管理(神学)
认知
奖学金
平民
知识管理
社会分布认知
心理学
人力资源
公司治理
集体智慧
劳动力
社会学
概念框架
公共关系
资源(消歧)
认知科学
人力资源管理
概念模型
组织理论
悲剧
政府(语言学)
工程伦理学
组织有效性
人类智力
业务
劳动力发展
管理
组织学习
专业发展
悲剧(事件)
标识
DOI:10.1177/15344843261470602
摘要
Artificial intelligence is reshaping cognitive work, but Human Resource Development scholarship has treated this transformation as an organizational training challenge, leaving the collective regeneration of professional expertise unexamined. This conceptual paper introduces the Cognitive Commons framework, integrating commons theory, HRD scholarship, and distributed cognition to explain how rational AI adoption decisions can deplete the shared expertise pool professions require for renewal. The framework distinguishes Internalized Mastery (deep domain knowledge from sustained practice) from Distributed Mastery (orchestrating human-AI systems), and develops the Validation Tether: effective AI oversight depends on the expertise AI adoption may undermine. Early labor market and clinical evidence suggests possible disruption to expertise-regeneration pathways in highly AI-exposed sectors, though adoption is recent and the strongest signals come from leading sectors rather than all professions. Five factors determine occupational vulnerability, and governance arrangements may form across organizational, professional-association, and policy levels. The paper reframes expertise development as collective stewardship rather than organizational optimization, with implications for HRD theory and workforce policy.
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