工作场所人工智能应用对员工影响的元分析

doi:10.3724/SP.J.1042.2024.01621

摘要/Abstract

摘要：

随着数字科技的发展, 人工智能为组织带来了新的机会和挑战, 其在工作场所中的应用对员工行为和心理的影响日益得到学术界的密切关注。但相关影响方向、程度和边界等研究结论尚未取得共识。本研究对包含85个结果变量, 150个效应量的64篇国内外文献进行了元分析。研究发现：工作场所AI应用有助于触发员工工作投入、组织承诺、工作幸福感等积极心理, 调动其知识共享、数字创新、工作重塑等积极行为, 但同时也会引发员工焦虑、离职倾向、工作不安全感等消极心理, 出现知识隐藏、工作退缩、服务破坏等消极行为, 且AI应用类型、行业类型以及AI应用测量方式对上述关系有不同程度的调节作用。研究结论表明工作场所AI应用是一柄双刃剑, 它既可以作为技术支持丰富员工心理资源, 激发积极行为, 亦会给员工造成威胁从而消耗心理资源, 引发消极行为。本研究在工作要求−资源模型的理论框架下, 明晰了工作场所AI应用与员工行为和心理结果变量间的关系效果以及边界条件, 对组织科学地调整AI管理方式、引导员工正确认识AI以有效发挥其价值具有指导意义。

关键词: 工作场所, 人工智能应用, 积极行为和心理, 消极行为和心理, 元分析

Abstract:

Given the widespread application of artificial intelligence (AI) technologies in workplaces, there has been a rapid increase in literature exploring AI-related themes. Scholars are increasingly focused on understanding how these applications influence employee behaviors and psychology. However, consensus on the direction, boundaries, and extent of these effects remains elusive. To address this issue, this paper conducts a meticulous review and selection of literature published from January 2017 to July 2023. A meta-analysis is performed on the 64 literatures (N = 150) to advance knowledge in three main areas: (1) Explore the strength and direction of the relationship between AI application and employees’ positive behaviors and psychological effects, as well as their negative behaviors and psychological effects. This aims to clarify the inconsistent conclusions and fill gaps in quantitative integration. (2) Based on the Job Demands-Resources model, this paper delineates the theoretical rationale underlying the impact of AI on employees’ behavior and psychology within an organizational context, upon its integration as a new technology, and elucidate specific pathways of its effects. (3) Investigate whether the effects of AI application on employee behavior and psychology are potentially influenced by the type of AI application, industry context, and measurement methods. Endeavor to furnish a clearer and more comprehensive overview of the correlation between AI and employee outcomes, thereby providing a theoretical foundation for tailored AI advantages in practical settings and methodological designs for subsequent empirical research in academia.

The result finds that: (1) The application of AI in the workplace exhibits a “double-edged sword” effect, which can enrich employees' psychological resources as technical support and stimulate positive behaviors, may also threaten employees to consume psychological resources and cause negative behaviors. (2) The relationships between AI application and employee behaviors/psychological effects vary under different AI types. Assisted and augmented AI enhance employee job satisfaction by reducing task costs, thereby increasing work engagement, creativity, and productivity. Such abundance in work resources contributes to an uplift in employees' job satisfaction and happiness. Consequently, when employees experience greater job involvement, there is a notable increase in creativity and productivity. However, managerial and autonomous AI types, despite improving efficiency and autonomy to some extent, introduce stress due to their supervisory and controlling attributes, suppressing positive work experiences and fostering negative psychological states. (3) Variations in AI application effects on employee behaviors and psychological effects across different industry types are evident. Employees in labor-intensive industries, with structured work environments and lower occupational skills, perceive more negative effects from AI. Conversely, employees in knowledge-intensive industries benefit from more flexible and autonomous work environments enhanced by AI, demonstrating stronger abilities in receiving, learning, and adapting to new information and technologies. (4) The relationship between AI application and employee behavior, as well as psychological impacts, varies depending on diverse measurement of AI application. Studies using subjective evaluations tend to reveal more negative impacts of AI on employee behaviors and psychological effects compared to those using objective measurement methods.

This study has made several theoretical contributions: (1) Systematically integrate and evaluate the fragmented research conclusions on the effects of AI application on employee behaviors and psychology, synthesizing empirical findings and responding to calls in the literature for understanding the personal impacts of automation technologies. (2) Within the framework of Job Demands-Resources model, this paper elucidates the diverse impacts of different types of AI application on employee behavior and psychology, expands the influencing factors that could augment the positive results of AI application, and further validates the concerns regarding potential adverse consequences. (3) Enrich the boundary conditions in the relationship between workplace AI application and employee behavior and psychology. This paper explores the moderating effects of the type of AI application, industry context, and measurement methods, responding to the scholarly calls for further examination of moderating variables of AI application affecting employee experience, thereby offering new insights for inconsistent research conclusions in the academic literature. Beyond theoretical advancements, the results of this study provide guidance for organizations to scientifically adjust the management strategies of AI, accurately direct employees perceptions, and effectively maximize its value.

