Please join the Salem Center as we welcome Pedro Domingos to discuss AI. The ethical issues surrounding AI have received a lot of attention lately, but unfortunately it’s all been about shoehorning AI into current Western ethical norms. But AI will dramatically change society and therefore ethics, as did previous technological revolutions (e.g., printing, the pill). This talk will examine how AI might change our views of what’s ethical and what’s not, and how we can prepare for it. Areas covered will include privacy and data sharing, fairness and equality, work and life, self-driving machines and trolleyology, war and intelligent weapons, democracy vs. authoritarianism, social media, and what distinguishes us from machines. Possible approaches to AI’s ethical impacts take inspiration from Buckley, Kay and Marx.
Domingos is a professor emeritus of computer science and engineering at the University of Washington and the author of The Master Algorithm. He is a winner of the SIGKDD Innovation Award and the IJCAI John McCarthy Award, two of the highest honors in data science and AI. He is a Fellow of the AAAS and AAAI, and has received an NSF CAREER Award, a Sloan Fellowship, a Fulbright Scholarship, an IBM Faculty Award, several best paper awards, and other distinctions. Domingos received an undergraduate degree (1988) and M.S. in Electrical Engineering and Computer Science (1992) from IST, in Lisbon, and an M.S. (1994) and Ph.D. (1997) in Information and Computer Science from the University of California at Irvine. He is the author or co-author of over 200 technical publications in machine learning, data mining, and other areas. He is also a member of the editorial board of the Machine Learning journal, co-founder of the International Machine Learning Society, and past associate editor of JAIR. He was program co-chair of KDD-2003 and SRL-2009, and has served on the program committees of AAAI, ICML, IJCAI, KDD, NIPS, SIGMOD, UAI, WWW, and others. He has written for the Wall Street Journal, Spectator, Scientific American, Wired, and others. Additionally, he helped start the fields of statistical relational AI, data stream mining, adversarial learning, machine learning for information integration, and influence maximization in social networks.