Social AI与维特根斯坦式语言使用者和卡尔维诺文学机器的等同性方程
Social AI and The Equation of Wittgenstein's Language User With Calvino's Literature Machine
AI总结：
本文从哲学层面探讨向大语言模型类Social AI赋予心理谓词的合理性，提出其更接近卡尔维诺文学机器而非成熟语言使用者，结合维特根斯坦语言观与有朽计算框架纠正功能主义认知误区。
摘要：
将心理谓词归于基于大语言模型（LLM）的聊天机器人等AI系统是否有意义？人们已直觉性地开始将情感或意识归于Social AI（“情感人工智能体”），由此引发的后果从爱恋到自杀不等。因此，这类归因是否合理的哲学问题极具现实意义。本文提出论点：LLM是路德维希·维特根斯坦意义上的语言使用者的具象化，但将心理谓词归于这类系统仍是一种功能主义的诱惑。Social AI并非成熟的语言使用者，反而更像是伊塔洛·卡尔维诺笔下的文学机器。本文将“LLM是维特根斯坦式语言使用者”与“卡尔维诺的文学生成写作机器”两种观点相结合，阐明了将二者等同进而向Social AI赋予心理谓词的过程中，固有的错误功能主义诱惑。最后，研究借助有朽计算（mortal computation）框架表明，Social AI缺乏叙事言说方式所需的基本自创生能力，也不具备该能力在人类（互动）行为意义建构中的作用。这类心理谓词归因或许可以成立：“从量变到质变”的转变可能发生，但其路径介于生死之间，而非介于情感人工制品与文学机器的情感模拟之间。
英文摘要：
Is it sensical to ascribe psychological predicates to AI systems like chatbots based on large language models (LLMs)? People have intuitively started ascribing emotions or consciousness to social AI ('affective artificial agents'), with consequences that range from love to suicide. The philosophical question of whether such ascriptions are warranted is thus very relevant. This paper advances the argument that LLMs instantiate language users in Ludwig Wittgenstein's sense but that ascribing psychological predicates to these systems remains a functionalist temptation. Social AIs are not full-blown language users, but rather more like Italo Calvino's literature machines. The ideas of LLMs as Wittgensteinian language users and Calvino's literature-producing writing machine are combined. This sheds light on the misguided functionalist temptation inherent in moving from equating the two to the ascription of psychological predicates to social AI. Finally, the framework of mortal computation is used to show that social AIs lack the basic autopoiesis needed for narrative façons de parler and their role in the sensemaking of human (inter)action. Such psychological predicate ascriptions could make sense: the transition 'from quantity to quality' can take place, but its route lies somewhere between life and death, not between affective artifacts and emotion approximation by literature machines.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
