在工作中使用基于增强的人工智能工具:基于学习的收益与挑战的日常调查

IF 9.3 1区 管理学 Q1 BUSINESS Journal of Management Pub Date : 2024-07-31 DOI:10.1177/01492063241266503
Yiduo Shao, Chengquan Huang, Yifan Song, Mo Wang, Young Ho Song, Ruodan Shao
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引用次数: 0

摘要

基于增强技术的人工智能(AI)工具正越来越多地融入工作场所。员工和人工智能工具优势互补,两者的结合扩大并加快了员工获取信息的速度,并提供了重要的学习机会。然而,现有研究尚未充分了解员工在增强过程中基于学习的收益和挑战。结合人工智能增强技术文献和认知负荷理论,我们开展了一项每日日记研究,以了解员工在日常工作中使用基于增强技术的人工智能的体验。我们推测并发现,一方面,在工作日期间频繁使用基于增强功能的人工智能与更多的知识增长相关,从而在工作日结束时获得更好的任务绩效。另一方面,频繁使用增强型人工智能也会导致员工信息超载,进而影响他们在工作日结束时的工作表现和恢复能力。除了阐明相互抵消的机制外,我们还发现员工对经验的开放性是一种倾向性因素,而积极情绪则是一种瞬间状态,它们影响着员工在工作日使用基于增强功能的人工智能的效果。我们的研究对于从基于学习的角度理解人工智能增强动态以及人工智能对广大员工的影响具有重要意义。
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Using Augmentation-Based AI Tool at Work: A Daily Investigation of Learning-Based Benefit and Challenge
Augmentation-based artificial intelligence (AI) artifacts are increasingly being incorporated into the workplace. The coupling of employees and AI tools, given their complementary strengths, expands and expedites employees’ access to information and affords important learning opportunities. However, existing research has yet to fully understand the learning-based benefits and challenges for employees in augmentation. Integrating insights from AI augmentation literature and cognitive load theory, we conducted a daily diary study to understand employees’ experience using augmentation-based AI at work on a daily basis. We theorized and found that, on the one hand, frequent usage of augmentation-based AI during a workday was associated with greater knowledge gain and subsequently better task performance at the end of the workday. On the other hand, using augmentation-based AI frequently also led employees to experience information overload, which in turn impaired their performance and recovery at the end of the workday. In addition to elucidating the countervailing mechanisms, we identified employee openness to experience as a dispositional factor, and positive affect as a momentary state that shaped the effects of using augmentation-based AI over the workday. Our research has implications for understanding AI augmentation dynamics from a learning-based perspective, as well as AI’s impact on employees at large.
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来源期刊
CiteScore
22.40
自引率
5.20%
发文量
0
期刊介绍: The Journal of Management (JOM) aims to publish rigorous empirical and theoretical research articles that significantly contribute to the field of management. It is particularly interested in papers that have a strong impact on the overall management discipline. JOM also encourages the submission of novel ideas and fresh perspectives on existing research. The journal covers a wide range of areas, including business strategy and policy, organizational behavior, human resource management, organizational theory, entrepreneurship, and research methods. It provides a platform for scholars to present their work on these topics and fosters intellectual discussion and exchange in these areas.
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