scholarly journals Criminal law and behavioral law and economics: observations on the neglected role of uncertainty in deterring crime

1999 ◽  
Vol 1 (1) ◽  
pp. 276-312 ◽  
Author(s):  
Alon Harel ◽  
Uzi Segal
Author(s):  
Eyal Zamir ◽  
Doron Teichman

In the past few decades, economic analysis of law has been challenged by a growing body of experimental and empirical studies that attest to prevalent and systematic deviations from the assumptions of economic rationality. While the findings on bounded rationality and heuristics and biases were initially perceived as antithetical to standard economic and legal-economic analysis, over time they have been largely integrated into mainstream economic analysis, including economic analysis of law. Moreover, the impact of behavioral insights has long since transcended purely economic analysis of law: in recent years, the behavioral movement has become one of the most influential developments in legal scholarship in general. Behavioral Law and Economics offers a state-of-the-art overview of the field. The book surveys the entire body of psychological research underpinning behavioral analysis of law, and critically evaluates the core methodological questions of this area of research. The book then discusses the fundamental normative questions stemming from the psychological findings on bounded rationality, and explores their implications for establishing the aims of legislation, and the means of attaining them. This is followed by a systematic and critical examination of the contributions of behavioral studies to all major fields of law—property, contracts, consumer protection, torts, corporate, securities regulation, antitrust, administrative, constitutional, international, criminal, and evidence law—as well as to the behavior of key players in the legal arena: litigants and judicial decision-makers.


Author(s):  
Chelsea Barabas

This chapter discusses contemporary debates regarding the use of artificial intelligence as a vehicle for criminal justice reform. It closely examines two general approaches to what has been widely branded as “algorithmic fairness” in criminal law: the development of formal fairness criteria and accuracy measures that illustrate the trade-offs of different algorithmic interventions; and the development of “best practices” and managerialist standards for maintaining a baseline of accuracy, transparency, and validity in these systems. Attempts to render AI-branded tools more accurate by addressing narrow notions of bias miss the deeper methodological and epistemological issues regarding the fairness of these tools. The key question is whether predictive tools reflect and reinforce punitive practices that drive disparate outcomes, and how data regimes interact with the penal ideology to naturalize these practices. The chapter then calls for a radically different understanding of the role and function of the carceral state, as a starting place for re-imagining the role of “AI” as a transformative force in the criminal legal system.


Author(s):  
Richard H. McAdams ◽  
Thomas S. Ulen

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