Machine learning (ML) is increasingly being used to support decision-making in critical settings, where predictions have potentially grave implications over human lives. In this talk, Maria De-Arteaga (Assistant Professor, Information, Risk and Operations Management) will discuss the gap that exists between ML predictions and ML-informed decisions. The first part of the talk will highlight the role of humans-in-the-loop through a study of the adoption of an algorithmic tool used to assist child maltreatment hotline screening decisions. The second part of the talk will focus on the gap between the observed outcome that the algorithm optimizes for and the construct of interest to experts. Learn more and register now.
Part of the Ethics in AI Seminar Series hosted by The Institute for Foundations of Machine Learning.
Event Details
Date and Time
April 12, 2021, All Day