Language Is Cognitive Exhaust: How AI Reconstructs Thought from Text [pdf] (dn720908.ca.archive.org)

A recent paper from A. Jacobs of the Semantic Fidelity Lab introduces the concept of "language as cognitive exhaust," positing that language is not merely a transparent medium of communication but rather a compressed residue that reflects deeper cognitive processes. This perspective challenges traditional views, highlighting how language arises not from thoughts themselves but as an external representation of complex cognitive activities like perception, memory, and emotion. Understanding this dynamic is crucial as it shapes how large language models (LLMs) learn from linguistic artifacts rather than direct human experiences. The significance of this research for the AI/ML community lies in its implications for AI alignment, natural language processing, and human-AI interactions. By framing language as a projection of cognitive structures, the study underscores the importance of preserving "semantic fidelity," which ensures that the intent and meaning behind human communication are maintained. As AI systems increasingly mediate communication, safeguarding semantic fidelity becomes essential for upholding the integrity of human cognition and its rich nuances, thus informing the design principles for future AI technologies.