Responsible Data Science
Data science is an emerging discipline that offers both promise and peril. Responsible data science refers to efforts that address both the technical and societal issues in emerging data-driven technologies. Prof. Getoor is a computer scientist who is well known for her theoretical work that integrates logic and probability to reason collectively and holistically about context in structured domains. In this lecture, she will describe some of the opportunities and challenges in developing the foundations for responsible data science. How can machine learning and AI systems reason effectively about complex dependencies and uncertainty? Furthermore, how do we understand the ethical and societal issues involved in data-driven decision-making? There is a pressing need to integrate algorithmic and statistical principles, social science theories, and basic humanist concepts so that we can think critically and constructively about the socio-technical systems we are building. In this talk, she will lay the groundwork for this important agenda.
Lise Getoor is a professor in the Computer Science Department at UC Santa Cruz and director of the Data, Discovery and Decisions (D 3 ) Data Science Research Center at the University of California, Santa Cruz. Her research areas include machine learning, data integration and reasoning under uncertainty, with an emphasis on graph and network data. She has over 200 publications, including 12 best paper awards, and over 18,000 citations. She is a Fellow of the Association for Artificial Intelligence, has served as an elected board member of the International Machine Learning Society, and the Computing Research Association (CRA). This past fall she was a visiting researcher in the Fairness, Accountability, Transparency and Ethics research group at Microsoft Research, NYC. She received her PhD from Stanford University in 2001, her MS from UC Berkeley, and her BS from UC Santa Barbara, and was a professor at the University of Maryland, College Park from 2001-2013.