Jacob Steinhardt
Jacob Steinhardt is an Associate Professor of Statistics and EECS at UC Berkeley and the Co-founder & CEO of Transluce, an independent nonprofit research lab based in San Francisco. His research focuses on ensuring ML systems are understood by and aligned with humans, spanning robustness, reward specification, scalable alignment, and AI evaluation. He is a 2023 AI2050 Early Career Fellow (Schmidt Sciences) and has received multiple grants from Open Philanthropy to support his lab's work on AI safety and alignment. He is also the author of the Bounded Regret blog on AI, science, and forecasting.
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Theory of Change
Steinhardt's theory of change holds that advanced AI systems will inevitably be complex and opaque, making external, independent oversight essential to ensuring they behave as intended. By building open-source, scalable tools for auditing and evaluating AI systems, he aims to create a public infrastructure for AI accountability that can be used by governments, safety organizations, and researchers independent of the AI labs themselves. His technical research on alignment, robustness, and reward specification addresses the root causes of unintended AI behavior, while Transluce's evaluation platforms provide practical mechanisms for detecting failures before deployment. The combination of foundational research and applied tooling is intended to shift industry norms toward responsible deployment and give non-lab actors the capability to hold AI developers accountable.
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from Open Philanthropy
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Details
- Last Updated
- Apr 2, 2026, 9:57 PM UTC
- Created
- Mar 20, 2026, 2:34 AM UTC