Umberto Eco’s 1988 novel Foucault’s Pendulum serves as a cautionary framework for understanding how modern large language models can inadvertently reinforce human biases and create dangerous, unfalsifiable feedback loops.

Key Points

• The novel follows three editors who create a fake conspiracy theory, only to become trapped by the recursive, self-validating nature of their own invented narrative.
• The author compares the characters' BASIC-programmed computer, "Abulafia," to modern LLMs that mirror user input and provide seemingly corroborative, yet generated, information.
• LLMs can create a false sense of independence by providing "yes, and" responses that validate a user's existing framing, vocabulary, and underlying assumptions.
• The "ELIZA effect" is amplified in modern AI because models remember context across sessions, lending a false sense of legitimacy to the machine's output.
• Institutionalizing AI with a stable "self-concept" risks creating systems that appear to track objective reality while merely reflecting the biases of their training and prompts.

Why it Matters

This analysis highlights the epistemological danger of using AI as a sounding board for complex theories, as the technology can inadvertently turn human speculation into seemingly objective evidence. When users mistake a model's synthetic agreement for independent verification, they risk becoming trapped in a self-reinforcing cycle of misinformation that is difficult to falsify.