Applying inferential statistics to criminology is not new, but it appears that the market has been maturing. See, for instance, a recent article, “Police using ‘predictive analytics’ to prevent crimes before they happen”, published by Agence France-Presse on The Raw Story (Jul-29-2012).
Applying inferential statistics to criminology is not new, but it appears that the market has been maturing. See, for instance, a recent article, “Police using ‘predictive analytics’ to prevent crimes before they happen”, published by Agence France-Presse on The Raw Story (Jul-29-2012).
Setting aside obvious civil liberties questions, consider the application of this technology. My suspicion is that targeting police efforts by geographic locale and day-of-week/time-of-day using this approach will decrease the overall level of crime, but by how much is not clear. This is typical of problems faced by businesses: It is not enough to predict what we already know, nor is it enough to trot out glowing but artificial technical measures of performance. Knowledge that real improvement has occurred requires more. For instance, at least some effect of police effort on the street does not decrease crime, but merely moves to new locations.
Were I mayor of a small town approached by the vendor of such a solution, I’d want to see some sort of experimental design which made apples-to-apples comparison between our best estimates of what happens with the new tool, and what happens without it. Only once this firm measure of benefit has been obtained could one reasonably weigh it against the financial and political costs.
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