研究跨国公司员工用生成式AI的接受度，发现角色、语言、资历影响使用效果
AI Adoption Across a Multinational Workforce: Sociotechnical Conditions for GenAI Acceptance in Human Resources
- 分析员工角色、语言、工龄与AI系统适配性对采纳的影响
- 员工通过比对系统、查证来源、请教同事建立对AI的信任
- 适合关注职场AI公平部署和高风险场景设计的团队
生成式AI在工作场所的应用正快速推进，但谁会采纳、谁受益、谁被落下及其原因仍缺乏研究。本文以一家跨国科技公司从旧人力资源搜索系统转向生成式AI支持系统为背景，分析了搜索日志数据、问卷数据（n=25）及十次半结构化访谈。研究发现，采纳程度取决于生成式AI系统的设计假设与员工工作定位（角色、语言、任期）之间的匹配度。此外，员工对生成式AI答案的信任来自多源验证、跨系统比较以及在不确定时向同事或人力资源部门求助。本研究贡献有二：一是提供了组织转型期间生成式AI实际采纳的实证证据，表明采纳受情境适配性、搜索素养和信任校准的影响，并进一步受系统内容质量、员工培训和指导等知识条件塑造；二是将发现转化为高风险领域（如人力资源）中包容性部署的设计建议，主张应根据社会群体差异设计系统，同时将组织知识基础设施视为人工智能基础设施，以提升生成式AI系统的可问责性和可用性。
原文摘要 · Abstract (English)
Generative AI (GenAI) deployment in the workplace is accelerating rapidly. Nevertheless, questions of who adopts, who benefits, and who is left behind and why are still understudied. In this paper, we investigate these dynamics in the context of a multinational tech company transitioning from a legacy Human Resources (HR) search system to a GenAI-supported system, analyzing search log data, survey data (n=25), and ten semi-structured interviews. Our findings show that adoption depended on the fit between the GenAI system's design assumptions and employees' work positionalities (role, spoken language, tenure). Further, we find that employees' trust in GenAI answers was built through source-checking, comparison among systems, and seeking input from colleagues or HR when in doubt. Our contribution is twofold. First, we provide empirical evidence of workplace GenAI adoption during a live organizational transition, showing that adoption is influenced by factors such as situational fit, search literacy, and trust calibration. It is also further shaped by knowledge conditions such as the system's content quality, employee training, and guidance. Second, we translate these findings into design considerations for inclusive deployment and adoption in high-stakes environments such as HR. We argue that organizations should design systems considering the role and context-sensitive benefits they yield to different social groups. They also need to treat the organizational knowledge infrastructure as AI infrastructure to improve the accountability and usability of GenAI systems
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。