We are witnessing an upsurge in crime forecasting software, which supposedly draws predictive knowledge from data on past crime. Although prevention and anticipation are already embedded in the apparatuses of government, going beyond a mere abstract aspiration, the latest innovations hold out the promise of replacing police officers’ “gut feelings” and discretionary risk assessments with algorithmic-powered, quantified analyses of risk scores. While police departments and private companies praise such innovations for their cost-effective rationale, critics raise concerns regarding their potential for discriminating against poor, black, and migrant communities. In this article, I address such controversies by telling the story of the making of CrimeRadar, an app developed by a Rio de Janeiro-based think tank in partnership with private associates and local police authorities. Drawing mostly on Latour’s contributions to the emerging literature on security assemblages, I argue that we gain explanatory and critical leverage by looking into the mundane practices of making and unmaking sociotechnical arrangements. That is, I address the chain of translations through which crime data are collected, organized, and transformed into risk scores. In every step, new ways of seeing and presenting crime are produced, with a significant impact on how we experience and act upon (in)security.

中文翻译：

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犯罪预测的形成：社会技术组合和治理未来犯罪的争议

我们正在目睹犯罪预测软件的热潮，据称该软件从过去犯罪的数据中提取预测知识。尽管预防和预期已经嵌入到政府机构中，超越了单纯的抽象愿望，但最新的创新有望用算法驱动的风险评分量化分析取代警察的“直觉”和酌情风险评估. 虽然警察部门和私营公司赞扬此类创新具有成本效益的理由，但批评者对其可能歧视贫困、黑人和移民社区的可能性提出了担忧。在这篇文章中，我通过讲述犯罪雷达的制作故事来解决这些争议，由位于里约热内卢的智囊团与私人合伙人和当地警察当局合作开发的应用程序。主要借鉴拉图尔对新兴安全组合文献的贡献，我认为通过研究制定和取消社会技术安排的世俗实践，我们可以获得解释性和批判性的影响力。也就是说，我将讨论犯罪数据收集、组织和转化为风险评分的转化链。在每一步中，都会产生看待和呈现犯罪的新方式，对我们如何体验和采取（不）安全的方式产生重大影响。我认为，通过研究制定和取消社会技术安排的世俗实践，我们可以获得解释性和批判性的影响力。也就是说，我将讨论犯罪数据收集、组织和转化为风险评分的转化链。在每一步中，都会产生看待和呈现犯罪的新方式，对我们如何体验和采取（不）安全的方式产生重大影响。我认为，通过研究制定和取消社会技术安排的世俗实践，我们可以获得解释性和批判性的影响力。也就是说，我将讨论犯罪数据收集、组织和转化为风险评分的转化链。在每一步中，都会产生看待和呈现犯罪的新方式，对我们如何体验和采取（不）安全的方式产生重大影响。