Nay, John, Law Informs Code: A Legal Informatics Approach to Aligning Artificial Intelligence with Humans (September 13, 2022). Northwestern Journal of Technology and Intellectual Property, Volume 20, Forthcoming, Available at SSRN: https://ssrn.com/abstract=4218031 or http://dx.doi.org/10.2139/ssrn.4218031

Artificial Intelligence (AI) capabilities are rapidly advancing, and highly capable AI could cause radically different futures depending on how it is developed and deployed. We are currently unable to specify human goals and societal values in a way that reliably directs AI behavior. Specifying the desirability (value) of an AI system taking a particular action in a particular state of the world is unwieldy beyond a very limited set of value-action-states. The purpose of machine learning is to train on a subset of states and have the resulting agent generalize an ability to choose high value actions in unencountered circumstances. But the function ascribing values to an agent’s actions during training is inevitably an incredibly incomplete encapsulation of the breadth of human values, and the training process is unavoidably a sparse exploration of states pertinent to all possible futures. Therefore, after training, AI is deployed with a coarse map of human preferred territory and will often choose actions unaligned with our preferred paths….We describe how the data generated by legal processes and the theoretical constructs and practices of law (methods of law-making, statutory interpretation, contract drafting, applications of standards, legal reasoning, etc.) can facilitate the robust specification of inherently vague human goals for AI. This helps with human-AI alignment and the local usefulness of AI. Toward society-AI alignment, we present a framework for understanding law as the applied philosophy of multi-agent alignment, harnessing public law as an up-to-date knowledge base of democratically endorsed values ascribed to state-action pairs. Although law is partly a reflection of historically contingent political power – and thus not a perfect aggregation of citizen preferences – if properly parsed, its distillation offers a legitimate computational comprehension of human goals and societal values. If law eventually informs powerful AI, engaging in the deliberative human political process to improve law takes on even more meaning.”