Inducement in AI-Mediated Decision Systems: A Framework for Decision Formation under Algorithmic Mediation

This paper develops a conceptual framework for understanding decision formation in AI-mediated systems. Rather than focusing solely on how decision spaces are structured, the paper introduces inducement as a probabilistic and structural mechanism through which certain decision trajectories become more likely under conditions of AI mediation. The framework integrates algorithmic mediation, decision formation, reflexive systems, and system-level counter-dynamics such as anti-GEO and anti-AEO. It argues that decision outcomes increasingly emerge through interaction between users and AI systems, rather than from fully pre-formed human preferences alone. This work contributes to ongoing discussions surrounding AI-mediated decision-making, preference construction, and the shifting relationship between human intent and computational systems.