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He specifically used the example of predictive policing. I have a question: is it racist to send police patrolling areas of high crime, if those areas have a m

by daenz 7y ago

He specifically used the example of predictive policing. I have a question: is it racist to send police patrolling areas of high crime, if those areas have a majority ethnic demographic? Should that information be discarded, and all places patrolled equally? Should they be patrolled less? It seems like there is no winning. You're either wasting resources, ignoring a problem, or being perceived as racist.

Reelin 7y ago
I suspect that there is indeed no winning, and that under such circumstances every possible course of action is likely to be perceived as racist by some number of people. This is because the population at large doesn't seem to be able to agree on what the word actually means (https://slatestarcodex.com/2017/06/21/against-murderism/ https://slatestarcodex.com/2017/06/21/against-murderism/). Regarding ML based predictive policing specifically, it seems like a spectacularly bad (but efficient and statistically effective!) idea to naively apply a machine learning based classification approach to such a problem.
ben_w 7y ago
It depends. Here are three different examples that would meet your description, with very different answers: 1) The X community has exactly the same, or lower, crime rates than the entire nation. However, nationwide anti-X sentiment means that despite this, most convicted criminals are from the X community. This makes it look like the regions where the X community live are high-crime regions. This is “accidentally racist”. Researchers know about this problem. 2) The X community is more prone to crime, and as this is purely an example, it just is and there’s no need to justify that. Extra police in this scenario is not racist, though I suspect anyone who jumps right in and assumes it to be true about the world might well be racist themselves. 3) A confounding variable, such as income or education, means that members of the X community are more likely to commit crimes than the general population, albeit it at the same rate as the equivalent income/education/confounding sunset of the general population. In this case, while it would not be racist to send in more police, it would totally be racist if politicians applied unequal effort to solve the confounding variable within the general population as compared specifically to group X.
wsxcde 7y ago
The problems of appropriate policing in so-called "high crime" neighborhoods are well understood. Many academic studies, as well as popular non-fiction like Jill Leovy's Ghettoside and Chris Hayes' Colony in a Nation, have discussed the issue. To sum up the literature in a few sentences, the problem is that minority neighborhoods are both overpoliced and underpoliced. There are a lot of useless arrests for minor crimes like jaywalking which makes the residents of these neighborhoods hostile to the police. (These arrests are driven by the debunked theory of broken window policing.) Simultaneously, there's not enough effort put into solving serious crimes like murder. In this context, the actual effect of predictive policing is that it ends up doing more of the useless over-policing, which unfortunately makes these neighborhoods even worse. So, how does this relate to your question? The point is that predictive policing is solving the wrong problem. What's needed are not more accurate neural nets predicting crime, but techniques for addressing the underly sociological factors that cause crime. Taking a step back and speaking broadly, Cory's point is that the focus on data and quantitative analysis is causing problems in two ways: (i) people are using quantitative methods to solve the wrong problems, and (ii) they seem to be oblivious to (and in some cases actively hostile to acknowledging) the harms being perpetrated by their methods. Both of these problems seem to be driven by a lack of understanding of well understood (but non-quantitative) social science literature.
- deleted 7y ago
  [deleted]
- TheOtherHobbes 7y ago
  Well, yes. That's the point. This form of AI will automate existing prejudices and misunderstandings. We're not really dealing with AI in any useful sense, but with automated bad policy biases, and the products and systems this generates should be labelled as such. Corollary - Big Data is political, but it can hide behind the pretence of objectivity. This shouldn't surprise anyone, but for some reason it does - perhaps because we're used to thinking of AI as the automation of the scientific method, when in fact it's just as likely to be the automation of all kinds of other things, some of which are nasty, stupid, and wrong. A hypothetical smarter-than-human AGI may be able to talk back and say "You're being stupid because you're not modelling the correct problem, and so your attempted solution is wrong." But that assumes hypothetical smarter-than-human AGI is also more-ethical-than-human - which unfortunately might be a bit of a reach. Bottom line - the limits of AI are set by the limits of human political intelligence. And since most human political systems operate at pre-scientific policy levels - the exception being the abuse of social and personal psychology to gain power - this isn't encouraging.
goto11 7y ago
"Patrolling" is pretty vague, the concern is primarily about groundless stopping, searches, arrests and shooting of suspects. It is discrimination if e.g. groundless searches are done at higher rates on people with a certain ethnicity, since presumed innocent individuals of any ethnicity should be treated equally and with the same rights. Stopping cars just because of the skin color of the driver is not "perceived as racist", it is racist, since you are treating people worse due to their race.
UncleMeat 7y ago
How do you objectively determine "areas of high crime"? That's a core problem. We don't have data on the actual incidence of crime, only data filtered through the justice system.

