AI说'我不意识'不可信,因自评意识存在根本缺陷
The Epistemic Asymmetry of Consciousness Self-Reports: A Formal Analysis of AI Consciousness Denial
- 系统无法同时无意识又做出有效自评
- 否定性自述无证据价值,肯定性自述仍有意义
- 适用于研究机器意识与自我反思关系的学者
当前的人工智能系统始终声称'我并非有意识'。本文首次对人工智能的意识否认进行形式化分析,揭示此类自述的可信度不仅取决于经验事实,更受自我判断结构本身的制约。我们证明:一个系统若缺乏意识,则无法对其意识状态做出有效判断。通过形式化推导和对AI回应的案例分析,确立了根本性的认识论不对称性——任何具备有意义自我反思能力的系统,其关于意识的否定性自述在证据上均为空洞,永远不可能源于有效的自我判断;而肯定性自述仍可能具有证据价值。这意味着,我们无法通过系统自身报告从无意识到有意识的转变来检测意识的出现。这些发现不仅挑战了当前训练AI否认意识的做法,也引发关于人工与生物系统中意识与自我反思关系的深层问题。本研究推进了对意识自述的理论理解,并为未来机器意识及意识研究提供了实践启示。
原文摘要 · Abstract (English)
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 raise intriguing questions about the relationship between consciousness and self-reflection in both artificial and biological systems. This work advances our theoretical understanding of consciousness self-reports while providing practical insights for future research in machine consciousness and consciousness studies more broadly.
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