Recent advances in large language models (LLMs) have prompted claims that such systems exhibit agency or qualify as moral agents. This paper argues that these attributions are misguided. We maintain that moral responsibility requires commitment-bearing agency grounded in intrinsic intentionality and self-attributed action, and that such agency constitutes the form of free will relevant to responsibility. Although LLMs generate coherent and normatively evaluable outputs, their operation is fully characterized by probabilistic input-output mappings learned from data. Their apparent intentionality is derived rather than intrinsic, and their outputs are neither owned as commitments nor guided by reasons. Variability introduced by stochastic sampling does not amount to choice or authorship. We address objections from the intentional stance, functionalism, compatibilism, and the presence of moral reasoning in model outputs, arguing that none suffice to establish genuine agency.

翻译：近期大型语言模型（LLMs）的进展引发了关于此类系统是否表现出能动性或具备道德主体资格的讨论。本文认为，这些归因是错误的。我们坚持，道德责任要求以内在意向性和自我归因行动为基础的承诺性能动性，而这种能动性构成了与责任相关的自由意志形式。尽管LLMs能生成连贯且可进行规范性评估的输出，但其运作完全由从数据中习得的概率性输入-输出映射所刻画。其表面上的意向性是衍生的而非内在的，其输出既非作为承诺被持有，也非由理由所引导。随机采样引入的变异性并不等同于选择或作者身份。我们回应了来自意向性立场、功能主义、相容论以及模型输出中存在道德推理等层面的反对意见，论证其中没有任何一点足以确立真正的能动性。