Klowait Nils, Erofeeva Maria
Transregional Collaborative Research Centre 318, Faculty of Mechanical Engineering, Department of Technology and Diversity, Paderborn University, Paderborn, Germany.
Laboratory of Anthropology of Contemporary Worlds (LAMC), Faculty of Philosophy and Social Sciences, Institute of Sociology, Université Libre de Bruxelles (ULB), Brussels, Belgium.
Front Sociol. 2025 Aug 21;10:1614473. doi: 10.3389/fsoc.2025.1614473. eCollection 2025.
Contemporary debates about artificial intelligence (AI) still treat automation as a straightforward substitution of human labor by machines. Drawing on Goffman's dramaturgical sociology, this paper reframes AI in the workplace as rather than automation. We argue that the central-but routinely overlooked-terrain of struggle is symbolic-interactional: workers continuously stage, conceal, and re-negotiate what counts as "real" work and professional competence. Large language models (LLMs) such as ChatGPT exemplify this dynamic. They quietly take over the invisible, routinised tasks that underpin cognitive occupations (editing, summarizing, first-draft production) while leaving humans to enact the highly visible or relational facets that sustain occupational prestige. Drawing on diverse sources to illustrate our theoretical argument, we show how individual workers, dramaturgical teams, and entire professional fields manage impressions of expertise in order to counter status threats, renegotiate fees, or obscure the extent of AI assistance. The paper itself, having been intentionally written with the 'aid' of all presently available frontier AI models, serves as a meta-reflexive performance of professional self-staging. The dramaturgical framework clarifies why utopian tales of friction-free augmentation and dystopian narratives of total displacement both misread how automation is actually unfolding. By foregrounding visibility, obfuscation, and impression management, the article presents a differentiated case for AI's impact on the performative structure of work, outlines diagnostic tools for assessing real-world AI exposure beyond hype-driven headlines, and argues for a more human-centered basis for evaluating policy responses to the 'fourth industrial revolution.' In short, AI enters the labor process not as an autonomous actor, but as a prop within an ongoing social performance-one whose scripts, stages, and audiences remain irreducibly human.
当代关于人工智能(AI)的争论仍将自动化视为机器对人类劳动的直接替代。借鉴戈夫曼的戏剧社会学理论,本文将工作场所中的人工智能重新界定为 而非自动化。我们认为,斗争的核心——但经常被忽视的领域——是符号互动层面的:工人不断地上演、隐藏并重新协商什么才算是“真正的”工作和专业能力。ChatGPT等大型语言模型(LLMs)就是这种动态变化的例证。它们悄然接管了支撑认知职业的无形的、常规化的任务(编辑、总结、初稿撰写),而让人类去承担那些维持职业声望的高度可见或涉及人际关系的方面。我们借鉴多种资料来源来说明我们的理论观点,展示个体工人、戏剧团队和整个专业领域如何管理专业形象,以应对地位威胁、重新协商费用或掩盖人工智能协助的程度。本文本身就是在当前所有可用的前沿人工智能模型的“协助”下有意撰写的,它是专业自我呈现的一种元反思性表现。戏剧框架阐明了为什么无摩擦增强的乌托邦故事和完全替代的反乌托邦叙事都误解了自动化的实际发展情况。通过突出可见性、模糊性和印象管理,本文阐述了人工智能对工作表演结构影响的差异化情况,勾勒了用于评估现实世界中人工智能影响(而非炒作驱动的头条新闻)的诊断工具,并主张以更以人为本的基础来评估对“第四次工业革命”的政策回应。简而言之,人工智能进入劳动过程并非作为一个自主行为体,而是作为正在进行的社会表演中的一个道具——其脚本、舞台和观众仍然不可避免地是人类。