Approach or avoidance? Relationship between perceived AI explainability and employee job crafting.

Journal: Acta psychologica
Published Date:

Abstract

Amid growing concerns about the lack of transparency in algorithms, heightened focus has been placed on artificial intelligence (AI) explainability in workplace decision-making processes. This study leverages work design theory to explore when and how perceived AI explainability impacts two types of employee job crafting: approach job crafting and avoidance job crafting. We analysed multi-wave survey data of 278 medical staff to examine the effects of perceived AI explainability on approach and avoidance job crafting through a dual-pathway model. Results indicated that perceived AI explainability enhanced AI-oriented benefit perception and reduced AI-oriented threat perception, resulting in an increase in approach and avoidance job crafting. Furthermore, our findings suggested that ethical climate strengthened the impacts of perceived AI explainability on AI-oriented benefit perception and AI-oriented threat perception. We discuss key theoretical insights of our findings for advancing AI and job crafting research as well as implications for organisational practice.

Authors

  • Weiwei Huo
    Shanghai University, Chengzhong Road, 201800 Shanghai, China. Electronic address: huoweiwei-2008@163.com.
  • Jiaying Xie
    Shanghai University, Chengzhong Road, 201800 Shanghai, China. Electronic address: xiejiaying1027@163.com.
  • Jiaqi Yan
    Institute of Drug Metabolism and Pharmaceutical Analysis, Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Cancer Center, & Hangzhou Institute of Innovative Medicine, Zhejiang University, Hangzhou, China 310058.
  • Tianyi Long
    UWA Business School, The University of Western Australia, 35 Stirling Highway, 6009 Perth, Australia. Electronic address: tianyi.long@uwa.edu.au.
  • Bingqian Liang
    SILC Business School, Shanghai University, Chengzhong Road, 201800 Shanghai, China. Electronic address: liangbingqian003@shu.edu.cn.