This event is hosted by the Canadian Statistical Sciences Institute (CANSSI). For full details, please visit their events page.
Speaker
Dr.
Kristian
Lum
Assistant
Research
Professor
Department
of
Computer
and
Information
Science
School
of
Engineering
and
Applied
Science
University
of
Pennsylvania
Talk Title: Fairness, Accountability, and Transparency: (Counter)-Examples from Predictive Models in Criminal Justice
Abstract: The need for fairness, accountability, and transparency in computer models that make or inform decisions about people has become increasingly clear over the last several years. One application area where these topics are particularly important is criminal justice, as statistical models are being used to make or inform decisions that impact highly consequential decisions— those concerning an individual’s freedom. In this talk, I’ll highlight three threads of my own research into the use of machine learning and a statistical models in criminal justice models that demonstrate the importance of careful attention to fairness, accountability, and transparency. In particular, I’ll discuss how predictive policing has the potential to reinforce and amplify unfair policing practices of the past. I’ll also discuss some of the ways in which recidivism prediction models can fail to require the accountability and transparency necessary to prevent gaming.