Law is Code: A Software Engineering Approach to Analyzing the United States Code

75 Pages Posted: 21 Oct 2014  

William Li

Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Pablo Azar

Massachusetts Institute of Technology, Sloan School of Management, Students

David Larochelle

Harvard University - Berkman Klein Center for Internet & Society

Phil Hill

Harvard Law School; Harvard University - Berkman Klein Center for Internet & Society

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER); Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Date Written: September 21, 2014

Abstract

The agglomeration of rules and regulations over time has produced a body of legal code that no single individual can fully comprehend. This complexity produces inefficiencies, makes the processes of understanding and changing the law difficult, and frustrates the fundamental principle that the law should provide fair notice to the governed. In this article, we take a quantitative, unbiased, and software-engineering approach to analyze the evolution of the United States Code from 1926 to today. Software engineers frequently face the challenge of understanding and managing large, structured collections of instructions, directives, and conditional statements, and we adapt and apply their techniques to the U.S. Code over time. Our work produces insights into the structure of the U.S. Code as a whole, its strengths and vulnerabilities, and new ways of thinking about individual laws. For example, we identify the first appearance and spread of important terms in the U.S. Code like "whistleblower" and "privacy." We also analyze and visualize the network structure of certain substantial reforms, including the Patient Protection and Affordable Care Act (PPACA) and the Dodd-Frank Wall Street Reform and Consumer Protection Act, and show how the interconnections of references can increase complexity and create the potential for unintended consequences. Our work is a timely illustration of computational approaches to law as the legal profession embraces technology for scholarship, to increase efficiency, and to improve access to justice.

Suggested Citation

Li, William and Azar, Pablo and Larochelle, David and Hill, Phil and Lo, Andrew W., Law is Code: A Software Engineering Approach to Analyzing the United States Code (September 21, 2014). Available at SSRN: https://ssrn.com/abstract=2511947 or http://dx.doi.org/10.2139/ssrn.2511947

William Li (Contact Author)

Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL) ( email )

77 Massachusetts Avenue
Room 32-337
Cambridge, MA 02139
United States

HOME PAGE: http://people.csail.mit.edu/wli

Pablo Azar

Massachusetts Institute of Technology, Sloan School of Management, Students ( email )

Cambridge, MA 02139
United States

David Larochelle

Harvard University - Berkman Klein Center for Internet & Society ( email )

Harvard Law School
23 Everett, 2nd Floor
Cambridge, MA 02138
United States

Phil Hill

Harvard Law School ( email )

1563 Massachusetts Ave
Cambridge, MA 02138
United States

Harvard University - Berkman Klein Center for Internet & Society ( email )

Harvard Law School
23 Everett, 2nd Floor
Cambridge, MA 02138
United States

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-618
Cambridge, MA 02142
United States
617-253-0920 (Phone)
781 891-9783 (Fax)

HOME PAGE: http://web.mit.edu/alo/www

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Stata Center
Cambridge, MA 02142
United States

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