AI Public Value Creation: Data Encoding, Aggregation, and Algorithmic Computation

Abstract

AI systems in public administration challenge the premise that value creation arises from managers' strategic mediation among the vertices of Moore's strategic triangle: Public value, legitimacy, and operational capacity. AI imposes new logics that reshape vertices and their interaction dynamics. Critically, these transformations become entrenched through what we term algorithmic public value lock-in: the crystallization of contingent value definitions into durable technical infrastructures resistant to democratic revision. Examining Peru's SISFOH, an algorithmic welfare-targeting system, we reveal three interconnected shifts: data management recasts legitimacy as computational objectivity; standardized classifications redefine public value in narrow, quantifiable terms; and algorithmic processing transforms operational capacity from adaptive discretion to rigid execution. Together, these shifts produce lock-in effects that potentially insulate public value creation from political negotiation.