Michael A. Livermore (University of Virginia School of Law), Peter Beling (University of Virginia, Dept. of System & Information Engineering), Keith Carlson (Dartmouth College), Faraz Dadgostari (University of Virginia), Mauricio Guim (Instituto Tecnológico Autónomo de México (ITAM) – Law School), and Daniel Rockmore (Dartmouth College – Department of Mathematics; Dartmouth College – Department of Computer Science) have posted “Law Search In The Age Of The Algorithm” (2020 MICH. ST. L. REV. 1183) on SSRN. Here is the abstract:
The process of searching for relevant legal materials is fundamental to legal reasoning. However, despite its enormous practical and theoretical importance, law search has not been given significant attention by scholars. In this Article, we define the problem of law search and examine the consequences of new technologies capable of automating this core lawyerly task. We introduce a theory of law search in which legal relevance is a sociological phenomenon that leads to convergence over a shared set of legal materials and explore the normative stakes of law search. We examine ways in which law scholars can understand empirically the phenomenon of law search, argue that computational modeling is a valuable epistemic tool in this domain, and report the results from a multi-year, interdisciplinary effort to develop an advanced law search algorithm based on human-generated data. Finally, we explore how policymakers can manage the challenges posed by new machine learning-based search technologies.