Prediction, Presumption, Preemption: The Path Of Law After The Computational Turn

Prediction, Presumption, Preemption: The Path of Law After the Computational Turn‘, forthcoming in Privacy, Due Process and the Computational Turn: The Philosophy of Law Meets the Philosophy of Technology, eds. Mireille Hildebrandt & Ekaterina De Vries.

This chapter examines the path of law after the computational turn. In framing my argument, I use Oliver Wendell Holmes Jr.’s famous “bad man” theory as a heuristic device for evaluating predictive technologies currently embraced by public and private sector entities worldwide. Perhaps America’s most famous jurist, Holmes was so fascinated by the power of predictions and the predictive stance that he made prediction the centerpiece of his own prophecies regarding the future of legal education. Holmes believed that predictions should be understood with reference to the standpoint of everyday people, made from their point of view and operationalized with their sense of purpose in mind.

In this chapter, I argue that Holmes’ vision is rapidly giving way to a very different model: machines making predictions about individuals for the benefit of institutions. This trend in today’s predictive technologies, I suggest, threatens due process by enabling a dangerous new philosophy of pre-emption. My primary concern is that the perception of increased efficiency and reliability in the use of predictive technologies might be seen as justification for a fundamental jurisprudential shift from our current ex post facto systems of penalties and punishments to ex ante preventative measures. Such a shift, I argue, would fundamentally alter the path of law by undermining the core presumptions and procedures built into the fabric of today’s retributive model of social justice, many of which would be pre-empted by tomorrow’s “actuarial justice”. Given the foundational role that due process values play in our legal system, I raise the question of whether law ought to set reasonable limits on the types of presumptions and predictions that institutions are permitted to make about people without their involvement or participation. While reliability, efficiency, and the bottom line will continue to be important social goals, I am concerned that to limit the discussion to issues of system design is to ignore the insight underlying the presumption of innocence and associated due process values—namely, that there is wisdom in setting boundaries around the kinds of assumptions that can and cannot be made about people.

This chapter does not offer concrete solutions; rather, it is written in the hopes of inspiring further research in the area of important threshold issues about the broader permissibility of prediction, pre-emption and presumption in the face of the computational turn.

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