Ricardo Baeza-Yates – Northeastern University
Title: Ethics Challenges in AI
Abstract: In the first part we cover five current AI issues through examples: (1) discrimination (e.g., search, facial recognition, justice, sharing economy, etc.); (2) physiognomy (e.g., personality predictions based in facial biometrics); (3) unfair feedback loops (e.g., exposure and popularity biases); (4) stupidity (e.g., lack of semantic and context understanding) and (5) indiscriminate use of computing resources (e.g., large language models). These examples do have a personal bias but set the context for the second part where we address four generic challenges: (1) too many principles (e.g., principles vs. techniques), (2) cultural differences (e.g., Christian vs. Muslim vs. Ubuntu); (3) regulation (e.g., privacy, antitrust) and (4) our cognitive biases. We finish discussing what we can do to address these challenges in the near future.
Bio: Ricardo Baeza-Yates is Director of Research at the Institute for Experiential AI of Northeastern University. He is also part-time professor at Universitat Pompeu Fabra in Barcelona and Universidad de Chile in Santiago. Before, he was VP of Research at Yahoo Labs, based in Barcelona, Spain, and later in Sunnyvale, California, from 2006 to 2016. He is co-author of the best-seller Modern Information Retrieval textbook published by Addison-Wesley in 1999 and 2011 (2nd ed), which won the ASIST 2012 Book of the Year award. From 2002 to 2004 he was elected to the Board of Governors of the IEEE Computer Society and between 2012 and 2016 was elected for the ACM Council. Since 2010 he has been a founding member of the Chilean Academy of Engineering. In 2009 he was named ACM Fellow and in 2011 IEEE Fellow, among other awards and distinctions. He obtained a Ph.D. in CS from the University of Waterloo, Canada, in 1989, and his areas of expertise are web search and data mining, information retrieval, bias on AI, data science and algorithms in general.
Event Timeslots (1)
Thu (Feb. 24)
Ricardo Baeza-Yates: "Ethics Challenges in AI". Session chair: Jiliang Tang