AI Language Models Revive Study of Wittgenstein’s Theory “Meaning is Use”

The success of AI language models in producing coherent, informative text that resonates with human readers has reignited interest in philosopher Ludwig Wittgenstein’s theory that “meaning is use” when it comes to language.

Wittgenstein’s perspective on meaning: In his influential work “Philosophical Investigations,” Wittgenstein argued that in many cases, the meaning of a word is determined by its practical use within a language, rather than by some inherent, fixed definition:

• He famously stated, “For a large class of cases of the employment of the word ‘meaning’ – though not for all – this word can be explained in this way: the meaning of a word is its use in the language.”
• This view suggests that language derives its meaning from the complex web of social practices, conventions, and contexts in which words are deployed, rather than from some essential, unchanging essence.

Implications of AI language models for Wittgenstein’s theory: The apparent success of AI systems in generating human-like text based on statistical analysis of vast language datasets raises intriguing questions about the nature of meaning and its relationship to use:

• If machines can produce text that strikes humans as meaningful and coherent without possessing genuine understanding, does this lend credence to the notion that meaning in language is fundamentally a matter of use and convention?
• The fact that AI language models are trained on massive corpora of human-generated text and learn to mimic patterns of word usage could be seen as aligning with Wittgenstein’s emphasis on meaning as arising from practical linguistic behavior.

Caveats and open questions: While the achievements of AI language models are impressive, it’s important to approach the philosophical implications with caution and to recognize the limitations of current systems:

• Wittgenstein himself was skeptical of the idea of thinking machines, famously remarking, “But surely a machine cannot think!”
• The question at hand is not whether AI systems truly understand, think, or possess consciousness, but rather whether their ability to generate seemingly meaningful text through statistical analysis supports a use-based theory of linguistic meaning.
• It remains unclear whether the success of AI language models in mimicking human language use fully captures the richness and complexity of meaning as it functions in human communication and cognition.

Broader significance for philosophy of language: The intersection of AI and Wittgenstein’s ideas highlights the ongoing relevance of philosophical debates about the nature of language and meaning in the era of advanced language technologies:

• As AI systems become increasingly sophisticated in their ability to process and generate human-like language, they serve as a valuable testbed for exploring longstanding questions in the philosophy of language.
• The success of AI language models in producing coherent text based on patterns of use may lend support to use-based theories of meaning, but further philosophical analysis and empirical investigation will be needed to fully unpack the implications.
• Engaging with the philosophical dimensions of AI language technologies can enrich our understanding of both the capabilities and limitations of these systems, as well as shed new light on fundamental questions about the nature of language and meaning.