Criminal Justice Forecasts of Risk

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How researchers see this paper

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Fairness in Criminal Justice Risk Assessments: The State of the Art (2017, neutral): “…been ongoing discussions about how much better in practice risk assessments derived from machine learning perform compared to risk assessments derived from older, conventional methods (Berk 2012; Berk and Bleich 2013; Brennan and Oliver 2013; Liu et al. 2011; Rhodes 2013; Ridgeway 2013a, 2013b).”
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).”
Forecasts of Violence to Inform Sentencing Decisions (2013, methodology): “5 This weighting is broadly consistent with work we have done in the past (Berk 2012).”
Forecasting Domestic Violence: A Machine Learning Approach to Help Inform Arraignment Decisions (2016, background): “There are examples of successful forecasting in other criminal justice settings and for other kinds of crimes (Berk 2012).”
An Experimental Evaluation of the Impact of Intensive Supervision on the Recidivism of High-Risk Probationers (2017, methodology): “These models can be difficult to construct and rely on a vast amount of historical data (Berk, 2012).”