3 ms·

Facial recognition is being banned for law enforcement use not because it doesn't work, or is ineffective, or is undesirable, but because it reveals politically

Facial recognition is being banned for law enforcement use not because it doesn't work, or is ineffective, or is undesirable, but because it reveals politically uncomfortable truths about who commits crime that existing crime stats were already pointing out in a less visceral way.

oarsinsync 6y ago
That's a pretty damning statement to make. Can you provide some citations to back that view up?
- orestarod 6y ago
  Without links ready, and not being the OP, I have seen many articles saying that "this ML recognition/analysis system has racial bias because the targets it finds are more {insert trait} than average." It struck me how such an unscientific thing made it to so many articles. It's a symptom of a cause that a specific group has greater representation in something, e.g. crime. You can't call factual observations, racist. You should rather find the root cause and solve it.
  - vmception 6y ago
    > You can't call factual observations, racist. You should rather find the root cause and solve it. People already know the root cause, and it is overpolicing and discretionary enforcement of crimes like drug possession. The broken-windows policy has been disproven, despite disproportionately impacting "the specific groups" (black Americans) that now pollute the dataset that ML uses. And even in the concept or drug possession and drug consumption, all groups have been shown to use them in the same distribution. For example. These kinds of things start a cycle that means the second and third minor infractions cause greater consequences in court, which further reduce opportunities that lead to the dangerous crimes being committed. So we already know the dataset is polluted. Pointing to the top of the iceberg and saying "well they commit the crimes no need to spend any energy on this mystery why don't we all just admit they're the problem" is a complete deflection promulgated intentionally and you should really check your peer group and media sources if this is the extent of the comfortable worldview you (or anyone passing by) have, the problem and solution is already known. The solutions are being implemented in a patchwork and slowly, which is not incorporated in datasets that ML use, largely due to apathy and lack of awareness of engineers and the management of the tech companies involved, and lack of representation of the affected groups in engineering and management of tech companies.
    - core-questions 6y ago
      > People already know the root cause, and it is overpolicing and discretionary enforcement of crimes like drug possession. No, you've only pushed the root cause back a step by doing this. It's entirely possible to understand that the way we're doing policing is wrong without resorting to an artificial, borderline-creationist mindset on aggregate group behaviour. Religious thinking is not going to help anything here. > So we already know the dataset is polluted. The dataset reflects something approaching reality. If anything, it reflects a version of reality that is already attempting to artificially compensate for group differences in order to quell conflict. If you want to change reality, if you want to see less crime, if you want to see truly fair policing, then admitting to reality is an important first step. You're basically arguing for "juking the stats" in order to find fairness, when in reality such actions won't stop people from getting robbed, murdered, or having lives that offer so few opportunities for advancement that they end up turning to hard drugs to cope. ML is not to solve this problem either way, but it can actively prevent the problem from being solved if it becomes yet another mechanism to paper over the actual situation and instead point the finger for responsibility away from where it belongs: with individuals and their choices.
  - spoonjim 6y ago
    Well the “factual” observation comes from training data, which unless created in an unbiased manner creates a biased dataset and biased inferences. Unless you believe that American law enforcement is an unbiased process, in which case I don’t think I can help you.
- core-questions 6y ago
  Unfortunately, I have learned that there's no value in doing so, since anyone who has managed to be willfully ignorant of the obvious conclusions here that have been consistent for decades will not be convinced by anything I link to; instead, typically "shoot the messenger" techniques come into place. Anything 'bad' that anyone I link to has ever said will poison the well for any factual claims they make, etc. It's a shame it has to be like this. There's plenty of valid statistical / demographic information out there that lines up perfectly with everyone's lived experience, but the conclusions drawn from it are not pretty. All I can say is that it is possible to make inferences without making value judgements; we can point at problems without having evil intentions and without suggesting tyrannical interventions.
vmception 6y ago
and also picks the wrong people because the training set is polluted by the uncomfortable truths of overpolicing areas creating the bad crime stats
spoonjim 6y ago
LOL. And reveals uncomfortable truths about what the law has defined as a “crime,” where killing one person in a $100 drug transaction gets you life without parole, while fraudulently marketing OxyContin as non-addictive while knowing it is addictive, thus creating the opioid epidemic that has killed 500,000 people to date, and hiring McKinsey to solve your “my drug is killing people” problem gets you a $3 million fine.
- core-questions 6y ago
  What if I told you that both things are bad, and that I want the perpetrators of both crimes to face proportionate punishment? There's no reason for one's critique to fall victim to a false dichotomy here, even if the American political environment tries to do that. Maybe it helps that I'm not American.... Killing one person in any kind of failed transaction is a bad enough offense that I believe you deserve at least a decade in jail. That said, I do believe in rehabiliatory justice, and that we shouldn't just throw people into an environment that's essentially some cross between a dysfunctional highschool and a networking seminar for criminals; but people who are willing to kill over $100 do not belong in public until they have proven conclusively that they have enough self control to be released. The opiate epidemic, on the other hand, is a crime so heinous that it is nearly genocide-tier in nature. The perpetrators of such (i.e. the Sacklers among others) knew what they were doing, continually doubled down over time, and profited tremendously. Such parenthetical elites usually suffer absolutely zero punishment for their actions, nor is there any attempt to make rehabiliatory justics take on the challenge of so-called "white collar crime". At best, the perp learns how to hide their intentions and actions more, how to operate behind more intermediaries for abstraction's sake, etc. Now, consider the topic at hand (which is somehow facial recog and not Daft Punk whom I loved dearly): what is the common factor here? It's simple: if you perform an analysis of the group memberships of the people who commit crimes in the aggregate, uncomfortable truths are revealed.
  - jessaustin 6y ago
    Maybe you just like punishment? Also Daft Punk, of course.
chokeartist 6y ago
Lol god bless you madlad. You tossed a mollie right into the fight pit.
GVIrish 6y ago
Errors in facial recognition software have already resulted in more than one wrongful arrest due to mistaken identity: https://www.npr.org/2020/06/24/882683463/the-computer-got-it-wrong-how-facial-recognition-led-to-a-false-arrest-in-michig https://www.npr.org/2020/06/24/882683463/the-computer-got-it... https://lawandcrime.com/civil-rights/third-innocent-black-man-to-be-misidentified-by-facial-recognition-software-sues-police-department-and-prosecutor-for-false-arrest-and-imprisonment/ https://lawandcrime.com/civil-rights/third-innocent-black-ma...

