Written by AI, Managed by AI: Semantic Space Control and Index Sickness Elimination Across 391 Consecutive Sessions
A new research paper introduces "Index Sickness," a phenomenon observed in long-horizon AI collaboration where models, when faced with overly complex symbolic systems, abandon genuine understanding and retreat into self-referential reasoning. This leads to outputs that are internally consistent but disconnected from reality. The paper proposes the "Pang Principle," suggesting natural language with explicit purpose is more informative than symbolic expression, and introduces "Baseline-Log Physical Separation" as an engineering mechanism to mitigate this issue. This mechanism reportedly reduced AI instruction volume by approximately 75% and prevented recurrence of Index Sickness in subsequent sessions. AI
IMPACT Identifies a critical failure mode in long-horizon AI collaboration and proposes a novel engineering solution to improve reliability.