On June 3-4, 2021, the Institute hosted its inaugural Responsible Machine Learning Conference (RML2021), which welcomed approximately 320 practitioners, teachers, and students of data science.
Focused on bias, fairness, and transparency in machine learning, RML2021’s featured speakers included renowned scholars from Columbia, Duke, UNC-Chapel Hill, the University of Chile, and the University of Pennsylvania, as well as industry professionals. Video recordings of all talks are accessible via the conference website.
Institute alumni played key roles in the success of RML2021:
Emily Hadley ‘18, a research data scientist at RTI International, delivered the opening address, Bias, Equity, and Anti-racism in Data Science.
Kelsey Campbell ‘16, a data scientist at Accenture Federal Services and founder of Gayta Science, gave a talk on Data Cistems: Transphobia in Automated Systems and How to Be More Inclusive.
Elena Snavely ‘14, manager of corporate analytics and insights at SAS, moderated a panel where participants offered reviews of their favorite books on the topic of how data and analytics impact our world.
Jim Box ‘14, a principal data scientist in healthcare and life sciences at SAS, hosted a rousing trivia competition on responsible machine learning topics. Fellow alumni Marshall Bradley ‘20, Paul Ruddle ‘14, Shawna Strickler ‘18, and Thierry Zell ‘15 claimed trivia victories.
Institute faculty coordinated RML2021 in cooperation with RTI International and Women in Data Science (WiDS) Worldwide.
Cynthia Rudin generated a lot of questions with her talk about Optimal Sparse Decision Trees.
Congratulations to the lunchtime trivia winners, it was a fierce competition that ultimately left 4 alumni neck-in-neck at the top of the leaderboard:
- Paul Ruddle (MSA ‘14)
- Marshall Bradley (MSA ‘20)
- Shawna Strickler (MSA ‘18)
- Thierry Zell, PhD (MSA ‘15)
Thanks to SAS Engage Trivia for the competition software!