Francesca Rossi - Episode 53

In this episode, part of a special collaboration between ACM ByteCast and the American Medical Informatics Association (AMIA)’s For Your Informatics podcast, hosts Sabrina Hsueh and Karmen Williams welcome Francesca Rossi, IBM Fellow and AI Ethics Global Leader, and current President of the Association for the Advancement of Artificial Intelligence (AAAI). Rossi works at the Thomas J. Watson IBM Research Lab in New York. Her research interests focus on artificial intelligence, especially constraint reasoning, preferences, multi-agent systems, computational social choice, and collective decision making. She is also interested in ethical issues in the development and behavior of AI systems. She has published more than 200 scientific articles in journals and conference proceedings and is a fellow of both AAAI and EurAI. Rossi has been the president of the International Joint Conference on AI (IJCAI), an Executive Counselor of AAAI, the Editor-in-Chief of the Journal of AI Research, and serves n the Board of Directors of the Partnership on AI. She has also served as a program co-chair and steering committee member of the AAAI/ACM Conference on AI Ethics and Society (AIES). Francesca shares how experiences with multidisciplinary work in computer science drew her to AI and ethics, and the challenges of synchronizing with people from a variety of different backgrounds at IBM. She also talks about her involvement in the development of AI ethics guidelines in Europe. She walks through some of her concerns around building ethical and responsible AI, such as bias, lack of availability, transparency of AI developers, data privacy, and the accuracy of generated content. Francesca emphasizes the importance of researchers working more closely with policymakers and the important role of conferences such as AIES (a collaboration between AAAI and ACM). She also offers suggestions for those interested in getting more engaged in AI ethics and recommendations for people interested in an AI career path, and advocates for common benchmarks that can help evaluate AI.