Key words: workplace, AI application, positive behavior and psychology, negative behavior and psychology, meta-analysis

中图分类号:

B849: C93

蒋建武, 龙晗寰, 胡洁宇. (2024). 工作场所人工智能应用对员工影响的元分析. 心理科学进展 , 32(10), 1621-1639.

JIANG Jianwu, LONG Hanhuan, HU Jieyu. (2024). A meta-analysis of the impact of AI application on employees in the workplace. Advances in Psychological Science, 32(10), 1621-1639.

图/表 11

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员工行为和心理	概念界定
积极行为效应	员工采取的能为自我职业生涯带来积极改变的行为。
积极心理效应	员工感知的持久及稳定的积极情感体验和主观倾向。
消极行为效应	员工采取的妨碍个人发展的负面工作或非工作行为。
消极心理效应	员工经历的不利于个人健康及发展的负面情绪状态。

员工行为和心理	概念界定
积极行为效应	员工采取的能为自我职业生涯带来积极改变的行为。
积极心理效应	员工感知的持久及稳定的积极情感体验和主观倾向。
消极行为效应	员工采取的妨碍个人发展的负面工作或非工作行为。
消极心理效应	员工经历的不利于个人健康及发展的负面情绪状态。

工作场所AI应用类型	实际应用	功能特征
辅助智能	虚拟助理、服务机器人等	辅助员工完成其原本能够完成的, 但需花费大量时间处理的日常性、基本性事宜。
增强智能	数据分析程序、情绪增强识别等	通过拓展人类思维能力和生理边界, 帮助员工完成其原本难以独自完成的任务, 发挥人脑与AI的互补优势。
管理智能	智能设备监控、AI决策等	通过AI算法智能管理员工任务, 并执行监管职能, 改进传统的工作流程。
自主智能	自动分拣机器人、无人驾驶快递车等	通过智能自动化技术取代员工完成低效能的重复程序化工作。

工作场所AI应用类型	实际应用	功能特征
辅助智能	虚拟助理、服务机器人等	辅助员工完成其原本能够完成的, 但需花费大量时间处理的日常性、基本性事宜。
增强智能	数据分析程序、情绪增强识别等	通过拓展人类思维能力和生理边界, 帮助员工完成其原本难以独自完成的任务, 发挥人脑与AI的互补优势。
管理智能	智能设备监控、AI决策等	通过AI算法智能管理员工任务, 并执行监管职能, 改进传统的工作流程。
自主智能	自动分拣机器人、无人驾驶快递车等	通过智能自动化技术取代员工完成低效能的重复程序化工作。

影响效果及方面		包含结果变量
积极效应	积极行为(26个)	工作绩效、知识共享、AI支持行为、数字创新、数字弹性、非正式学习、工作重塑、员工创造力、主动学习、关系重塑、认知重塑、预期绩效、员工生产力、知识共享、职业探索行为、服务质量、创新工作行为、服务革新行为、职业胜任力、工作目标达成、人际情绪调节行为、个人竞争生产力、自我扩展、学习导向行为、建言、突破性创新行为
积极效应	积极心理(28个)	工作信任、工作投入、工作旺盛感、工作胜任感、工作满意度、工作幸福感、工作安全感、工作自主性、突破性创新投入、AI使用意愿、与服务机器人合作意愿、内在动机、组织承诺、组织自尊、角色宽度自我效能、社会认同感、积极情绪、健康和福祉、继续使用意愿、AI技术接受意愿、程序公平感知、与AI合作意愿、整体幸福感、心理幸福感、生理幸福感、社会幸福感、变革支持意愿、冒险意愿
消极效应	消极行为(5个)	知识隐藏、家庭退缩行为、工作退缩行为、服务破坏、对机器人主管的报复
消极效应	消极心理(26个)	消极情绪、技能要求、工作要求、知识技能要求、AI焦虑、AI身份威胁、服务机器人技术焦虑、离职倾向、工作不安全感、工作强度、预期负荷、感知虐待、失业风险感知、抑郁、情绪耗竭、激情衰退、工作载荷、心理疲劳、身体疲劳、心理困扰、角色模糊、角色冲突、工作倦怠、压力、玩世不恭、威胁感知