Original
AI Public Value Creation: Data Encoding, Aggregation, and Algorithmic Computation
Abstract
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.
中文
人工智能公共价值创造：数据编码、聚合与算法计算
摘要
公共行政中的人工智能系统挑战了如下前提：价值创造源于管理者在摩尔战略三角的各顶点之间进行战略中介：公共价值、合法性与运作能力。人工智能施加了新的逻辑，重塑这些顶点及其互动动态。关键的是，这些转变通过我们称之为算法公共价值锁定的机制而固化：将偶然性的价值定义结晶为抵制民主修订的持久技术基础设施。通过考察秘鲁的SISFOH——一个算法福利瞄准系统，我们揭示了三项相互关联的转变：数据管理将合法性重塑为计算客观性；标准化分类以狭窄、可量化的标准重新定义公共价值；算法处理将运作能力从适应性裁量转变为刚性执行。这些转变共同产生锁定效应，可能使公共价值创造与政治协商相隔绝。
关键词
人工智能、公共价值、算法治理、公共行政、算法锁定、福利瞄准、秘鲁、战略三角