BUILDING DATA EQUITY SYSTEMS

Summary
Join RI-AI Meetup and Julia Stoyanovich, Director of the Center for Responsible AI at New York University as she discusses the technical work behind the “Data, Responsibly” project and presents a vision for designing, developing, deploying, and overseeing data-intensive systems that consider equity as an essential requirement.

Abstract
Equity as a social concept — treating people differently depending on their endowments and needs to provide equality of outcome rather than equality of treatment — lends a unifying vision for ongoing work to operationalize ethical considerations across technology, law, and society. In my talk I will present a vision for designing, developing, deploying, and overseeing data-intensive systems that consider equity as an essential requirement. I will discuss ongoing technical work in scope of the “Data, Responsibly” project, and will place this work into the broader context of policy, education, and public outreach activities.

Speaker Bio
Julia Stoyanovich is an Assistant Professor of Computer Science & Engineering, and of Data Science at New York University (NYU). She directs the Center for Responsible AI at NYU, a hub for interdisciplinary research, public education, and advocacy that aims to make responsible AI synonymous with AI. Julia’s research focuses on responsible data management and analysis: on operationalizing fairness, diversity, transparency, and data protection in all stages of the data science lifecycle. She established the Data, Responsibly consortium and served on the New York City Automated Decision Systems Task Force, by appointment from Mayor de Blasio. Julia developed and has been teaching courses on responsible data science at NYU, and is a co-creator of an award-winning comic book series on this topic. In addition to data ethics, Julia works on the management and analysis of preference data, and on querying large evolving graphs. She holds M.S. and Ph.D. degrees in Computer Science from Columbia University, and a B.S. in Computer Science and in Mathematics & Statistics from the University of Massachusetts at Amherst. Julia is a recipient of an NSF CAREER award.