A Rejoinder to Dressel and Farid: New Study Finds Computer Algorithm Is More Accurate Than Humans at Predicting Arrest and as Good as a Group of 20 Lay Experts 1

[...]specifying relevant risk factors and providing feedback on the degree to which they predict recidivism "loaded the deck" for laypeople to predict more accurately than experts would in the much more complicated context of a real criminal case-with relevant and irrelevant information pr...

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Veröffentlicht in:	Federal Probation 2018-09, Vol.82 (2), p.50-56
Hauptverfasser:	Holsinger, Alexander M, Lowenkamp, Christopher T, Latessa, Edward J, Serin, Ralph, Cohen, Thomas H, Robinson, Charles R, Flores, Anthony W, VanBenschoten, Scott W
Format:	Artikel
Sprache:	eng
Schlagworte:	Arrests Case management Correctional personnel Correctional treatment programs Criminal sentences Decision making Parole & probation Pretrial detention Public safety Recidivism Risk assessment Risk factors Validity
Online-Zugang:	Volltext
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