On Ethics and Machine Learning

Irina Raicu is the director of the Internet Ethics program at the Markkula Center for Applied Ethics at Santa Clara University. Over in Santa Clara University's Leavey School of Business, professor Sanjiv Das teaches machine learning to graduate students enrolled in the MS of Information Systems program. As the Spring 2017 quarter was about to start, Subramaniam (Subbu) Vincent (the Tech Lead for the center's Trust Project, and an engineer-journalist with experience in data science) suggested that the two of them might collaborate in an effort to introduce the students to some key questions in data analytics: what do fairness and bias look like in the context of machine learning? And, if bias is detected in a dataset or an algorithm, are there ways to minimize or correct for it? In his hands-on, skill-building course, professor Das asked the students to work in small groups as they practiced predictive modeling on data sets--and proposed the fairness questions as one project option. Five of the groups took him up on the offer.