Advances in Psychological Science ›› 2024, Vol. 32 ›› Issue (12): 2005-2017.doi: 10.3724/SP.J.1042.2024.02005
• Conceptual Framework • Previous Articles Next Articles
WANG Yongyue1, HUANG Piaopiao1, JIN Yanghua2, BAI Xinwen3, YUE Fengkai1, ZHANG Fanying1, GUO Zihao1
Received:
2024-03-21
Online:
2024-12-15
Published:
2024-09-24
CLC Number:
WANG Yongyue, HUANG Piaopiao, JIN Yanghua, BAI Xinwen, YUE Fengkai, ZHANG Fanying, GUO Zihao. Technical hollowing out of knowledge workers in the manufacturing industry in artificial intelligence context: The definition, formation and influence mechanism[J]. Advances in Psychological Science, 2024, 32(12): 2005-2017.
[1] 蔡莉, 杨亚倩, 詹天悦, 盛乃珩. (2022). 数字经济下创新驱动创业过程中认知、行为和能力的跨层面作用机制—基于三一集团的案例研究. [2] 曹昕怡, 王前. (2021). 人工智能对人类思维能力的双重影响. [3] 高中华, 徐燕. (2023). 智能制造师徒关系理论构建及对团队双元创新的驱动机制. [4] 胡双钰, 吴和成. (2023). 技术多元化、吸收能力与创新绩效. [5] 李敏, 黄海艳. (2022). 工业机器人应用与制造业企业创新绩效——基于研发投入和员工知识能力的中介效应. [6] 梁萌. (2015). 知识劳动中的文化资本重塑—以E互联网公司为例. [7] 马克思. (1985). 马克思 1844 年经济学哲学手稿 (中共中央马克思恩格斯列宁斯大林著作编译局译). 人民出版社. (原著发表于1932年) [8] 邱子童, 吴清军, 杨伟国. (2019). 人工智能背景下劳动者技能需求的转型: 从去技能化到再技能化. [9] 束超慧, 王海军, 金姝彤, 贺子桐. (2022). 人工智能赋能企业颠覆性创新的路径分析. [10] 孙强. (2020). 马克思主义视野下的人工智能与人权问题探析. [11] 王林辉, 姜昊, 董直庆. (2022). 工业智能化会重塑企业地理格局吗. [12] 汪前元, 魏守道, 金山, 陈辉. (2022). 工业智能化的就业效应研究—基于劳动者技能和性别的空间计量分析. [13] 王琼. (2022). 职业可续视角下的工作重塑行为研究: 动力, 路径及干预机制. [14] 王潇. (2019). 技术空心化: 人工智能对知识型员工劳动过程的重塑—以企业电子研发工程师为例. [15] 吴海民. (2012). 资产价格波动、通货膨胀与产业“空心化”—基于我国沿海地区民营工业面板数据的实证研究. [16] 谢小云, 左玉涵, 胡琼晶. (2021). 数字化时代的人力资源管理: 基于人与技术交互的视角. [17] 杨倩, 焦特, 雷亚萍. (2022). 团队心理资本对个体双元创新行为的影响研究. [18] 杨艳玲, 郑雁玲, 田宇. (2022). 渐进还是突破? 双元创新对新企业绩效的影响. [19] 尹萌, 牛雄鹰. (2024). 与 AI “共舞”: 系统化视角下的AI-员工协作. [20] 于文轩, 魏炜. (2023). 数据开放中的算法依赖: 发展模式与驱动路径. [21] Acemoglu D., Autor D., Hazell J., & Restrepo P. (2022). Artificial intelligence and jobs: Evidence from online vacancies. [22] AlQershi N., Saufi R. B. A., Yaziz M. F. B. A., Permarupan P. Y., Muhammad N. M. N., Yusoff M. N. H. B., & Ramayah T. (2023). The threat of robots to career sustainability, and the pivotal role of knowledge management and human capital. [23] Aminizadeh S., Heidari A., Toumaj S., Darbandi M., Navimipour N. J., Rezaei M., .. Unal, M.(2023). The applications of machine learning techniques in medical data processing based on distributed computing and the Internet of Things. [24] Baruch, Y., & Sullivan, S. E. (2022). The why, what and how of career research: A review and recommendations for future study. [25] Braverman, H. (1998). Labor and monopoly capital: The degradation of work in the twentieth century. NYU Press. [26] Bright, J. R. (1958). [27] Brougham, D., & Haar, J. (2018). Smart technology, artificial intelligence, robotics, and algorithms (STARA): Employees’ perceptions of our future workplace. [28] Cain, S. (2023-1-17). ‘This song sucks’: Nick Cave responds to ChatGPT song written in style of Nick Cave. [29] Cardon M. S., Stevens C. E., & Potter D. R. (2011). Misfortunes or mistakes?: Cultural sensemaking of entrepreneurial failure. [30] Cazzaniga M., Jaumotte M. F., Li L., Melina M. G., Panton A. J., Pizzinelli C., .. Tavares, M. M. M. (2024). [31] Cha J., Kim Y., & Kim T. Y. (2009). Person-career fit and employee outcomes among research and development professionals. [32] Chatterjee S., Chaudhuri R., & Vrontis D. (2022). Knowledge sharing in international markets for product and process innovation: Moderating role of firm’s absorptive capacity. [33] Danneels, E. (2002). The dynamics of product innovation and firm competences. [34] Daugherty P. R.,& Wilson, H. J. (2018). Human+ machine: Reimagining work in the age of AI. Harvard Business Press. [35] De Rond M., Holeman I., & Howard-Grenville J. (2019). Sensemaking from the body: An enactive ethnography of rowing the Amazon. [36] Dervin, B. (1999). Chaos, order and sense-making: A proposed theory for information design. Cambridge: MIT Press. [37] Dervin, B., & Frenette, M. (2001). Sense-making methodology: Communicating communicatively with campaign audiences. [38] De Vos A., Van Der Heijden, B. I. J. M., & Akkermans J. (2020). Sustainable careers: Towards a conceptual model. [39] Dwivedi Y. K., Kshetri N., Hughes L., Slade E. L., Jeyaraj A., Kar A. K., .. Wright R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. [40] Farhan, A. (2023). The impact of artificial intelligence on human workers. [41] Fayad, Y., & El Ebrashi, R. (2022). Social capital and corporate entrepreneurship: The role of absorptive capacity in emerging markets. [42] Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? [43] Fui-Hoon Nah F., Zheng R., Cai J., Siau K., & Chen L. (2023). Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration. [44] Gallie D., Felstead A., Green F., & Inanc H. (2017). The hidden face of job insecurity. [45] Haipeter, T. (2020). Digitalisation, unions and participation: The German case of ‘industry 4.0’. [46] Haug A., Adsbøll Wickstrøm K., Stentoft J., & Philipsen K. (2023). The impact of information technology on product innovation in SMEs: The role of technological orientation. [47] Ibrahim, S., & Fallah, M. H. (2005). Drivers of innovation and influence of technological clusters. [48] Iskender, A. (2023). Holy or unholy? Interview with open AI’s ChatGPT. [49] Jaiswal A., Arun C. J., & Varma A. (2022). Rebooting employees: Upskilling for artificial intelligence in multinational corporations. [50] Kellogg K. C., Valentine M. A., & Christin A. (2020). Algorithms at work: The new contested terrain of control. [51] Kok H., Faems D., & de Faria P. (2020). Ties that matter: The impact of alliance partner knowledge recombination novelty on knowledge utilization in R&D alliances. [52] Kong H. Y., Yuan Y., Baruch Y., Bu N., Jiang X., & Wang K. (2021). Influences of artificial intelligence (AI) awareness on career competency and job burnout. [53] Kreps, D., & Rowe, F. (2021 December). [54] Li J., Bonn M. A., & Ye B. H. (2019). Hotel employee’s artificial intelligence and robotics awareness and its impact on turnover intention: The moderating roles of perceived organizational support and competitive psychological climate. [55] Lingmont, D. N., & Alexiou, A. (2020). The contingent effect of job automating technology awareness on perceived job insecurity: Exploring the moderating role of organizational culture. [56] Mabungela, M. (2023). Artificial intelligence (AI) and automation in the world of work: A threat to employees? [57] Maitlis, S., & Christianson, M. (2014). Sensemaking in organizations: Taking stock and moving forward. [58] Malik N., Tripathi S. N., Kar A. K., & Gupta S. (2021). Impact of artificial intelligence on employees working in industry 4.0 led organizations. [59] Martin S. L., Javalgi R. G., & Cavusgil E. (2017). Marketing capabilities, positional advantage, and performance of born global firms: Contingent effect of ambidextrous innovation. [60] McArdle S., Waters L., Briscoe J. P., & Hall, D. T. T. (2007). Employability during unemployment: Adaptability, career identity and human and social capital. [61] McDonald K. S., Hite L. M., & O’Connor K. W. (2022). Developing sustainable careers for remote workers. [62] Meister D.,& Chandrasekhar, R. (2021). McCormick & Co: Deploying artificial intelligence in new product development (Case No. W25509). Ivey Publishing. [63] Morais-Storz M., Nguyen N., & Sætre A. S. (2020). Post- failure success: Sensemaking in problem representation reformulation. [64] Ng T. W., Eby L. T., Sorensen K. L., & Feldman D. C. (2005). Predictors of objective and subjective career success: A meta-analysis. [65] O’ Connor, S. (2022). Open artificial intelligence platforms in nursing education: Tools for academic progress or abuse? [66] Petropoulos, G. (2018). The impact of artificial intelligence on employment. [67] Piasna, A. (2024). Algorithms of time: How algorithmic management changes the temporalities of work and prospects for working time reduction. [68] Piszczek, M. M. (2017). Boundary control and controlled boundaries: Organizational expectations for technology use at the work-family interface. [69] Retkowsky J., Nijs S., Akkermans J., Jansen P., & Khapova S. N. (2023). Toward a sustainable career perspective on contingent work: A critical review and a research agenda. [70] Sandberg, J., & Tsoukas, H. (2015). Making sense of the sensemaking perspective: Its constituents, limitations, and opportunities for further development. [71] Scott, S. G., & Bruce, R. A. (1994). Determinants of innovative behavior: A path model of individual innovation in the workplace. [72] Smith, C. (2006). The double indeterminacy of labour power: Labour effort and labour mobility. [73] Srisathan W. A., Ketkaew C., & Naruetharadhol P. (2023). Assessing the effectiveness