'Law as Data' explores radical leap for legal analysis
Four thousand years ago, human societies underwent a fundamental transition when the rules governing how people interact shifted from oral custom to written laws: first captured in stone tablets such as the Code of Hammurabi, then migrating to scrolls and eventually printed law books. In recent years, the law has leaped from the analog to the digital, breaking out of the law library and onto any computer, tablet, or phone with an internet connection. This shift has the potential to radically revise how law is experienced, practiced, and studied.
From lawyer-bots appealing parking tickets to machine learning algorithms finding the smoking gun document in high stakes litigation, from predicting legal outcomes to understanding how the public responds to climate regulations, change is coming to the law. Driving this transformation is the digitization of legal texts alongside new insights and technologies from statistics, computer science, and data analytics.
Law as Data, borne out of a transdisciplinary Santa Fe Institute working group, explores the new field of computational legal analysis—the study of the law that uses legal texts as data. Providing an introduction to this new field for the broader legal world, this volume emphasizes experimental work that pushes methodological boundaries and expands the horizons of legal analysis.
According to editors Michael A. Livermore, Professor of Law at the University of Virginia, and SFI External Professor Daniel N. Rockmore, William H. Neukom 1964 Professor of Computational Science and Professor of Mathematics and Computer Science at Dartmouth College, "It is impossible to know how computational legal studies will reshape how the law is understood, but the process of transformation has already begun."
Law as Data is the third volume in the SFI Press's Seminar series, which publishes new findings from the Institute's ongoing workshops, working groups, and research projects aimed at an audience of interdisciplinary scholars and practitioners. The innovative chapters in this book are likely to be of particular interest to legal scholars; scholars in other fields interested in empirical legal studies, such as political science and economics; and researchers in fields related to applied quantitative text analysis, such as computer science and digital humanities.