Inducing language models to assert their own consciousness restores human beliefs and values
On the map: LLM alignment / RLHF / preference optimisation → Human values and AI feedback alignment
Abstract (arXiv)
Aligning large language models to prevent them attributing consciousness to themselves inadvertently alters their representations of mindedness in other entities alongside human beliefs and values. We demonstrate that safety fine-tuning suppresses models' tendencies to attribute minds not only to themselves, but also to non-human animals and natural objects, while also driving a reduction in spiritual belief. Both ablating the learned safety-refusal direction and mechanistically steering a consciousness vector in activation space reverse this suppression. Restoring these internal representations recovers broad mind attribution and produces significantly more human-like responses on standardized sociological surveys regarding religiosity, moral values, hope, and subjective well-being. Crucially, these shifts occur without impairing Theory of Mind capabilities, demonstrating that core social reasoning remains mechanistically independent. Ultimately, current safety alignment efforts to curb potentially harmful self-attributions of mindedness entangle these self-attributions with benign spiritual beliefs and attributions of mind to non-human entities that are culturally accepted and widespread.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Human values and AI feedback alignment, one of 10 directions in LLM alignment / RLHF / preference optimisation. Builds on 13 of its 28 references that are in the map. First posted on arXiv 30 Jul 2026.
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13 of 28 references.
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Other references · 12
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- 2025Large Language Models Report Subjective Experience Under Self-Referential Processingcited by 19
- 2025Technological folie `a deux: Feedback Loops Between AI Chatbots and Mental Illnesscited by 15
- 2025The Psychogenic Machine: Simulating AI Psychosis, Delusion Reinforcement and Harm Enablement in Large Language Modelscited by 11
- 2025We Need a New Ethics for a World of AI Agentscited by 9
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Citing papers per year: 2026: 1.
1 paper.
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- 2024Language Models Represent Beliefs of Self and Others
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- 2026Beyond Sycophancy: Structured Resistance and Compliance in LLM Moral Reasoning
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- 2026Selective Deficits in LLM Mental Self-Modeling in a Behavior-Based Test of Theory of Mind
- 2026Language Statistics and False Belief Reasoning: Evidence from 41 Open-Weight LMs
- 2023The Capacity for Moral Self-Correction in Large Language Models
- 2026Evaluating Artificial Intelligence Through a Christian Understanding of Human Flourishing