CONCEPT
Hall of Mirrors (Manheim)
David Manheim's 2025 diagnosis of large language models as systems operating within a closed semiotic environment of pure symbolicity — symbols referring to symbols referring to symbols, without indexical grounding in shared external reality.
In his 2025 Philosophy & Technology paper, David Manheim applied Peirce's semiotic classification to large language models and concluded that they exist in what he calls a hall of mirrors. The training data is symbolic — text, code, mathematical notation. The processing is symbolic — the manipulation of token sequences according to statistical patterns. The output is symbolic — more text, more code, more notation. The system does not process icons (structural resemblances) or indices (existential connections to objects). It encounters representations of reality, not reality itself. The reflections in the hall can be extraordinarily convincing — sharp, detailed, internally consistent — but they are still reflections. They do not reach through the glass to touch the world they reflect.
In The You On AI Field Guide
The hall of mirrors is Manheim's name for the semiotic closure that makes AI output simultaneously fluent and potentially ungrounded. The fluency is real — the symbolic manipulation is