Could this be down to the people training the algorithm being predominantly middle class white people? It's a pretty well known phenomenon that people are bad at recognising features of people of other races.
Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots
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Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots
#12Things I want to know: - Show us the side-by-side images of the false-positives. Are the matches plausible? - What is the demographic distribution of the mugshot database? If the data is disproportionately biased, then that bias would be reflected in the false-positives. A casual skimming of some mughot websites shows a potentially significant racial bias.
How dare you question our great overlords the ACLU. They would never use statistics to find results favourable to their hypothesis.
Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots
#13Are you sure? lol
Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots
#14The scary part is that people believe "science" because it is created by people who they think are "clever" and thefore not likely to be wrong.
How many people have been falsely convicted because "DNA"? 1B-1 odds of a match, "and sir, yet you claim you were not even in the area?".
There should be a way of recognising the parts of the science that are basically correct and the parts that are either less reliable, open to bias or could simply be broken due to incorrect process/mistake in the lab.
Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots
#15https://www.theverge.com/2018/7/26/17615634/amazon-rekogniti...
>Reached by The Verge, an Amazon spokesperson attributed the results to poor calibration. The ACLU’s tests were performed using Rekognition’s default confidence threshold of 80 percent — but Amazon says it recommends at least a 95 percent threshold for law enforcement applications where a false ID might have more significant consequences.
Presented without real comment on my part.
Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots
#16Things I want to know: - Show us the side-by-side images of the false-positives. Are the matches plausible? - What is the demographic distribution of the mugshot database? If the data is disproportionately biased, then that bias would be reflected in the false-positives. A casual skimming of some mughot websites shows a potentially significant racial bias.
I have a ton of quibbles with the article and methodology, honestly. I suspect it's just straight-up so flawed as to be irrelevant to the discussion.
At the same time, they do still have the correct final conclusion. Dragnet facial recognition is a bad idea that will produce too many false positives to be of use. Or at the very least, dragnet facial recognition used by people who put too much faith in it is a bad idea. It's at most useful to produce flags for slightly more attention; on its own, I would not consider it anywhere close to enough to arrest someone on.
And it can serve as a demonstration of how a clumsily-put-together system can be used to produce bad results, so, if we correctly assume that there may be people bodging together a system in much the same way the ACLU did, well, hey, it's a valid result then!
Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots
#17I don't see any mention of them verifying those members of congress are not in fact the same people as the mugshots (/s)
I admit that was my first interpretation before I remembered the issues with accuracy.
Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots
#18Internet used to be delivered through unreliable 28.8kbps modems. I didn't think for a second that we should cease using the Internet.
Bone marrow transplants for cancer treatment used to have a 20% failure rate. I didn't think for a second that we should cease using bone marrow transplants.
And yet why does the ACLU think we should cease using a technology to deliver potential location hits on wanted criminals because its not 100% perfect?
Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots
#19Things I want to know: - Show us the side-by-side images of the false-positives. Are the matches plausible? - What is the demographic distribution of the mugshot database? If the data is disproportionately biased, then that bias would be reflected in the false-positives. A casual skimming of some mughot websites shows a potentially significant racial bias.
Depending on the technologi behind Amazons facial recognitions, there's very real chance that the software simply associated some black facial features with "being criminal". If that's the case we're back to craniometry in the 1910-1940.
Perhaps lawmakers should consider implementing rules to ban facial recognition software until the developers can prove some like 99.999% accuracy. Otherwise we end up harassing a large number of people, and the credibility of the technology will stuff. As it stand any lawyer will be able to argue that facial recognition isn't admisible as evidence, do to the high margin of error.
Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots
#20I don't see why this is a bad thing.
Falsely arrest 28 members of Congress due to poor face recognition, and the problem of facial recognition in law enforcement is resolved the next day.