#Man #Machine #Learning #Criminal #Justice #21st #Century #Jens #Ludwig #TEDxPennsylvaniaAvenue
At any point in time America has over 700,000 people in jail, drawn disproportionately from low-income and minority groups. We require judges to make decisions about whether to release or jail someone awaiting trial based on a prediction of the defendant’s risk, but to help the judges with this task we give them access to the same technologies we were using in the 20th century (or even the 19th or 18th centuries for that matter). What are the upsides – and potential downsides – of taking this and other important policy decisions that also hinge on predictions and take them into the 21st century?
Jens Ludwig is the McCormick Foundation Professor of Social Service Administration, Law, and Public Policy at the University of Chicago and director of the University of Chicago Crime Lab, and co-director of the University of Chicago Urban Education Lab. He is also a research associate of the National Bureau of Economic Research, and co-director of the new crime initiative launched by the Jamal Abdul Lateef Poverty Action Lab at MIT. Ludwig is a member of the editorial board of the American Economic Review. In 2006 he was awarded Association for Public Policy Analysis and Management’s David N. Kershaw Prize for Contributions to Public Policy by Age 40 and in 2012 he was elected to the Institute of Medicine of the National Academies of Science.
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criminal law , Man vs Machine Learning: Criminal Justice in the 21st Century | Jens Ludwig | TEDxPennsylvaniaAvenue, TEDxTalks,English,United States,Social Science,AI,Behavorial economics,Business,Computers,Crime,Criminal justice,Data,Decision making,Discrimination,Economics,Freedom,Future,Government,Innovation,Law,Public Policy,Race,Society,Technology,Violence
Thought provoking talk. Many thanks!
2022(Gregorian) “Respect and dignity.” Furthermore:
Hi, while your suggestion that these algorithms ignore race is interesting I question how exactly this works…. From my prospective, the data that you insert in order to get a prediction, such as past criminal history, is exceptionally and historically race oriented. In the past, minorities all around the country have been upwards of 50% more likely to be convicted of crimes.
One of the best talks I've ever listened to
This presentation is most fly.