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Administrative Law In The Automated State, Cary Coglianese
Administrative Law In The Automated State, Cary Coglianese
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In the future, administrative agencies will rely increasingly on digital automation powered by machine learning algorithms. Can U.S. administrative law accommodate such a future? Not only might a highly automated state readily meet longstanding administrative law principles, but the responsible use of machine learning algorithms might perform even better than the status quo in terms of fulfilling administrative law’s core values of expert decision-making and democratic accountability. Algorithmic governance clearly promises more accurate, data-driven decisions. Moreover, due to their mathematical properties, algorithms might well prove to be more faithful agents of democratic institutions. Yet even if an automated state were …
In-Group Bias And The Police: Evidence From Award Nominations, Nayoung Rim, Roman G. Rivera, Bocar A. Ba
In-Group Bias And The Police: Evidence From Award Nominations, Nayoung Rim, Roman G. Rivera, Bocar A. Ba
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This paper examines the impact of in-group bias on the internal dynamics of a police department. Prior studies have documented racial bias in policing, but little is known about bias against officers due to lack of available data. We construct a novel panel dataset of Chicago Police Department officers, with detailed information on officer characteristics and work productivity. Exploiting quasi-random variation in supervisor assignment, we find that white supervisors are less likely to nominate black officers than white or Hispanic officers. We find weaker evidence that male supervisors are less likely to nominate female officers than male officers. We explore …
Tightening The Ooda Loop: Police Militarization, Race, And Algorithmic Surveillance, Jeffrey L. Vagle
Tightening The Ooda Loop: Police Militarization, Race, And Algorithmic Surveillance, Jeffrey L. Vagle
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This Article examines the role military automated surveillance and intelligence systems and techniques have supported a self-reinforcing racial bias when used by civilian police departments to enhance predictive policing programs. I will focus on two facets of this problem. First, my research will take an inside-out perspective, studying the role played by advanced military technologies and methods within civilian police departments, and how they have enabled a new focus on deterrence and crime prevention by creating a system of structural surveillance where decision support relies increasingly upon algorithms and automated data analysis tools, and which automates de facto penalization and …