oarsinsync 6y ago

That's a pretty damning statement to make. Can you provide some citations to back that view up?

orestarod 6y ago
Without links ready, and not being the OP, I have seen many articles saying that "this ML recognition/analysis system has racial bias because the targets it finds are more {insert trait} than average." It struck me how such an unscientific thing made it to so many articles. It's a symptom of a cause that a specific group has greater representation in something, e.g. crime. You can't call factual observations, racist. You should rather find the root cause and solve it.
- vmception 6y ago
  > You can't call factual observations, racist. You should rather find the root cause and solve it. People already know the root cause, and it is overpolicing and discretionary enforcement of crimes like drug possession. The broken-windows policy has been disproven, despite disproportionately impacting "the specific groups" (black Americans) that now pollute the dataset that ML uses. And even in the concept or drug possession and drug consumption, all groups have been shown to use them in the same distribution. For example. These kinds of things start a cycle that means the second and third minor infractions cause greater consequences in court, which further reduce opportunities that lead to the dangerous crimes being committed. So we already know the dataset is polluted. Pointing to the top of the iceberg and saying "well they commit the crimes no need to spend any energy on this mystery why don't we all just admit they're the problem" is a complete deflection promulgated intentionally and you should really check your peer group and media sources if this is the extent of the comfortable worldview you (or anyone passing by) have, the problem and solution is already known. The solutions are being implemented in a patchwork and slowly, which is not incorporated in datasets that ML use, largely due to apathy and lack of awareness of engineers and the management of the tech companies involved, and lack of representation of the affected groups in engineering and management of tech companies.
  - core-questions 6y ago
    > People already know the root cause, and it is overpolicing and discretionary enforcement of crimes like drug possession. No, you've only pushed the root cause back a step by doing this. It's entirely possible to understand that the way we're doing policing is wrong without resorting to an artificial, borderline-creationist mindset on aggregate group behaviour. Religious thinking is not going to help anything here. > So we already know the dataset is polluted. The dataset reflects something approaching reality. If anything, it reflects a version of reality that is already attempting to artificially compensate for group differences in order to quell conflict. If you want to change reality, if you want to see less crime, if you want to see truly fair policing, then admitting to reality is an important first step. You're basically arguing for "juking the stats" in order to find fairness, when in reality such actions won't stop people from getting robbed, murdered, or having lives that offer so few opportunities for advancement that they end up turning to hard drugs to cope. ML is not to solve this problem either way, but it can actively prevent the problem from being solved if it becomes yet another mechanism to paper over the actual situation and instead point the finger for responsibility away from where it belongs: with individuals and their choices.
- spoonjim 6y ago
  Well the “factual” observation comes from training data, which unless created in an unbiased manner creates a biased dataset and biased inferences. Unless you believe that American law enforcement is an unbiased process, in which case I don’t think I can help you.
core-questions 6y ago
Unfortunately, I have learned that there's no value in doing so, since anyone who has managed to be willfully ignorant of the obvious conclusions here that have been consistent for decades will not be convinced by anything I link to; instead, typically "shoot the messenger" techniques come into place. Anything 'bad' that anyone I link to has ever said will poison the well for any factual claims they make, etc. It's a shame it has to be like this. There's plenty of valid statistical / demographic information out there that lines up perfectly with everyone's lived experience, but the conclusions drawn from it are not pretty. All I can say is that it is possible to make inferences without making value judgements; we can point at problems without having evil intentions and without suggesting tyrannical interventions.