of open innovation implementation strategies in the promotion of ambidextrous innovation in Thai small and medium-sized enterprises. [74] Tang, C. S. (2022). Innovative technology and operations for alleviating poverty through women's economic empowerment. [75] Thomas J. B., Clark S. M., & Gioia D. A. (1993). Strategic sensemaking and organizational performance: Linkages among scanning, interpretation, action, and outcomes. [76] Thompson, P. (1983). [77] Trenerry B., Chng S., Wang Y., Suhaila Z. S., Lim S. S., Lu H. Y., & Oh P. H. (2021). Preparing workplaces for digital transformation: An integrative review and framework of multi-level factors. [78] Van der Heijden, B. I., & De Vos, A. (2015). Sustainable careers: Introductory chapter. In A. De Vos, Antwerp Management School and University of Antwerp, Belgium, B. I. Van der Heijden, Radboud University Institute for Management Research, Nijmegen, the Open University of the Netherlands, Heerlen, the Netherlands and Kingston University, London, UK (Eds.), Handbook of research on sustainable careers (pp. 1-19). Edward Elgar Publishing. [79] Van der Heijden B., De Vos A., Akkermans J., Spurk D., Semeijn J., Van der Velde M., & Fugate M. (2020). Sustainable careers across the lifespan: Moving the field forward. [80] Xu G., Xue M., & Zhao J. (2023). The relationship of artificial intelligence opportunity perception and employee workplace well-being: A moderated mediation model. [81] Yilmaz E. D., Naumovska I., & Aggarwal V. A. (2023). AI-driven labor substitution: Evidence from Google translate and ChatGPT.SSRN Electronic Journal, 60. [82] Yu, S. H., & Chen, H. C. (2020). External knowledge, intraorganisational networks and exploratory innovation: An empirical examination. [83] Zarifhonarvar, A. (2024). Economics of ChatGPT: A labor market view on the occupational impact of artificial intelligence. |
[1] | WENG Zhigang, CHEN Xiaoxiao, ZHANG Xiaomei, ZHANG Ju. Social presence oriented toward new human-machine relationships [J]. Advances in Psychological Science, 2025, 33(1): 146-162. |
[2] | WU Bo, ZHANG Aojie, CAO Fei. Professional design, user design, or AI design? The psychological mechanism of the source of design effect [J]. Advances in Psychological Science, 2024, 32(6): 995-1009. |
[3] | HOU Hanchao, NI Shiguang, LIN Shuya, WANG Pusheng. When AI learns to empathize: Topics, scenarios, and optimization of empathy computing from a psychological perspective [J]. Advances in Psychological Science, 2024, 32(5): 845-858. |
[4] | SHU Lifang, WANG Kui, WU Yueyan, CHEN Siyun. Multi-stage impacts of artificial intelligence coaches on consumers’ long-term goal pursuit and its mechanism [J]. Advances in Psychological Science, 2024, 32(3): 451-464. |
[5] | YIN Meng, NIU Xiongying. Dancing with AI: AI-employee collaboration in the systemic view [J]. Advances in Psychological Science, 2024, 32(1): 162-176. |
[6] | Wei Huang, Hengjiang Li, Diwei Wu, Huafu Chen, Hongmei Yan. Language Decoding for Visual Perception Based on Transformer [J]. Advances in Psychological Science, 2023, 31(suppl.): 11-11. |
[7] | TU Yan, HAO Po, LONG Lirong. Job replacement or job transformation? Definition, consequences, and sources of technology-driven job insecurity [J]. Advances in Psychological Science, 2023, 31(8): 1359-1373. |
[8] | JIANG Luyuan, CAO Limei, QIN Xin, TAN Ling, CHEN Chen, PENG Xiaofei. Fairness perceptions of artificial intelligence decision-making [J]. Advances in Psychological Science, 2022, 30(5): 1078-1092. |
[9] | DENG Shichang, XU Qi, ZHANG Jingjing, LI Xiangqian. User acceptance mechanism and usage promotion strategy of AI services based on mind perception theory [J]. Advances in Psychological Science, 2022, 30(4): 723-737. |
[10] | YUAN Yuzhuo, LUO Fang. Early screening and diagnosis of autism spectrum disorder assisted by artificial intelligence [J]. Advances in Psychological Science, 2022, 30(10): 2303-2320. |
[11] | JIANG Liming, TIAN Xuetao, REN Ping, LUO Fang. A new type of mental health assessment using artificial intelligence technique [J]. Advances in Psychological Science, 2022, 30(1): 157-167. |
[12] | Xu Yuanli,Guo Dejun. Discussing the Relations Between Emotional Intelligence and Affective Computing in Artificial Intelligence Simply [J]. , 2004, 12(2): 209-214. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||