The pressure on the criminal justice system in England and Wales is mounting. Recent figures reveal that despite a rise in recorded crime, the number of defendants in court proceedings has been the lowest in 50 years. This indicates a crisis of access to criminal justice. Predictive policing and risk assessment programmes based on algorithmic decision making (ADM) offer a prospect of increasing efficiency of law enforcement, eliminating delays and cutting the costs. These technologies are already used in the UK for crime-mapping and facilitating decisions regarding prosecution of arrested individuals. In the US their deployment is much wider, covering also sentencing and parole applications.

Machine-Learnt Bias? Algorithmic Decision Making and Access to Criminal Justice / M.A. Wojcik. - In: LEGAL INFORMATION MANAGEMENT. - ISSN 1472-6696. - 20:2(2020), pp. 99-100. [10.1017/s1472669620000225]

Machine-Learnt Bias? Algorithmic Decision Making and Access to Criminal Justice

M.A. Wojcik
2020

Abstract

The pressure on the criminal justice system in England and Wales is mounting. Recent figures reveal that despite a rise in recorded crime, the number of defendants in court proceedings has been the lowest in 50 years. This indicates a crisis of access to criminal justice. Predictive policing and risk assessment programmes based on algorithmic decision making (ADM) offer a prospect of increasing efficiency of law enforcement, eliminating delays and cutting the costs. These technologies are already used in the UK for crime-mapping and facilitating decisions regarding prosecution of arrested individuals. In the US their deployment is much wider, covering also sentencing and parole applications.
Settore GIUR-17/A - Filosofia del diritto
2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1203635
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