Oakland, California On Its Way To Becoming The Third US City To Ban Facial Recognition Tech
from the beat-it,-face-jockeys dept
For the third time in two months, a US city has banned the use of facial recognition tech by local government agencies.
San Francisco started this movement (oh god please let it be a movement) back in May, booting the tech out of the city before local agencies had even gotten a chance to fool around with it. Earlier this month, Somerville, Massachusetts took home the silver in the anti-surveillance-state games, enacting a local ban on facial recognition tech.
Oakland, California has become the third city in the nation move forward with a facial recognition tech ban, as KPIX reports:
The city of Oakland on Tuesday took a first step towards banning the use of facial recognition technology by city employees, including the Oakland Police Department.
The City Council voted unanimously to approve the ordinance, which would prohibit police from both acquiring the software or using it at all, including if used by other police agencies.
This won't become official until September, when the council will reconvene for a second -- and final -- vote on the ordinance. It seems unlikely a majority of councilmembers will switch positions in the next 60 days, so local agencies with an eye on acquiring this tech should probably put those dreams to bed.
This ban appears to be slightly broader than those enacted elsewhere. It forbids government agencies from using the tech even when partnering with non-city agencies that might have this tech in their possession.
And a little homework goes a long way. The city council's president wrote a report on all the downsides of facial recognition tech, including its lack of accuracy and its tendency to err more often when attempting to identify minorities.
This ban will cramp the Oakland PD's style a bit. It already uses facial recognition tech via a database owned by the San Mateo County Sheriff. It argued that it should still be allowed to do this, but the council disagreed, voting for a ban that locks them out of the Sheriff's database. Hopefully, that language will be retained when it comes up for a final vote in September.
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Filed Under: bans, facial recognition, oakland, privacy
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Now we just need to ban
If we could now ban Stingrays and the TSA, we'd be closer to normalcy in this country.
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Three cities doth not a country make, except perhaps in Liechtenstein. I'm rather dubious that banning facial recognition will become a trend. If anyone remembers, DNA evidence was only supposed to exclude people as suspects and so it will go with facial recognition, unfortunately.
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Re:
Thank you Mr Soothsayer,
Those of us at Facial Recog International (FRI) who have stock options want to thank you for your support. Please continue with your belief in our crusade.
I must point one thing however, and that is DNA is not the same as a picture. One could do a bit for bit comparison between two instances of pictures that seem to be the same in order to determine whether they are actually contain the same data, this cannot be said about DNA. As you pointed out, DNA can be used to exclude possible matches but fails when asked to confirm it is the same data. So, your conclusion is not necessarily correct.
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Re: Re:
If you work for a facial recognition company, you should know better than that. If you compare two different photos, you obviously cannot have the same data, bit by bit, so your use of "same data" is highly misleading, since the only possible way to refer to data from different images is to assume that you've extracted what is important to matching two images, which is exactly the problem. The only way a bitwise comparison of two images will be the same is if you are comparing an image to an exact bitwise copy of itself.
Further,ore, you can read the following and the references therein to see how to manipulate images such that two images that appear the same will be determined to be different by AI software:
https://arxiv.org/abs/1607.02533
If that is possible, it is just as possible to take images of two different people which might look similar and manipulate them to cause AI to determine the images are of the same person. It's not like it's unknown for forensics labs to get the results they were predisposed to getting when the evidence would not support their conclusions.
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