Thomas G. Dietterich - Machine Learning for Ecological Science & Ecosystem Management

Thomas G. Dietterich is Emeritus Professor of computer science at Oregon State University. He is one of the founders of the field of machine learning. He served as Executive Editor of Machine Learning (journal) (1992–98) and helped co-found the Journal of Machine Learning Research.

Among his research contributions were the invention of
error-correcting output coding to multi-class classification, the
formalization of the multiple-instance problem, the MAXQ framework for hierarchical reinforcement learning, and the development of methods for integrating non-parametric regression trees into probabilistic graphical models.

In response to the media's attention on the dangers of artificial intelligence, Dietterich has been quoted for an academic perspective to a broad range of media outlets including National Public Radio, Business Insider, Microsoft Research, CNET, and The Wall Street Journal.

https://en.wikipedia.org/wiki/Thomas_G._Dietterich

Oregon State University profile: http://web.engr.oregonstate.edu/~tgd/

Audio of full interview (including other parts on AI): https://archive.org/details/ThomasG.DietterichOnAGIAIAssistedScienceAndClimateChange

Interviewed by Yiqing Liang & Adam Ford

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- Science, Technology & the Future

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