Conti et al.: A Conservation Theory of Governance for Automated Law Enforcement

Professor Dr. Gregory Conti , Professor Dr. Woodrow Hartzog , Professor Dr. John Nelson , and Professor Dr. Lisa A. Shay have posted the full text of their paper entitled A Conservation Theory of Governance for Automated Law Enforcement , presented this week at We Robot 2014, at the University of Miami in Coral Gables, Florida, USA.

Here is the abstract:

Continued advances in robotic technology, distributed sensor networks, and computerized analysis have made possible the automation of the entire law enforcement process, from detection of a crime, to identification of the perpetrator, to imposition of punishment. While this augurs well for more efficient and lower cost systems as inefficient and relatively expensive manual labor is replaced by robots and computers, governments and citizens must look beyond these obvious savings to assess the more subtle, but arguably more important, costs to society. To facilitate better decision making about when, where, and to what extent a law enforcement process should be automated, we propose a conservation theory of governance for automated law enforcement (ALE).

While efficiency and determinacy are often lauded as advantages for employing computers and robots over humans, inefficiency and indeterminacy have significant value in ALE systems and should be preserved in order to prevent severe societal harms. The conservation theory of governance for ALE states that those introducing or increasing

automation in one part of the ALE system should evaluate the entire system holistically and ensure that inefficiency and indeterminacy are explicitly preserved or increased in other parts of the system.

Filed under: Applications, Articles and papers, Conference papers, Policy debates, Technology developments Tagged: Automated law enforcement, Conservation theory of governance for automated law enforcement, Criminal law information systems, Gregory Conti, Indeterminacy in law enforcement information systems, Indeterminacy in legal information systems, Indeterminacy in policing information systems, Inefficiency in law enforcement information systems, Inefficiency in legal information systems, Inefficiency in policing information systems, John Nelson, Law enforcement information systems, Legal prediction, Lisa A. Shay, Policing information systems, Predictive policing, Quantitative legal prediction, We Robot, We Robot 2014, Woodrow Hartzog



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