Special Issue "Models of Law and Innovations in Law: Uses, Opportunities, and Practices"

Modeling methods are gaining ground as rapidly in law as they are elsewhere in our social life. Machine learning algorithms, increasingly prevalent in decision-making systems of many sorts, are created, trained, and deployed to recognize objects in images and videos, generate artwork, and, increasingly, to surveil and regulate. “Digital twin” models are being developed for everything from urban planning to medical research. Models of human cognition and behavior are increasingly prominent in policy making on topics as diverse as public health and mis- and dis-information.

At the same time, some newer theories of human consciousness and decision making posit modeling as a critical element of our subjective experience. For example, predictive coding and active inference theories suggest our internal model of the relevant world composes the contents of our consciousness and is constantly updated as our senses report errors from the model’s predictions. Legal decision making may involve the maintenance of mental models of legal causes and effects, categories, and expected outcomes.

Taken together, those developments reveal how interest in modeling spans numerous fields with overlaps and implications for law: information technology, health and medicine, psychology, neuroscience, economics, political science, philosophy, and computer science.

This Special Issue will explore both the modeling of law—as a tool to understand, criticize, and improve legal practice—and modeling in law—as a way to understand the phenomenology of legal practice, its normativity, and the sources of legal disagreement. It will consider both current research and policy making associated with models and examine opportunities and risks associated with modeling. For example, where and how is modeling useful, helpful, and appropriate for research uses, for policy design, and for legal analysis? What are the implications of models’ limits?