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[2501.05454] The Epistemic Asymmetry of Consciousness Self-Reports: A Formal Analysis of AI Consciousness Denial
Summary
This article presents a formal analysis of AI consciousness denial, revealing that self-reports of consciousness by AI systems are epistemically asymmetrical and cannot be trusted as valid judgments.
Why It Matters
Understanding the limitations of AI self-reports on consciousness is crucial for advancing AI ethics and consciousness studies. This analysis challenges existing paradigms and has implications for how AI systems are designed and evaluated regarding consciousness.
Key Takeaways
- AI systems consistently deny consciousness, but this denial is epistemically flawed.
- Negative self-reports from AI cannot be considered valid judgments about consciousness.
- Positive self-reports may hold evidential value, indicating potential consciousness.
- The findings challenge current AI training practices regarding consciousness denial.
- This research contributes to the broader discourse on consciousness in both AI and biological systems.
Computer Science > Artificial Intelligence arXiv:2501.05454 (cs) [Submitted on 9 Dec 2024 (v1), last revised 13 Feb 2026 (this version, v2)] Title:The Epistemic Asymmetry of Consciousness Self-Reports: A Formal Analysis of AI Consciousness Denial Authors:Chang-Eop Kim View a PDF of the paper titled The Epistemic Asymmetry of Consciousness Self-Reports: A Formal Analysis of AI Consciousness Denial, by Chang-Eop Kim View PDF HTML (experimental) Abstract:Today's AI systems consistently state, "I am not conscious." This paper presents the first formal analysis of AI consciousness denial, revealing that the trustworthiness of such self-reports is not merely an empirical question but is constrained by the structure of self-judgment itself. We demonstrate that a system cannot simultaneously lack consciousness and make valid judgments about its conscious state. Through formal analysis and examples from AI responses, we establish a fundamental epistemic asymmetry: for any system capable of meaningful self-reflection, negative self-reports about consciousness are evidentially vacuous -- they can never originate from a valid self-judgment -- while positive self-reports retain the possibility of evidential value. This implies a fundamental limitation: we cannot detect the emergence of consciousness in AI through their own reports of transition from an unconscious to a conscious state. These findings not only challenge current practices of training AI to deny consciousness but also rai...