Tom Mitchell

Tom M. Mitchell is the Founders University Professor at Carnegie Mellon University, where he founded the world's first Machine Learning Department, and authored the widely used textbook "Machine Learning." Mitchell's research over the years has focused on machine learning, artificial intelligence, cognitive neuroscience, and the impact of AI on society.

Mitchell and colleagues in CMU's Psychology Department used machine learning to create the first computational model to predict fMRI brain activation patterns associated with reading arbitrary nouns, work that has since been extended to sentence and story reading. His novel research on never-ending machine learning produced a computer program that has run continuously for over eight years, teaching itself to read the web.

More recently, Mitchell has explored how machine learning and information technology will affect jobs. He co-chaired a study by the National Academies of Sciences, Engineering and Medicine that produced a 2017 report on this topic, and since then has published papers with colleagues suggesting that machine learning technology is more likely to lead to job redefinition than to job replacement. Mitchell has testified to a variety of U.S. Congressional committees regarding potential uses and impacts of artificial intelligence.

Mitchell currently co-directs the CMU--Squirrel AI Lab on Personalized Education at Scale, which is pursuing the use of artificial intelligence to transform personalized education over the coming years.

A former president of the Association for the Advancement of Artificial Intelligence (AAAI), Mitchell is a fellow of both the AAAI and the American Association for the Advancement of Science, and winner of the 2007 AAAI Distinguished Service Award. He was elected in 2010 to the U.S. National Academy of Engineering, and in 2016 to the American Academy of Arts and Sciences. His AI research has been featured in media ranging from the New York Times, to CBS's 60 Minutes, to PBS's "NOVA Science NOW," to Chinese national television.