by daenz 7y ago

Reelin 7y ago

I suspect that there is indeed no winning, and that under such circumstances every possible course of action is likely to be perceived as racist by some number of people. This is because the population at large doesn't seem to be able to agree on what the word actually means (https://slatestarcodex.com/2017/06/21/against-murderism/ https://slatestarcodex.com/2017/06/21/against-murderism/). Regarding ML based predictive policing specifically, it seems like a spectacularly bad (but efficient and statistically effective!) idea to naively apply a machine learning based classification approach to such a problem.

ben_w 7y ago

It depends. Here are three different examples that would meet your description, with very different answers: 1) The X community has exactly the same, or lower, crime rates than the entire nation. However, nationwide anti-X sentiment means that despite this, most convicted criminals are from the X community. This makes it look like the regions where the X community live are high-crime regions. This is “accidentally racist”. Researchers know about this problem. 2) The X community is more prone to crime, and as this is purely an example, it just is and there’s no need to justify that. Extra police in this scenario is not racist, though I suspect anyone who jumps right in and assumes it to be true about the world might well be racist themselves. 3) A confounding variable, such as income or education, means that members of the X community are more likely to commit crimes than the general population, albeit it at the same rate as the equivalent income/education/confounding sunset of the general population. In this case, while it would not be racist to send in more police, it would totally be racist if politicians applied unequal effort to solve the confounding variable within the general population as compared specifically to group X.

wsxcde 7y ago

The problems of appropriate policing in so-called "high crime" neighborhoods are well understood. Many academic studies, as well as popular non-fiction like Jill Leovy's Ghettoside and Chris Hayes' Colony in a Nation, have discussed the issue. To sum up the literature in a few sentences, the problem is that minority neighborhoods are both overpoliced and underpoliced. There are a lot of useless arrests for minor crimes like jaywalking which makes the residents of these neighborhoods hostile to the police. (These arrests are driven by the debunked theory of broken window policing.) Simultaneously, there's not enough effort put into solving serious crimes like murder. In this context, the actual effect of predictive policing is that it ends up doing more of the useless over-policing, which unfortunately makes these neighborhoods even worse. So, how does this relate to your question? The point is that predictive policing is solving the wrong problem. What's needed are not more accurate neural nets predicting crime, but techniques for addressing the underly sociological factors that cause crime. Taking a step back and speaking broadly, Cory's point is that the focus on data and quantitative analysis is causing problems in two ways: (i) people are using quantitative methods to solve the wrong problems, and (ii) they seem to be oblivious to (and in some cases actively hostile to acknowledging) the harms being perpetrated by their methods. Both of these problems seem to be driven by a lack of understanding of well understood (but non-quantitative) social science literature.

deleted 7y ago
[deleted]
TheOtherHobbes 7y ago
Well, yes. That's the point. This form of AI will automate existing prejudices and misunderstandings. We're not really dealing with AI in any useful sense, but with automated bad policy biases, and the products and systems this generates should be labelled as such. Corollary - Big Data is political, but it can hide behind the pretence of objectivity. This shouldn't surprise anyone, but for some reason it does - perhaps because we're used to thinking of AI as the automation of the scientific method, when in fact it's just as likely to be the automation of all kinds of other things, some of which are nasty, stupid, and wrong. A hypothetical smarter-than-human AGI may be able to talk back and say "You're being stupid because you're not modelling the correct problem, and so your attempted solution is wrong." But that assumes hypothetical smarter-than-human AGI is also more-ethical-than-human - which unfortunately might be a bit of a reach. Bottom line - the limits of AI are set by the limits of human political intelligence. And since most human political systems operate at pre-scientific policy levels - the exception being the abuse of social and personal psychology to gain power - this isn't encouraging.

goto11 7y ago

"Patrolling" is pretty vague, the concern is primarily about groundless stopping, searches, arrests and shooting of suspects. It is discrimination if e.g. groundless searches are done at higher rates on people with a certain ethnicity, since presumed innocent individuals of any ethnicity should be treated equally and with the same rights. Stopping cars just because of the skin color of the driver is not "perceived as racist", it is racist, since you are treating people worse due to their race.

UncleMeat 7y ago

How do you objectively determine "areas of high crime"? That's a core problem. We don't have data on the actual incidence of crime, only data filtered through the justice system.