Legal and Ethical Issues in the Prediction of Recidivism

By M. Tonry. 2014

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Subfields: Law, Sociology and Political Science

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Fairness in Criminal Justice Risk Assessments: The State of the Art (2017, background): “…and Stevenson 2016), government agencies (National Science and Technology Council 2016:30-32), foundations (Pew Center of the States 2011), and academics (Berk 2008; Berk and Hyatt 2015; Demuth 2003; Hamilton 2016; Harcourt 2007; Hyatt, Chanenson, and Bergstrom 2011; Starr 2014b; Tonry 2014).”
An impact assessment of machine learning risk forecasts on parole board decisions and recidivism (2017, background): “But, the past few years have seen increased scrutiny and controversy surrounding the use of actuarial risk assessments for a variety of criminal justice decisions (Gottfredson and Moriarty 2006; Conroy 2006; Berk 2012; Tonrey 2014; Monahan and Skeem 2014).”
A Primer on Fairness in Criminal Justice Risk Assessments (2016, background): “…Department of Criminology Department of Statistics University of Pennsylvania Introduction There are widespread concerns about fairness when actuarial risk assessments are used to inform criminal justice decisions (Harcourt, 2008; Tonrey, 2014; Starr, 2014; Berk and Hyatt, 2015, Crawford, 2016).”
Machine Learning Risk Assessments in Criminal Justice Settings (2018, background): “Current practice is far more sophisticated and nuanced, but some can still reasonably ask whether actuarial justice is a good thing (Feeley and Simon 1994; Buruma 2004; Robert 2005; Monahan 2006; Harcourt 2007; Boonin 2011; Tonry 2014; Starr 2014; Ferguson 2017; Huq 2019).”
Risk Assessment in Criminal Sentencing. (2016, background): “, while on probation, parole, or bail) all reflect the depth of an offender’s involvement in crime (Tonry 2014) and are often used simultaneously to aggravate perceptions of blame for past crime and to increase assessed risk of future crime.”
Gender, risk assessment, and sanctioning: The cost of treating women like men. (2016, background): “, & and Tonry, M. (1997). Gender, race, and sentencing.”
RISK, RACE, AND RECIDIVISM: PREDICTIVE BIAS AND DISPARATE IMPACT*: RISK, RACE, AND RECIDIVISM (2016, background): “…articulate how to distinguish risk factors that reflect life choices from those that mark hapless socioeconomic circumstance (a fraught task; see Tonry, 2014), her suggestion mirrored Holder’s (2014) view that the most objectionable risk factors for the purposes of sentencing are “static” and…”