II2,3 Complexity science has spread from its origins in the physical sciences into biological and social sciences (1). In- creasingly, the social sciences frame policy problems from the financial system to the food system as complex adaptive systems (CAS) and urge policy- makers to design legal solutions with CAS properties in mind. What is often poorly recognized in these initiatives is that legal systems are also complex adaptive systems (2). Just as it seems unwise to pursue regulatory measures while ignoring known CAS properties of the systems targeted for regulation, so too might failure to appreciate CAS qualities of legal systems yield policies founded upon unrealistic as- sumptions. Despite a long empirical studies tradition in law, there has been little use of complexity science. With few robust empirical studies of legal systems as CAS, researchers are left to gesture at seemingly evident assertions, with limited scientific sup- port. We outline a research agenda to help fill this knowledge gap and ad- vance practical applications. Legal systems exhibit what com- plexity scientists identify as hallmark elements of CAS (1). The diverse in- stitutions (e.g., legislatures, agencies, and courts); norms (e.g., due process, equality, and fairness); actors (e.g., legislators, bureaucrats, and judges); and instruments (e.g., regulations, injunctions, and taxes) are intercon- nected through stochastic processes (e.g., trials, negotiations, and rule- makings) with feedback mechanisms (e.g., appeals to higher courts and ju- dicial review of legislation). These are all em- bedded in hierarchical and nonhierarchical network architectures (e.g., cross-references (e.g., emergence of common-law doctrines or codified statutory law). Agents typically exercise bounded rationality, have only par- tial information, and are able to exercise only varying degrees of control on overall system behavior (2). Efforts to integrate CAS approaches to regulated systems may flounder if complex adaptive characteristics of the legal system it- self are not taken into account. For example, although natural-resources policy theorists have advocated for a new field of adaptive management based on an understanding and judicial systems (4). CAS approaches can allow modeling of interconnections in this system of systems that can be difficult to capture in simple models (1). Minor changes in network structure may lead to cascade ef- fects throughout the systems. By leveraging traditional methods, it is difficult to isolate instability and systemic risk in other social systems from instability and systemic risk in the legal system. Regulatory system failure was a factor in the 2008 financial crisis (5) and the Deepwater Horizon oil spill (6). THEORY, ANALYSIS, APPLICATION Application of informatics and big-data– styled research to law offers many potential benefits for conventional empirical legal studies. The CAS framework is neither an extension of nor a replacement for that ap- proach but a different way of envisioning systems in which agent strategies and sys- SCIENCE AND LAW Harnessing legal complexity Bring tools of complexity science to bear on improving law U.S. Supreme Court term Percentage of cases contained within giant component Giant component (%) 60 1805 1810 1810 1815 1820 1820 1825 1830 1830 1835 50 40 30 20 10 0 United States Supreme Court citation network (1805–1835) Cases are represented as nodes, citations between cases as edges. Emergence of a giant [connected] component after 1815, a hallmark phenomenon in complex systems, represents a transition from jurisprudential reliance on foreign to domestic law following the War of 1812 (4). We include all cases that had been cited at least once over the Court’s history (1791–2015). For figure code and data, see https://github.com/mjbommar/legal-complexity-science. on March 30, 2017 http://science.sciencemag.org/ Downloaded from J.B. Ruhl, Daniel Martin Katz & Michael Bommarito, Harnessing Legal Complexity, 355 Science 1377 (2017)
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