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- 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.
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>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.
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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.
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They are trying to make this racially charged without giving enough information to verify their claims. If you use a dataset of mugshots, that's statistically going to have more data on people of color. If you have more data on people of color, it is more likely to match people of color. Claiming the algorithm is racist because your data is racist is inflammatory bullshit.
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Oh, wait: https://www.usatoday.com/story/tech/talkingtech/2018/06/29/c...
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The technology is not perfect. And should never be used as evidence of a crime, just as an indication that two images might be of the same person and to have humans look at them.
And then those humans will also make mistakes. People do look alike. And there are twins.
I think a jury should require more evidence than just similar appearance. But such a match is a strong indication of where to look.
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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.
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Presumption of Guilt is the new normal, isn't it?
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When the gov steers opinion, we call it manufactured consent, when public advocacy organizations engage in sloppy methodology to further a cause, I propose calling it manufactured outrage.
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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?
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It also possibly highlights the fact that algorithms are not immune to bias when they are designed by humans. Obviously I don’t think this bias is intentional, but so much of it isn’t and happens anyway.