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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

#31

Post by mrweasel »

sadris wrote: post #18

Internet 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 becau…

The problem is that it's only 95% perfect in this case (28 out of 534, being identified as criminals). That a pretty big margin of error when the result is possible arrest. The scope of its use is also in question, sure if you looking a someone who kidnapped a child, 95% is good enough. If you use it for any minor violation you risk harassing a large percentage of the population, who then will need to prove that it wasn't them. Some will flat out deny being the guilty party, and there's a 5% margin of error, so they may very well be right. Then what will you do, drop the charge? In that case what's the point. Or will you spend police time finding evidence that some random person stole $10 worth of good at the super market?

The cost associated with being just 5% wrong is huge, and that's not including the emotional damage done to falsely accused citizens, or the decrease level of trust in law enforcement.

Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots

#32

Post by otakucode »

joemaller1 wrote: post #10

Things 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.

When facial recognition fails, it usually looks pretty weird. Like it will identify faces in the knots and grain patterns of a wooden wall behind somebody. It's really a very ineffective technology and it's disturbing that it gets sold as something you could use to justify locking someone in a cage over. Machines with pareidolia are not good tools.

Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots

#34

Post by onemoresoop »

rebuilder wrote: post #8
nolite wrote: post #2

predictive analytics..?

So phrenology again? IIRC, that idea didn't exactly hold up to scrutiny.

I think it was humor and made me laugh a bit.. phrenology cannot be taken seriously

Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots

#35

Post by dfundako »

fluxsauce wrote: post #29
cthalupa wrote: post #15

https://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 witho…

> but Amazon says it recommends at least a 95 percent threshold for law enforcement applications where a false ID might have more significant consequences. That's not in https://aws.amazon.com/rekognition/faqs/ - while that threshold may minimize false positives, I'm curious if it was in any documentation that the ACLU saw. Or, to the bigger point, is it in any public documentation?

I would be shocked if LE started using this tech, imprisoned a bunch of people, and used the excuse "Well, we followed the FAQS." I would imagine they would work very closely with Amazon and run a ton of calibration. For the ACLU to say that we used the default settings and it doesn't work correctly is disingenuous.

Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots

#36

Post by twothamendment »

They have Montana Rep. Greg Gianforte in the list of false positives. Did they call it a false positive because they are sure he wasn't included in the 25,000 mugs they loaded? His mug is out there.

https://www.google.com/amp/s/amp.usatoday.com/amp/756343001

Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots

#38

Post by sadris »

mrweasel wrote: post #31
sadris wrote: post #18

Internet 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 becau…

The problem is that it's only 95% perfect in this case (28 out of 534, being identified as criminals). That a pretty big margin of error when the result is possible arrest. The scope of its use is also in question, sure if you looking a someone who kidnapped a child, 95% is good enough. If you use it for any minor violation you risk harassing a large percentage of the population, who then will need to prove that it w…

They weren't "identified as criminals." They were identified as possibly being criminals. (And as other posters have shown, they were identified with only 80% confidence as being a criminal.) And an officer can review the evidence presented by the report and make a human determination to follow up with a physical arrest.

Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots

#39

Post by EliRivers »

dfundako wrote: post #35
fluxsauce wrote: post #29

Earlier quoted context omitted.

> but Amazon says it recommends at least a 95 percent threshold for law enforcement applications where a false ID might have more significant consequences. That's not in https://aws.amazon.com/rekognition/faqs/ - while that threshold may minimize false positives, I'm curious if it was in any documentation that the ACLU saw. Or, to the bigger point, is it in any public documentation?

I would be shocked if LE started using this tech, imprisoned a bunch of people, and used the excuse "Well, we followed the FAQS." I would imagine they would work very closely with Amazon and run a ton of calibration. For the ACLU to say that we used the default settings and it doesn't work correctly is disingenuous.

I would imagine they would work very closely with Amazon and run a ton of calibration.

Do you have any evidence for this? I would have imagined the other way; that it would be badly deployed by ill-trained gung-ho operators who will routinely end up clubbing some innocent guy round the head (if they don't just shoot him) because the magic machine said he was a dangerous killer on the loose. I don't have any evidence my way, but what I imagined is the polar opposite of what you imagined.

Re: Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots

#40

Post by SmellyGeekBoy »

sadris wrote: post #38
mrweasel wrote: post #31

Earlier quoted context omitted.

The problem is that it's only 95% perfect in this case (28 out of 534, being identified as criminals). That a pretty big margin of error when the result is possible arrest. The scope of its use is also in question, sure if you looking a someone who kidnapped a child, 95% is good enough. If you use it for any minor violation you risk harassing a large percentage of the population, who then will need to prove that it w…

They weren't "identified as criminals." They were identified as possibly being criminals . (And as other posters have shown, they were identified with only 80% confidence as being a criminal.) And an officer can review the evidence presented by the report and make a human determination to follow up with a physical arrest.

Perhaps more of an issue in a country where being arrested can involve being murdered by the police.
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