Professor Dr. Lisa Shay of the West Point Department of Electrical Engineering and Computer Science, and colleagues, presented a paper entitled Do Robots Dream of Electric Laws? An Experiment in Law as Algorithm, at We Robot 2013 Conference, held 8-9 April 2013 at Stanford Law School.
Here is the abstract:
Due to recent advances in computerized analysis and robotics, automated law enforcement has become technically feasible. Unfortunately, laws were not created with automated enforcement in mind, and even seemingly simple laws have subtle features that require programmers to make assumptions about how to encode them. We demonstrate this ambiguity with an experiment where a group of 52 programmers was assigned the task of automating the enforcement of traffic speed limits. A late model vehicle was equipped with a sensor that collected actual vehicle speed over an hour long commute. The programmers (without collaboration) each wrote a program that computed the number of speed limit violations and issued mock traffic tickets. Despite quantitative data for both vehicle speed and the speed limit, the number of tickets issued varied from none to one per sensor sample above the speed limit. Our results from the experiment highlight the significant deviation in number and type of citations issued during the course of the commute, based on legal interpretations and assumptions made by programmers untrained in the law. These deviations were mitigated, but not eliminated, in one sub-group that was provided with a legally reviewed software design specification, providing insight into ways to automate the law in the future. Automation of legal reasoning is likely to be the most effective in contexts where legal conclusions are predictable because there is little room for choice in a given model; that is, they are determinable. Yet this experiment demonstrates that even relatively narrow and straightforward “rules” can be problematically indeterminate in practice.
Tags: Ambiguity in statutory language, Ambiguity of legal rules, Criminal law algorithms, Criminal law information systems, Determinacy of legal rules, Gregory Conti, Indeterminacy of legal rules, John Nelson, Law as algorithm, Law enforcement algorithms, Legal algorithms, Lisa Shay, Modeling criminal law violations, Modeling criminal laws, Modeling legal rules, Modeling traffic law violations, Modeling violations of criminal law as algorithm, Modeling violations of law as algorithm, Traffic law algorithms, We Robot, We Robot 2013, Woodrow Hartzog