Tom Mitchell's Home Page

How can AI improve education? My thesis: this is the decade when AI will truly revolutionize online education. Why? Because (1) for the first time we have finally have online education sites that have taught millions of students, providing more training data showing how students learn, than a human teacher could ever see in a 100-year teaching career, and (2) recent AI advances in machine learning, large natural language models, and reasoning give us the right tools to build AI agents that tutor online students. ...

Here are two problems I've been working on with my collaborators:

Tracing the knowledge state of students as they work through the online curriculum.
- Assessing the Knowledge State of Online Students -- New Data, New Approaches, Improved Accuracy, Robin Schmucker, Jingbo Wang, Shijia Hu, and Tom M. Mitchell, arXiv:2109.01753, September, 2021. To appear in Journal of Educational Data Mining.
- Transferable Student Performance Modeling for Intelligent Tutoring Systems, Robin Schmucker, Tom M. Mitchell. arXiv preprint arXiv:2202.03980, February 2022.
Learning which teaching actions work best for which students.
- watch this space for upcoming publications...

How does the brain represent language meaning? We collect images of brain activity while human subjects read text, then use machine learning to analyze how observed brain activity represents language meaning. ...

Relating Simple Sentence Representations in Deep Neural Networks and the Brain, S. Jat, P. Talukdar, and T. Mitchell, Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019), pp. 5137--5154, 2019.
The Lexical Semantics of Adjective-Noun Phrases in the Human Brain, A. Fyshe, G. Sudre, L. Wehbe, N. Rafidi, and T. Mitchell, Human Brain Mapping, DOI: 10.1002/hbm.24714, pp. 4457--4469, 2019.
"Predicting Human Brain Activity Associated with the Meanings of Nouns," T. M. Mitchell, S. V. Shinkareva, A. Carlson, K.M. Chang, V. L. Malave, R. A. Mason, and M. A. Just, Science, 320, 1191, May 30, 2008. DOI: 10.1126/science.1152876. Supporting Online Material. Supporting website.

How will AI change the future of work? I co-chaired a U.S. National Academy study on this question with Erik Brynjolfsson in 2017. We are now co-chairing a new Congressionally-mandated follow on study, due out in 2023. ...

2017 U.S. National Academy report on Information Technology and the Future of Work. Study co-Chairs Erik Brynjolfsson, Tom Mitchell.
What Can Machine Learning Do? Workforce Implications, Erik Brynjolfsson and Tom M. Mitchell, Science, December 22, 2017 358:6370.
Track how Technology is Transforming Work, Tom M. Mitchell and Erik Brynjolfsson, Nature, April 20, 2017 544:290-292.

Tom Mitchell

Current Research

Textbook: Machine Learning

Publications

Colleagues