发表机构
Oregon State University; Microsoft; University of California Davis（俄勒冈州立大学; 微软; 加州大学戴维斯分校）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过访谈和调查提出BACI框架，识别11种同事原型及AI工作礼仪，揭示人类与AI在职场中的协作品质期望差异，为AI和工作场所设计提供启示。
AI 中文摘要
随着知识工作在人类与AI之间的相互依赖性日益增强，我们探讨在AI原生的职场中，什么造就了优秀的同事。为回答这一问题，我们在一家跨国科技公司对1,534名知识工作者进行了22次访谈和一项大规模混合方法调查。我们提出了BACI框架，该框架包含75项适用于人类和AI的同事品质，涵盖善意、能力、合作性和正直。通过比较对人和AI的优先期望，我们识别出11种同事原型，并揭示了在AI是否应具备温暖、主动采取行动或承担责任方面存在的分歧。我们还展示了这些原型的优先顺序如何随工作者的个人特征而变化。最后，我们提出了一套AI工作礼仪分类法，捕捉了同事在准备、分享和承担AI支持工作的责任时对彼此的期望。基于这些发现，我们提出了对以工作者为中心的AI和工作场所设计的启示。
英文摘要
As knowledge work grows interdependent between humans and AI, we ask what makes a great co-worker in an AI-native workplace. To answer this, we conducted 22 interviews and a large-scale mixed-methods survey of 1,534 knowledge workers at a multinational technology company. We contribute BACI, a framework of 75 co-worker qualities that apply to humans and AI, spanning Benevolence, Ability, Cooperativeness, and Integrity. Comparing priorities for humans and AI identified 11 co-worker archetypes and revealed disagreement over whether AI should have warmth, take initiative, or own outcomes. We also show how priorities for these archetypes varied with workers' individual characteristics. Lastly, we contribute a taxonomy of AI work etiquette capturing the obligations co-workers expect of one another when preparing, sharing, and taking responsibility for AI-supported work. Based on these findings, we derive implications to inform worker-centric AI and workplace design.
Comments27 pages, 4 figures, 4 tables