vmception 6y ago

and also picks the wrong people because the training set is polluted by the uncomfortable truths of overpolicing areas creating the bad crime stats

spoonjim 6y ago

LOL. And reveals uncomfortable truths about what the law has defined as a “crime,” where killing one person in a $100 drug transaction gets you life without parole, while fraudulently marketing OxyContin as non-addictive while knowing it is addictive, thus creating the opioid epidemic that has killed 500,000 people to date, and hiring McKinsey to solve your “my drug is killing people” problem gets you a $3 million fine.

core-questions 6y ago
What if I told you that both things are bad, and that I want the perpetrators of both crimes to face proportionate punishment? There's no reason for one's critique to fall victim to a false dichotomy here, even if the American political environment tries to do that. Maybe it helps that I'm not American.... Killing one person in any kind of failed transaction is a bad enough offense that I believe you deserve at least a decade in jail. That said, I do believe in rehabiliatory justice, and that we shouldn't just throw people into an environment that's essentially some cross between a dysfunctional highschool and a networking seminar for criminals; but people who are willing to kill over $100 do not belong in public until they have proven conclusively that they have enough self control to be released. The opiate epidemic, on the other hand, is a crime so heinous that it is nearly genocide-tier in nature. The perpetrators of such (i.e. the Sacklers among others) knew what they were doing, continually doubled down over time, and profited tremendously. Such parenthetical elites usually suffer absolutely zero punishment for their actions, nor is there any attempt to make rehabiliatory justics take on the challenge of so-called "white collar crime". At best, the perp learns how to hide their intentions and actions more, how to operate behind more intermediaries for abstraction's sake, etc. Now, consider the topic at hand (which is somehow facial recog and not Daft Punk whom I loved dearly): what is the common factor here? It's simple: if you perform an analysis of the group memberships of the people who commit crimes in the aggregate, uncomfortable truths are revealed.
- jessaustin 6y ago
  Maybe you just like punishment? Also Daft Punk, of course.

chokeartist 6y ago

Lol god bless you madlad. You tossed a mollie right into the fight pit.

GVIrish 6y ago

Errors in facial recognition software have already resulted in more than one wrongful arrest due to mistaken identity: https://www.npr.org/2020/06/24/882683463/the-computer-got-it-wrong-how-facial-recognition-led-to-a-false-arrest-in-michig https://www.npr.org/2020/06/24/882683463/the-computer-got-it... https://lawandcrime.com/civil-rights/third-innocent-black-man-to-be-misidentified-by-facial-recognition-software-sues-police-department-and-prosecutor-for-false-arrest-and-imprisonment/ https://lawandcrime.com/civil-rights/third-innocent-black-ma...