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Comment by daenz | Hacker News Reader

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.

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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.

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.

> 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.

Slightly off context but I think that the solution to this is some kind of quota and or tier system to laws and policing. Basically to restrict the amount of policing that may be done for things like jaywalking and traffic violations while the violent crime rate is above a certain threshold.

I have been held at gun point twice in my life as part of armed robbery and hijacking and neither time did I even consider for a moment that the police would find the people who did it. But if I do 60 km/h in a 40 km/h zone they will follow me to the end of the earth to get me to pay them.

Broken windows policing is not "debunked". A lot of people would prefer for ideological reasons that it not work, but it does. Anyone who lived in NYC can tell you that.

Speaking of NYC specifically, a lot of cities across the US, as well as worldwide, experienced a major decrease in crime at the same time that NYC did. Most of the cities were not practicing broken window policing. That's one reason to be skeptical.

From an academic perspective, it is true that there is some debate about the efficacy of broken windows policing, but even the most supportive academic studies find only a small correlation between violations of "order" (like jaywalking and graffiti) more serious crimes. There's just isn't any evidence at all that the way to reduce serious crimes is by going after jaywalkers.

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.

"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.

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.

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/).

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.

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