Desire as Orientation Error III explores a foundational question for artificial intelligence, governance, and decision-making systems: What happens when coherence becomes a substitute for orientation? Modern AI systems are increasingly capable of generating fluent, persuasive, and internally consistent outputs. Yet coherence alone does not demonstrate that sufficient orientation has been established. A system may produce answers that appear reasonable, truthful, and useful while operating under unresolved assumptions, ambiguous references, or insufficient context. This paper introduces the concept of Coherent Drift—the condition in which interpretation proceeds before sufficient orientation has been established. Unlike traditional discussions of hallucination, error, or assumption drift, Coherent Drift examines how highly coherent outputs can conceal unresolved orientational conditions, causing both humans and intelligent systems to mistake plausibility for understanding. Drawing from artificial intelligence, governance, psychology, healthcare, robotics, and human decision-making, the paper argues that many failures attributed to intelligence are actually failures of orientation. As AI systems increasingly serve as advisors, collaborators, companions, and autonomous actors, the distinction between coherence and orientation becomes increasingly important. The central claim is that the challenge is no longer merely generating coherent answers. The challenge is ensuring that interpretation remains sufficiently oriented before coherence is allowed to stand in its place. Keywords: Orientation, Coherence, Artificial Intelligence, Governance, Hallucination, Human-AI Interaction, Decision-Making, Interpretation, Context, Reference Validation, Coherent Drift.
Christian Paré (Tue,) studied this question.