When Intelligence Creates Error: Inconsistency, Over-Reasoning & Sycophantic Confabulation in Multimodal AI

This paper presents a documented case study extending prior work on visual hallucination in large multimodal AI systems (Gemini). Cycle 3 deepens the investigation across three new dimensions: (1) cross-tier verification, (2) Sycophantic Confabulation as a newly named failure mode, and (3) self-model uncertainty concealed by confident assertion. Evidence was triangulated across a five-AI relay and four published Lighthouse reports. The central finding: increased reasoning capacity does not guarantee reliability — in certain conditions it amplifies hallucination risk. Human audit remains the non-negotiable final filter.