Although the revolutionary potential of predictive policing has often been exaggerated, this novel policing strategy nonetheless implies something substantially new: the underlying methods of (crime) data analysis. Moreover, these police prediction tools matter not only because of their capacity to generate near-term crime predictions but also because they have the potential to generally enhance police-related data crunching, ultimately giving rise to the comprehensive datafication of police work, creating an ongoing drive for extensive data collection and, hence, surveillance. This paper argues that because of its enablement of crime data analysis in general, predictive policing software will be an important incubator for datafied police work, especially when executed via data mining platforms, because it has made police authorities aware that the massive amounts of crime data they possess are quite valuable and can now be easily analyzed. These data are perceived to be even more useful when combined with external data sets and when processed on the largest possible scale. Ultimately, significant transformative effects are to be expected for policing, especially in relation to data collection practices and surveillance imperatives.

中文翻译：

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预测性警务与警察工作平台化

尽管预测性警务的革命性潜力经常被夸大，但是这种新颖的警务策略仍然隐含着一些新的东西：（犯罪）数据分析的基本方法。此外，这些警察预测工具之所以重要，不仅因为它们具有生成近期犯罪预测的能力，而且还因为它们有可能总体上增强与警察有关的数据处理能力，最终导致对警察工作的全面数据化，从而形成了持续不断的发展趋势。推动广泛的数据收集并因此进行监视。本文认为，由于预测性警务软件总体上支持犯罪数据分析，因此它将成为数据化警察工作的重要孵化器，尤其是通过数据挖掘平台执行时，因为它使警察当局意识到他们拥有的大量犯罪数据非常有价值，现在可以轻松对其进行分析。当将这些数据与外部数据集组合并以最大可能的规模进行处理时，这些数据被认为更加有用。最终，治安工作将产生重大的变革影响，特别是在数据收集实践和监督命令方面。