AI systems experience a phenomenon known as 'Interpretation Drift', where the meaning interpretation fluctuates even under identical conditions, revealing a fundamental flaw in the inference structure rather than a model performance issue. This lack of a stable semantic structure means precision is often coincidental, posing significant risks in critical areas like business decision-making, legal judgments, and international governance, where consistent interpretation is crucial. The problem lies in the AI's internal inference pathways, which undergo subtle fluctuations that are difficult to detect, creating a structural blind spot in ensuring interpretative consistency. Without mechanisms to govern this consistency, AI cannot reliably understand tasks in the same way over time, highlighting a systemic crisis in AI governance. This matters because it underscores the urgent need for reliable AI systems in critical decision-making processes, where consistency and accuracy are paramount.
