人工智能时代的价值贡献测度与分配正义重构——基于公善贡献的理论探索

中文摘要

人工智能和平台经济正在重塑劳动、资本与社会价值的关系。劳动替代、数据垄断与财富集中加剧了传统分配原则的解释压力，而照护、教育、公共卫生等公善贡献常难以被市场价格充分识别。与此同时，人工智能在全球范围内对不同经济体和劳动者群体产生差异化影响，国际分配不平等问题日益凸显。为回应这一挑战，本文提出将公善贡献作为分配正义的补充性参考维度。公善贡献是指主体通过产品、服务、制度或行动满足他人合理私善、增进社会福祉的价值创造。在吸收能力方法、公共价值理论、社会影响评估和数字治理研究启发的基础上，本文构建人本价值模型（HumanisticValueModel,HVM），从认知能力、服务人数、服务时长和服务深度四个维度对公善贡献进行启发式评估。基于此，本文设计"尊严底线—贡献激励—约束调节"的三层分配结构：以底线分配保障基本尊严，以贡献分配激励真实价值创造，以约束分配调节垄断性、掠夺性和投机性收益；并进一步提出负外部性调节与公善贡献补偿机制。这一框架旨在为人工智能时代的分配正义提供一种补充性校正视角，在科技进步、经济效率与人的尊严之间寻求更合理的制度连接，同时回应国内与国际层面的AI分配不平等挑战

Abstract

Artificial intelligence and the platform economy are reshaping the relations among labor, capital, and social value. Labor substitution, data monopoly, and wealth concentration intensify the explanatory pressure on traditional principles of distribution, while public-good contributions in care, education, and public health are often hard to adequately recognize through market prices. At the same time, AI produces differentiated effects across economies and worker groups worldwide, and international distributional inequality is becoming increasingly salient. To respond to this challenge, the paper proposes taking public-good contribution as a supplementary reference dimension of distributive justice. Public-good contribution refers to the value creation by which subjects satisfy others' reasonable private goods and enhance social welfare through products, services, institutions, or actions. Inspired by the capability approach, public value theory, social impact assessment, and digital governance research, the paper constructs the Humanistic Value Model (HVM), which heuristically evaluates public-good contribution along four dimensions: cognitive capacity, number of people served, duration of service, and depth of service. On this basis, the paper designs a three-layer distribution structure of "dignity bottom line, contribution incentive, and constraint regulation": bottom-line distribution guarantees basic dignity, contribution distribution incentivizes genuine value creation, and constraint regulation adjusts monopoly, predatory, and speculative gains; it further proposes negative-externality regulation and a compensation mechanism for public-good contribution. This framework aims to provide a supplementary corrective perspective on distributive justice in the age of AI, seeking a more reasonable institutional connection among technological progress, economic efficiency, and human dignity, while responding to domestic and international challenges of AI-related distributional inequality.

关键词：人工智能；分配正义；公善贡献；价值测度；数字治理；人本价值模型

Keywords: Artificial intelligence; distributive justice; public-good contribution; value measurement; digital governance; Humanistic Value Model