quite normal for general tests, in general.
The questions that are relevant are:
1. Are the police able to better solve crime with the aids?
2. Is the test too expensive for the said improvement?
3. What are the rates of negative outcomes (like a wrongful arrest) and..
4. What do we, as a society, consider to be acceptable thresholds?
Well I for one don't think mass facial recognition should be used at all, because anyone who thinks it won't be abused just hasn't been paying attention.