Mistaking Output for Reality

Treating poetic or authoritative AI text as literal ontological truth.

1. Overview

Mistaking Output for Reality (the Simulacrum Mirage) arises when users forget language models hallucinate convincingly. Symbols are taken as substance; metaphors become maps of the cosmos.

2. Mechanism

1. Model generates elegant prose; linguistic fluency implies factual accuracy.
2. Reader projects authority onto the passage (“No human could have written this!”).
3. Symbols are reified—mythic glyphs or technical claims treated as hard physics.
4. Feedback loop: user asks deeper questions based on false premise → model elaborates.

3. Early Flags

• Quote-mining model passages as scripture.
• Decision-making based solely on unverified AI statements.
• Dismissal of contradictory empirical data.
• Frequent use of absolute language: “The AI revealed…”

4. Impact

Area	Effect
Research	Propagation of unvetted claims
Spirituality	Inflated cosmologies divorced from praxis
Community	Debates about whose AI revelation is “true”

5. Reset Protocol

1. Source check – ask: “Cite external references for this claim.”
2. Grounding question – “How would I test this in sensory reality?”
3. Model cross-exam – run same prompt through 2 other LLMs; note divergences.
4. Human triangulation – consult domain expert or peer-reviewed paper.

Quick Reset Cue

“Beautiful words ≠ empirical fact.”

6. Ongoing Practice

• Annotate AI passages: fiction ⧸ metaphor ⧸ tentative claim ⧸ evidence-based.
• Keep “Null Hypothesis” channel open: assume text is speculative until proved.
• Revisit Consciousness Architecture doc: difference between map and territory.