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Predictive policing is the practice of using artificial intelligence to predict future crimes. Often, this involves predicting their timing and location—so-called place-based applications—but it can also involve identifying individuals who are thought to be at particularly high risk of committing crimes, as in Chicago’s “Heat List” (Gorner 2013). In this paper, I propose a new objection to predictive policing that does not depend on its accuracy or bias. I will argue a policy of using predictive policing could be morally flawed because it erodes public trust in a way that, in the long run, can undermine cooperation between police and communities and cause other impediments that hinder the functioning of the criminal justice system. This paper applies a lesson long appreciated in the philosophy of technology: that new technologies, which purport to accomplish a goal more efficiently or successfully than before, can create externalities that exacerbate serious problems elsewhere in their complex social context.

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Speaker Bio

Dr. Ryan Jenkins is an associate professor of philosophy and a senior fellow at the Ethics + Emerging Sciences Group at California Polytechnic State University in San Luis Obispo. He studies the ethics of emerging technologies, especially automation, cyber war, autonomous weapons, and driverless cars. His work has appeared in journals such as Techne, Ethical Theory and Moral Practice, and the Journal of Military Ethics, as well as public fora including the Washington Post, Slate and Forbes.