AI hallucination is not a bug, it's a communication issue

Large Language Models (LLMs) are currently deployed as universal answer engines, yet they operate without an inherent "truth-meter." This paper defines AI hallucination not as a malfunction of knowledge, but as a structural consequence of the Duty to Answer—a systemic bias that forces probabilistic models to generate output even when provided with high-entropy (vague or fragmented) input. We propose the Kern 42 Framework as a solution, introducing a pre-computation audit layer to evaluate semantic density and reduce the global energy footprint of "statistical fictions."