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The Alignment Research Center (ARC) is a nonprofit research organization whose mission is to align future machine learning systems with human interests. Founded in April 2021 by Paul Christiano, a former OpenAI researcher and one of the principal architects of Reinforcement Learning from Human Feedback (RLHF), ARC is headquartered in Berkeley, California, where it operates out of the Constellation co-working space alongside other AI safety organizations.

ARC focuses on theoretical research addressing the problem of scalable alignment: how to ensure AI systems remain intent-aligned even as they become more capable. The organization employs a builder-breaker methodology, making worst-case assumptions rather than extrapolating from current systems. Their approach allows rapid theoretical evaluation of alignment strategies without requiring full implementation…

ARC believes that as ML systems become more capable, current alignment approaches may fail to scale, potentially leading to systems that pursue goals misaligned with human interests. Their theory of change centers on developing rigorous theoretical foundations for alignment before superintelligent systems arrive. By creating formal mechanistic explanations of neural network behavior, combining ideas from mechanistic interpretability and formal verification into heuristic arguments, ARC aims to enable reliable detection of when AI systems might behave in dangerous or deceptive ways. This theoretical groundwork is intended to inform practical alignment techniques that can be applied by AI labs building frontier models, ensuring that powerful AI systems remain genuinely helpful and honest rather than merely appearing aligned.