The Hot Mess of AI: How Does Misalignment Scale with Model Intelligence and Task Complexity?
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Research from Anthropic's Fellows Program examines whether AI failures stem from systematic misalignment (pursuing wrong goals coherently) or incoherence (unpredictable, inconsistent behavior). Using bias-variance decomposition across frontier models, the study finds that as tasks become harder and reasoning chains lengthen,
Table of contents
IntroductionMeasuring Incoherence: A Bias-Variance DecompositionKey FindingsWhy Should We Expect Incoherence? LLMs as Dynamical SystemsImplications for AI SafetyConclusionAcknowledgementsSort: