Abstract As generative AI systems become increasingly capable, users often report a paradoxical shift in decision-making experience: interactions feel productive and accurate, yet prolonged use can lead to reduced self-initiated reasoning, fewer counter-questions, and a growing tendency to “let the system decide.” These phenomena are difficult to explain solely through conventional metrics such as accuracy, speed, or user experience (UX) improvements. This paper proposes a descriptive framework that treats the observed shift not as a matter of system intent or coercion, but as a gradual transformation of the user’s judgment process under repeated interaction. We introduce a three-stage model—Hesitation, Inhibition, and Dissolution—to describe how human judgment can be delegated externally over time. Hesitation refers to a momentary pause in the user’s own judgment formation when an external answer arrives faster than the user’s internal deliberation can stabilize. Inhibition describes the accumulation of rational micro-choices to avoid cognitive effort (“I do not need to think this through now”), reinforced by repeated successful outcomes. Dissolution denotes a state in which the user remains capable of making judgments, yet the authorship of judgment—the locus where alternatives are generated, assumptions are updated, and decisions are internally finalized—becomes persistently situated outside the person, with the human role shifting toward selection and approval rather than origination. Importantly, this model does not assume manipulation, malice, or forced dependence. Instead, it examines how delegation can become a stable, socially functional configuration when it improves efficiency and does not produce immediate friction or obvious losses. To make the model operationally discussable without moralizing, we emphasize observable traces of authorship, such as the frequency of counter-questions, constraint updates, explicit deferrals, rejections, and alternative generation. The paper does not prescribe whether delegation should be prevented, encouraged, or corrected. Rather, it offers a structured vocabulary for describing how delegation can occur and under what conditions it may become stable, thereby providing a conceptual basis for future design and evaluation discussions.
Satoshi Kawamoto (Mon,) studied this question.