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I’m a MATS 10.0/10.1 scholar supervised by Oliver Sourbut, where I'm working on a benchmark for multi-agent epistemic propensities. I'm also a Master's student in computer science at Brigham Young University; under the supervision of David Wingate, I study learning mechanics in LLMs. Previously, I did my Bachelor's in BYU's Applied and Computational Mathematics program.

I wrote the software the drives “The Wall,” the floor-to-ceiling interactive display in the lobby of BYU’s computer science building.
I'm interested in deeply understanding AI to prevent catastrophic risks. In particular, I've researched learning mechanics to help predict how AI (mis)generalizes, and, as part of MATS, I've benchmarked multi-agent epistemics to help determine if agents are responsible enough to be trusted with our knowledge commons. Previously, I worked on pro-social applications of AI, like creating a chatroom that used AI suggestions to help improve online political conversations.

Thomas V Howe, David Wingate
Preprint

Jeffrey Olmo, Jared Wilson, Max Forsey, Bryce Hepner, Thomas V Howe, David Wingate
Findings of the Association for Computational Linguistics

Lisa P Argyle, Christopher A Bail, Ethan C Busby, Joshua R Gubler, Thomas V Howe, Christopher Rytting, Taylor Sorensen, David
Wingate
Proceedings of the National Academy of Sciences