From Holmes to AlphaGo
Thomas D. Grant, Damon Wischik · 2020
Holmes’s enduring interest was in the development of the law, as indicated by the title The Path of the Law. He drew on the philosophy of science and the role of induction in forming scientific theories, and he added a new ingredient: social induction. Social induction has two parts. First, the law develops through the accumulation of cases, which arise through the actions of agents who are embedded within society and who necessarily adapt their actions to the law. This is analogous to a subfield of machine learning called reinforcement learning, the basis for DeepMind’s AlphaGo, in which the machine is trained on a dataset of its own adaptive actions. The second part of social induction is the process whereby settled legal doctrine arises out of contested judicial decisions. We argue that this second part can be formulated in terms of prediction (law is constituted, after all, by prophecies of what courts will do), and that it is therefore a suitable topic for machine learning. This suggests new ways of thinking about explainability of machine learning decisions.