Casey Fiesler

Associate Professor, Department of Information Science (and Computer Science, by courtesy), University of Colorado Boulder

Data Is People: Ethics and Education for Data Science

November 11, 2020 - 12:00 PM Eastern Time

Talk Abstract:

Big data has opened up new possibilities and transformed the ways we conduct research in nearly every discipline. However, ethical considerations and education for research has long focused on human subjects, governed in the U.S. by institutional review boards. Data science often falls through the cracks of these regulations, so it is even more imperative that we have strong ethical norms and guidelines. This starts with the reminder that though data scientists may not interact directly with people, the data collected and analyzed very often comes from people, which opens up important considerations around privacy, consent, and harm. Moreover, applications of data science research, particularly with respect to prediction, have the potential for large-scale societal impacts. In considering the broad landscape of technology ethics when it comes to uses and applications of big data, I will argue for a fundamental shift in how we teach ethics to future data scientists and researchers.

Speaker Bio:

Casey Fiesler is an Associate Professor of Information Science (and Computer Science by courtesy) at University of Colorado Boulder. She researches and teaches in the areas of technology ethics, internet law and policy, and online communities. Her work on research ethics for data science, ethics education in computing, and broadening participation in computing has been supported by the National Science Foundation, and she is the recipient of an NSF CAREER Award. Also a public scholar, she is a frequent commentator and speaker on topics of technology ethics and policy, and her research has been covered everywhere from The New York Times to Teen Vogue (though she’s particularly proud of her TikToks). She holds a PhD in Human-Centered Computing and a a JD from Vanderbilt Law School.