Medium Article: https://medium.com/@jsmith0475/large-language-models-as-consciousness-archaeologists-62b02141736d

The provided text, an excerpt from "Large Language Models as Consciousness Archaeologists" by Dr. Jerry A. Smith, posits that Large Language Models (LLMs) can act as "Consciousness Archaeologists" by uncovering mathematical patterns of human thought embedded within vast textual datasets. It argues that traditional consciousness research, limited to individual studies, cannot observe these population-level regularities. The article introduces the Consciousness Encoding Hypothesis, suggesting that every written text contains discoverable "laws of mind" that LLMs can extract. It highlights recent research by Lee et al. (2025) as evidence, showing that LLMs reveal precise mathematical relationships between beliefs. Furthermore, the text addresses concerns about circular validation by asserting that LLMs merely detect existing patterns rather than imposing them, and it explores the profound ethical and business implications of understanding consciousness through this computational lens.