John Wentworth

San Francisco, California

Bio

John Wentworth is an independent AI alignment researcher best known for developing the Natural Abstraction Hypothesis, which proposes that a wide variety of cognitive systems tend to converge on similar high-level abstractions due to the low-dimensional structure of physical information at large distances. He holds a BS in Computational and Applied Mathematics from Harvey Mudd College and has been working as an independent researcher since approximately 2018, previously having worked as a software engineer and data scientist. His research agenda centers on formalizing abstraction and agency, with work spanning questions such as what makes certain concepts like 'trees' or 'cars' natural objects of thought, why biological organisms are modular, and how such modularity may carry over to machine learning systems. He publishes extensively on LessWrong and the Alignment Forum, where he has accumulated over 400 posts and more than 60,000 karma, and he has authored eight sequences. He attended the MIRI Summer Fellows Program in 2019 and has served as a mentor in the SERI MATS (ML Alignment Theory Scholars) program, working with scholars on natural abstraction and related research directions. He has received substantial research funding from the Long-Term Future Fund and the Survival and Flourishing Fund totaling over $700,000 to support his independent alignment work.