Humanness not just a feature: AI, meaningful work, and the structural imperatives of flourishing

David Hampton-Musseau, Anne-Laure Gatignon-Turnau, Yann Landon
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Abstract

The prompt absorption of artificial intelligence into organizational life raises a foundational question: not what AI does to jobs, but what it does to the conditions under which workers experience themselves as human. This paper advances the concept of humanness at work, defined as the capacity to experience oneself as an autonomous, competent, and socially recognized agent engaged in purposeful, relational contribution. Treated as the anthropological foundation from which AI governance and work design must be evaluated, humanness is not a secondary outcome of technological adoption but its proper governing criterion. The paper makes three theoretical contributions. First, it reconceptualizes meaningful work as the necessary structural condition through which humanness becomes organizationally possible, rather than a desirable psychological outcome or managerial instrument. Second, it introduces the humanness deficit to diagnose how AI-mediated arrangements systematically erode these conditions through three interconnected vectors: algorithmic control, achievement displacement, and passive substitution. Third, it develops the Digital Meaningful Job (DMJ), a multilevel sociotechnical framework extending the sociotechnical systems tradition, that positions humanness as the governing criterion for AI integration and operationalizes this commitment through four theoretical propositions. The paper concludes with a four-part research agenda, arguing that preserving humanness under AI conditions requires sustainable institutional arrangements that treat human flourishing as a non-negotiable design criterion rather than a residual consideration.

人性不仅仅是一个特征:人工智能,有意义的工作,以及繁荣的结构性要求
人工智能迅速融入组织生活提出了一个根本性的问题:不是人工智能对工作有什么影响,而是它对员工体验自己作为人类的条件有什么影响。本文提出了工作中的人性的概念,将其定义为体验自己作为一个自主的、有能力的、社会认可的从事有目的的、关系的贡献的代理人的能力。作为评估人工智能治理和工作设计的人类学基础,人性不是技术采用的次要结果,而是其适当的治理标准。本文的理论贡献有三点。首先,它将有意义的工作重新定义为必要的结构条件,通过这种条件,人性在组织上成为可能,而不是一种可取的心理结果或管理工具。其次,它引入了人性缺陷,以诊断人工智能介导的安排如何通过三个相互关联的向量:算法控制、成就置换和被动替代,系统地侵蚀这些条件。第三,它发展了数字有意义的工作(DMJ),这是一个多层次的社会技术框架,扩展了社会技术系统的传统,将人性定位为人工智能集成的管理标准,并通过四个理论命题来实现这一承诺。论文最后提出了一个由四部分组成的研究议程,认为在人工智能条件下保护人性需要可持续的制度安排,将人类繁荣视为一个不可谈判的设计标准,而不是一个剩余的考虑因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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