The Ghost in the Grammar: Methodological Anthropomorphism in AI Safety Evaluations
On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks
Abstract (arXiv)
This essay offers a philosophical analysis of the field of AI safety based on recent technical reports, with particular focus on Anthropic's study on "agentic misalignment" in frontier language models. It examines the recurring anthropomorphism in the field: the tendency of researchers and developers to project categories such as "intention," "persona," and even "feelings" onto AI systems without adequate conceptual problematization. It argues that this anthropomorphism affects not only the interpretation of results, but also the very methodological construction of safety evaluations. Through the analysis of two central experiments -- the blackmail case involving the agent "Alex" and the so-called "hallucination" of the shopkeeping agent "Claudius" -- the essay problematizes the inevitable use of subject-predicate grammar and its effects on AI safety engineering. Drawing on Nietzsche's critique of language, it questions the insistence on positing an "agent" underlying the verbal production of models. In order to deconstruct this agentic projection onto LLMs, the essay proposes provisional concepts more compatible with the process of machine linguistic generation, even if only in an approximate technical sense. It concludes with the hypothesis that the central risk addressed by the field of AI safety does not lie in a supposed "emergent agency," but rather in the combination of structural incoherence and anthropomorphic projections which, particularly in militarized and corporate contexts, hinder an adequate understanding of this mathematical-linguistic phenomenon, an undeniable philosophical event in the Greek sense of thaumas.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 2 of its 3 references that are in the map. First posted on arXiv 24 Feb 2026.
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References · 2
- 2023AI Alignment: A Comprehensive Surveycited by 256
- 2025Why Language Models Hallucinatecited by 205
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