人工智能会说我们的语言吗?对生成语言模型的伽达默尔式评估

Phillip Pinell
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摘要

语言论证是人类独特性的经典论证,千百年来一直被用来区分人类和非人类动物。生成语言模型(GLMs)对传统的基于语言的人类独特性模型提出了挑战,正是因为它们能够以类似人类语言能力的方式进行交流和回应。本文提出的问题是:GLMs 获得了自然语言吗?运用伽达默尔的语言理论,我认为它们没有。虽然通用语言模型能够可靠地生成可被解释为 "文本 "的语言内容,但它们缺乏语言所提供的以语言为媒介的现实。这些模式缺少了语言建构现实的四个关键特征:立足世界、理解、社区和传统。最后,我对全球语言模型能否实现自然语言持怀疑态度,因为它们在语言发展过程中缺乏这些特征。
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Does Artificial Intelligence Speak Our Language?: A Gadamerian Assessment of Generative Language Models
The language argument is a classic argument for human distinctiveness that, for millenia, has been used to distinguish humans from non-human animals. Generative language models (GLMs) pose a challenge to traditional language-based models of human distinctiveness precisely because they can communicate and respond in a manner resembling humanity’s linguistic capabilities. This article asks: have GLMs acquired natural language? Employing Gadamer’s theory of language, I argue that they have not. While GLMs can reliably generate linguistic content that can be interpreted as “texts,” they lack the linguistically mediated reality that language provides. Missing from these models are four key features of a linguistic construction of reality: groundedness to the world, understanding, community, and tradition. I conclude with skepticism that GLMs can ever achieve natural language because they lack these characteristics in their linguistic development.
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