Intrinsic Guardrails: How Semantic Geometry of Personality Interacts with Emergent Misalignment in LLMs

Fine-tuning Large Language Models (LLMs) on benign narrow data can sometimes induce broad harmful behaviors, a vulnerability termed emergent misalignment (EM). While prior work links these failures to specific directions in the activation space, their relationship to the model's broader persona remains unexplored. We map the latent personality space of LLMs through established psychometric profiles like the Big Five, Dark Triad, and LLM-specific behaviors (e.g. evil, sycophancy), and show that t

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ethics.ai (11 May 2026), “Intrinsic Guardrails: How Semantic Geometry of Personality Interacts with Emergent Misalignment in LLMs,” evidence record 4550, https://ethics.ai/record/4550 (originally published by arXiv).

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