Tang Pok Man, Koopman Joel, Mai Ke Michael, De Cremer David, Zhang Jack H, Reynders Philipp, Ng Chin Tung Stewart, Chen I-Heng
Department of Management, University of Georgia.
Department of Management, Texas A&M University.
J Appl Psychol. 2023 Nov;108(11):1766-1789. doi: 10.1037/apl0001103. Epub 2023 Jun 12.
The artificial intelligence (AI) revolution has arrived, as AI systems are increasingly being integrated across organizational functions into the work lives of employees. This coupling of employees and machines fundamentally alters the work-related interactions to which employees are accustomed, as employees find themselves increasingly interacting with, and relying on, AI systems instead of human coworkers. This increased coupling of employees and AI portends a shift toward more of an "asocial system," wherein people may feel socially disconnected at work. Drawing upon the social affiliation model, we develop a model delineating both adaptive and maladaptive consequences of this situation. Specifically, we theorize that the more employees interact with AI in the pursuit of work goals, the more they experience a need for social affiliation (adaptive)-which may contribute to more helping behavior toward coworkers at work-as well as a feeling of loneliness (maladaptive), which then further impair employee well-being after work (i.e., more insomnia and alcohol consumption). In addition, we submit that these effects should be especially pronounced among employees with higher levels of attachment anxiety. Results across studies ( = 794) with mixed methodologies (i.e., survey study, field experiment, and simulation study; Studies 1-4) with employees from four different regions (i.e., Taiwan, Indonesia, United States, and Malaysia) generally support our hypotheses. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
人工智能(AI)革命已经到来,因为人工智能系统越来越多地被整合到组织的各个职能中,融入员工的工作生活。员工与机器的这种结合从根本上改变了员工所习惯的与工作相关的互动方式,因为员工发现自己越来越多地与人工智能系统互动并依赖它们,而不是人类同事。员工与人工智能之间这种日益增加的结合预示着向一种更“非社交系统”的转变,在这种系统中,人们在工作中可能会感到社交上的脱节。借鉴社会归属模型,我们开发了一个模型来描述这种情况的适应性和适应不良后果。具体来说,我们提出理论,即员工在追求工作目标时与人工智能互动越多,他们就越会体验到对社会归属的需求(适应性的)——这可能会促使他们在工作中对同事提供更多帮助行为——以及孤独感(适应不良的),而这种孤独感随后会在下班后进一步损害员工的幸福感(即更多的失眠和饮酒)。此外,我们认为这些影响在依恋焦虑水平较高的员工中应该会特别明显。来自四个不同地区(即台湾、印度尼西亚、美国和马来西亚)的员工参与的混合方法(即调查研究、现场实验和模拟研究;研究1 - 4)的多项研究(N = 794)结果总体上支持了我们的假设。(PsycInfo数据库记录(c)2023美国心理学会,保留所有权利)