一篇新学术论文认为，当前的大型语言模型（LLMs）不具备真正的能动性或道德责任。作者认为，LLMs基于概率数据映射运作，缺乏内在的意向性，也无法将其输出视为承诺。虽然LLMs可以生成连贯且可进行规范评估的文本，但其表观意向性是派生的，随机采样不等于选择或作者身份，因此不能将其视为道德主体。 AI
影响 挑战了人工智能能动性的概念，可能影响伦理框架和公众对LLM能力的认知。
排序理由 该集群包含一篇讨论LLM能力和哲学含义的学术论文。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
arXiv:2606.13441v1 Announce Type: new Abstract: 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 require…
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 intrinsi…