Relational Expertise: What Machines Can't Know
基于实证研究，提出专长应被理解为通过互动关系构成，而非个人拥有的认知状态，并探讨这种关系性专长对AI在专业工作中应用的挑战。
Abstract Professions continue to be the primary means through which societies institutionalize expertise. Recent analyses and narratives predict that artificial intelligence (AI) will make meaningful inroads into non‐routine reasoning about complex cases, threatening the authority of professions. These predictions, we argue, draw on substantialist understandings of expertise as an intellectual possession, a mental achievement, or a cognitive state performed – by humans or machines – to achieve effects. A synthesis of empirical studies shows that expertise is more accurately conceptualized as relationally constituted – generated, applied, and recognized – through interactions. Relational expertise creates challenges of opacity, translation, and accountability for the development and deployment of AI technologies in the context of professional work. A relational understanding of expertise disrupts notions that professions may be augmented with, subordinated to, or dismantled by AI technologies. Instead, AI technologies are embedded in the network of interactions through which the relational expertise of professions is constituted.