Predictive policing is quite the buzz word these days. IBM (via SPSS) is one of the big players in the field. The most common use case is burglary, I suspect because that's somewhat easy (and also directly actionable). You rarely find other use cases in academic papers (well I only browsed the literature a couple of times preparing for related projects).
The basic idea is sending more police patrols to areas that are identified as high thread and thus using your available resources more efficiently. The focus in that area is more on objects/areas than on individuals so you don't try to predict who's a criminal but rather where they'll strike.
It sounds like a good enough idea in theory but at least in Germany I know that research projects for predictive policing will be scaled down due to privacy concerns even if the prediction is only area and not person based (noteworthy that that's usually mentioned by the police as a reason why they won't participate in the research). I'm not completely sure and only talked to a couple of state police research people but quite often the data also involves social media in some way and that's the major problem from what I can tell.
I’m biased, so I would give the most weight to what the computer science department says.
Predictive policing absolutely does work in some aspects. The opposite of predictive policing is to have all beat cops equidistant from each other in their jurisdiction. This is clearly wrong. The next step is to have cops near population centers, then around areas where there have been more reports, requests, etc. After that you move to time to day. Where you place cops during the day vs night is clearly different. Shops close, bars open. Places where young adults vs seniors gather will clearly have different coverage. Pretty much every study in the subject shows people age out of crime. This is used as supporting evidence against lifetime sentences and geriatric incarceration.
I have to assume only the most naive software will have an algorithm that uses secondary indicators / simplest predictive techniques would get such attention. For example “black neighborhoods” (that happen to be poor, with no other stats other than other departments say they have issues with black neighborhoods) and self fulfilling prophecies (we put most cops at location X and what a surprise, that location had the most arrests, w/o looking at the arrests themselves)
the report discusses multiple different types of predictive analysis, including the type you refer to (location and time based) but also personal: predicting which people might commit crimes, based on social media surveillance. that's a long ways from what police have always done.
I think there's a big difference in using it to predict who will commit a crime (a big nono imo) vs. where a crime will be committed. For example allocating patrols by likelyhood of breakins seems acceptable to me and might even free up resources for more important tasks. Same for mundane stuff like more patrol cars/checks for areas with more potential speeding violations/car accidents due to reckless driving etc.
Statistical analysis to figure the optimal use of police resources is a great idea, particularly to prevent violent crime and theft in public areas.
What concerns me, however, is the idea of predictive analytics being used on the vast databases collected by NSA/GCHQ (there's no reason to suspect they're not doing this already). Such a system of "pre-crime" would be bound to have false positives, and suddenly based on your Google searches, movie preferences, musical tastes, friendships, or who knows what, the state decides that you are a "person of interest".
I guess it depends on what we would want from crime predictions.
Do we want a Minority Report type system where someone shows up right before the crime and prevents it?
They mention burglary. I'm guessing most buglers aren't seasoned professional buglers and rather it is a crime of opportunity. So if a cop is on the street they won't do it ... but maybe they'll do it the next street over, 20 minutes later?
Even if somehow there was better prediction, there really aren't enough police to patrol the target street, and the next one over, and the next one ... predictions may suppose infinite police resources would prevent it, but that's not a thing.
This might be a topic where 'prevention' isn't really possible.
Predicting crime is great. It means you're working to understand the state of your society.
Using it for policing is idiotic. You can't arrest a statistic.
Instead, it should be used for public policy, to understand what communities are at risk, direct efforts to understand why they are risk, and engineer better systems to support those communities.
China perfected this all for us and now the U.S. government can piggyback off of their practices... great.
Serious note - the below is such a scary concept. There is a line somewhere and this feels like you are starting to cross it... both place-based and person-based predictive policing sound ripe for profiling / instigating actions that police can use as a reason to arrest an otherwise harmless person.
"Predictive policing programs are another illustrative example showing how data, surveillance technology, and a system of automated policing work together to spy on, search, and, ultimately, control Americans who have not committed or been convicted of a crime.
Predictive policing is premised on the idea that historical data of crime, demographics, socioeconomics, and geography can be used to forecast future incidents. Knowing where crime is likely to occur again, police try to intervene beforehand and prevent it.
Broadly there are two kinds of “heat maps” produced by predictive policing models: place-based, which uses less data to try to avoid systemic pitfalls of relying on crime and demographic data and surges police into specific areas, and person-based, which tracks and creates a list of “high-risk” individuals by combining a person's criminal history with an analysis of their social network. "
Predictive policing systems seem like they will be very difficult to properly validate. On the one hand, it could go like the drug industry where there are bodies "testing" potential solutions, but the money, incentives, and sheer noise make the results highly suspect. On the other hand, cities and towns may prove to be a good experimentation framework, in the same way that laws are "tested" at the country/state level. I'm curious to see if much useful will come out of this, and how long it will take.
Back before computers were a thing in most people's homes, let alone pockets, police would plot on a map the crime reports of the past year and assign more patrols to areas with a high density of crime.
Is this practice now banned? Because this is predictive policing, albeit in a crude form. Presumably it just means computerized predictive policing, but it still seems odd that people see to think that analyzing past patterns of crime to better allocate police is something novel.
Predictive policing is old, and has been done in consultation with universities before. There are papers on predicting crime vs criminals, predicting by time and address, predicting by age, etc., including discussion on whether this leads to uneven enforcement on minorities. It would be surprising to expect law enforcement to go towards less statistical and software usage.
What would be new would be formal preemptive detention by generic factors. Then again there was news covered by the Guardian on a police black site in Chicago that held thousands of largely black detainees without lawyers.
This is such a German judgement. So the police are using big data to predict who will commit crimes, which is sort of dystopian.
Police in the United States are close to this already. Chicago's police department used to brag about its data-crunching ability to predict where crime would happen. At the time, it was just by area, but it was stated that with enough data, it could be narrowed down to the block. It's not that big a leap to extrapolate that to the individual.
My guess, though, is that it didn't work, and the city was just parroting the promises made by the salespeople of whatever system they bought for this task. If it worked, then police would preemptively flood certain areas where they know crime is about to happen. But, as is seen on television most nights, and in the complaints of the aldermen, the police mostly seem to react to crime, rather than prevent it. The use of social media by crime mobs has only made it worse.
This appears to be the primary concern raised in the article. But surely data scientists could put in guards against this, such as weighting the crime count versus the time spent policing the area? In fact, presumably any functional predictive policing system must already do that, else you'd just tend towards policing one area incredibly intensively.
If they are concerned about the police arrest stats or racism biasing the data set, they could keep the input to something hard to interfere with, like where murders occur or where crimes are reported by the public, rather than where arrests occur.
My opinion is that predictive policing does need regulation, but banning it entirely, to me, seems like an overreaction that will over time result in much less effective use of police resources. I suppose time will tell.
This is dumb. Predictive policing algorithms predict where the police will be, not where crime takes place: as crime data is simply a measurement of policing activity.
If there is bias in policing, it would therefore be amplified.
The basic idea is sending more police patrols to areas that are identified as high thread and thus using your available resources more efficiently. The focus in that area is more on objects/areas than on individuals so you don't try to predict who's a criminal but rather where they'll strike. It sounds like a good enough idea in theory but at least in Germany I know that research projects for predictive policing will be scaled down due to privacy concerns even if the prediction is only area and not person based (noteworthy that that's usually mentioned by the police as a reason why they won't participate in the research). I'm not completely sure and only talked to a couple of state police research people but quite often the data also involves social media in some way and that's the major problem from what I can tell.
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