发表机构
University College London（伦敦大学学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文通过提出非对称通信框架，纠正了AI讨论对大语言模型的错误属性投射，将相关现象重新归类为接收方一侧的现象，为AI治理提供了启示，明确对齐是制度约束工程，责任归人类机构。
AI 中文摘要
当代AI讨论赋予语言模型诸多其无法具备的属性：将通用智能视为与载体无关的认知，把幻觉当作认知失败，视智能体为自主目标追求，认为感知是涌现的内在生命，将对齐视为目标同步。本文认为这些均属于单一范畴错误——将人类交际实践中形成的属性投射到了机器一侧，并解释了其结构。人类与LLM的互动构成了一种语言游戏，其中一方承担全部规范性活动。我们将这种配置称为非对称通信，因为模型输出在交际中循环，进入后续交流，而系统不承担承诺、享有权利或进行论辩立场所依赖的评估。三个条件定义了这种非对称性：（i）正确性完全由接收方强制；（ii）问责仅由人类参与者承担；（iii）任何输出的实践地位完全取决于人类的接纳。这些条件是结构性的，与能力无关，且随着更强大的模型提升了错误归因的风险，它们仍保持不变。该框架借鉴了维特根斯坦（意义在共享实践中实现）、卢曼（通信在接收方一侧完成）、埃斯波西托（算法偶然性足以支撑接纳）和布兰顿（规范性记分是论辩立场的来源）的理论。将其应用于上述五个方面，它将每个现象重新归类为接收方一侧的现象，将护栏确立为结构性必要条件而非机器道德智能体的表现，并对AI治理产生启示：对齐是制度约束工程，而非智能体之间的目标同步，责任仍由人类机构承担。
英文摘要
Contemporary AI discourse attributes to language models properties they cannot bear: general intelligence as substrate-independent cognition, hallucination as cognitive failure, agency as autonomous goal-pursuit, sentience as emergent inner life, alignment as goal synchronization. This paper argues that these are instances of a single category mistake--properties constituted within human communicative practice are projected onto the machine side--and explains its structure. Human-LLM interaction constitutes a language game in which one side bears all normative activity. We call this configuration asymmetric communication since model outputs circulate communicatively, entering further exchanges, without the system undertaking commitments, bearing entitlements, or performing the assessment on which discursive standing depends. Three conditions define the asymmetry: (i) correctness is enforced exclusively by the receiver; (ii) accountability is borne by human participants alone; and (iii) the practical standing of any output depends entirely on human uptake. These conditions are structural, hold independently of capability, and remain unchanged as more powerful models raise the stakes of misattribution. The framework draws on Wittgenstein (meaning enacted in shared practices), Luhmann (communication completed on the receiver's side), Esposito (algorithmic contingency sufficient for uptake), and Brandom (normative scorekeeping as the source of discursive standing). Applied to all five, it reclassifies each as a receiver-side phenomenon, grounds guardrails as structural necessities rather than manifestations of machine moral agency, and yields an implication for AI governance. Alignment is institutional constraint engineering, not goal synchronization between agents, while responsibility remains with human institutions.
