Be ethical then proficient: navigating employees’ ethical adoption of generative AI in the workplace

业务 公共关系 道德领导 生成语法 工程伦理学 社会学 心理学 政治学 工程类 计算机科学 人工智能
作者
Yang Yi,Dongya Wang,Jo-Yun Li,Yeunjae Lee,Weiting Tao
出处
期刊:Journal of Communication Management [Emerald (MCB UP)]
被引量:1
标识
DOI:10.1108/jcom-10-2024-0206
摘要

Purpose As the use of generative artificial intelligence (Gen AI) grows in the workplace, organizations prioritize employee training due to ethical concerns. Employing the social-cognitive perspective of moral action, this project examined how organizations’ communication strategies and employees’ ethical orientations collectively impact the Gen AI training outcomes. Design/methodology/approach An online survey was conducted in February 2024 with 500 full-time employees in the United States whose organizations had implemented any form of Gen AI training. Structural equation modeling (SEM) and Hayes’s PROCESS Model 1 were employed for the data analysis. Findings The results revealed that change leadership and transparent communication during the training fostered ethical Gen AI adoption. Such enhanced ethical adoption of Gen AI subsequently enhanced employees’ proficient use of this technology. Employees’ ethical orientations (deontology and consequentialism) moderated this effect: those with lower procedural ethics (higher scores in consequentialism and lower scores in deontology) were more likely to be influenced by their leaders’ change-related actions. Originality/value The study provides theoretical insights and practical advice for utilizing organizations’ efforts to navigate employees’ Gen AI usage at work. Theoretically, the study presents an organizational communication framework connecting leadership, internal communication, ethical readiness, and work empowerment outcomes to guide employees’ ethical decision-making during new implementations and training. Practically, it provides organizations with data-proven Gen AI ethical training suggestions, such as enhancing leaders’ change-specific guidance and building transparent training environments.

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