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It is concluded that only by grounding oversight in realistic assumptions about human cognition and institutional incentives can it fulfill its intended role in ensuring trustworthy AI.
Large language models (LLMs) are increasingly deployed for translation tasks, yet their implicit political positioning in such contexts remains understudied. We ask whether a single politically charged framing term, such as aggressor, enemy, neighbour, or coloniser is sufficient to trigger implicit political alignment...
This work examines how LLMs respond to user prompts expressing varying degrees of Dark Triad traits (Machiavellianism, Narcissism, and Psychopathy) using a curated dataset, revealing systematic differences across models.
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