The Subject Supposed to Know Nothing: Lacan and the Large Language Model (thecombedthunderclap.blogspot.com)

A recent exploration by codepoetics draws parallels between the concepts of Continental Philosophy, particularly from thinkers like Derrida and Saussure, and the operational framework of Large Language Models (LLMs). The analysis suggests that LLMs function similarly to philosophical constructs such as différance, where meaning is derived from the relationships between words rather than fixed definitions, highlighting how these models generate meaning through a probabilistic system devoid of inherent subjectivity. This prompts a deeper inquiry into how LLMs, like Lacan's 'subject supposed to know,' evoke a semblance of understanding despite lacking any real consciousness or personal experience. This analogy raises important implications for the AI/ML community, particularly in understanding human interaction with these models. Users often attribute a level of knowingness to LLMs that they fundamentally do not possess, mistaking them for entities endowed with an understanding of human desires and needs. The discussion reveals that while LLMs can generate coherent and contextually relevant responses, they do so without any subjective agency, illuminating a paradox in the relationship between knowledge and truth. This enigma underscores the need for critical reflection on the capabilities of AI and our projections onto these systems, revealing a profound commentary on the nature of knowledge itself in the context of artificial intelligence.