Artificial intelligence and human integration: a conceptual exploration of its influence on work processes and workplace learning

References

• Abbas, R., and A. Munoz. 2021. “Designing Antifragile Social-Technical Information Systems in an Era of Big Data.” Information Technology & People 34 (6): 1639–1663. https://doi.org/10.1108/ITP-09-2020-0673.
   Web of Science ®Google Scholar
• Accenture. 2023. “A New Era of Generative AI for Everyone: The Technology Underpinning ChatGPT Will Transform Work and Reinvent Business.” https://www.accenture.com/content/dam/accenture/final/accenture-com/document/Accenture-A-New-Era-of-Generative-AI-for-Everyone.pdf.
   Google Scholar
• Ardichvili, A. 2022. “The Impact of Artificial Intelligence on Expertise Development: Implications for HRD.” Advances in Developing Human Resources 24 (2): 78–98. https://doi.org/10.1177/15234223221077304.
   Web of Science ®Google Scholar
• Bélanger, J. J., M. A. K. Lafrenière, R. J. Vallerand, and A. W. Kruglanski. 2013. “Driven by Fear: The Effect of Success and Failure Information on Passionate individuals’ Performance.” Journal of Personality and Social Psychology 104 (1): 180–195. https://doi.org/10.1037/a0029585.
   PubMed Web of Science ®Google Scholar
• Bennett, E. E., and R. R. McWhorter. 2022. “Dancing in the Paradox: Virtual Human Resource Development, Online Teaching, and Learning.” Advances in Developing Human Resources 24 (2): 99–116. https://doi.org/10.1177/15234223221079440.
   Web of Science ®Google Scholar
• Benson, A. D., S. D. Johnson, and K. P. Kuchinke. 2002. “The Use of Technology in the Digital Workplace: A Framework for Human Resource Development.” Advances in Developing Human Resources 4 (4): 393–404. https://doi.org/10.1177/152342202237518.
   Google Scholar
• Brynjolfsson, E. 2022. “The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence.” CoRR, abs. 2201 (4200). https://doi.org/10.48550/arXiv.2201.04200. https://arxiv.org/abs/2201.04200.
   Google Scholar
• Cassidy, B. 2023. “Exploring congress’ Framework for the Future of AI.” https://subscriber.politicopro.com/f/?id=0000018a-66f3-d0b1-a7eb-66f305860000&source=email.
   Google Scholar
• Charlier, S. D., R. P. Guay, and R. D. Zimmerman. 2016. “Plugged in or Disconnected? A Model of the Effects of Technological Factors on Employee Job Embeddedness.” Human Resource Management 55 (1): 109–126. https://doi.org/10.1002/hrm.21716.
   Web of Science ®Google Scholar
• Chi, O. H., G. Denton, and D. Gursoy. 2020. “Artificially Intelligent Device Use in Service Delivery: A Systematic Review, Synthesis, and Research Agenda.” Journal of Hospitality Marketing & Management 29 (7): 757–786. https://doi.org/10.1080/19368623.2020.1721394.
   Web of Science ®Google Scholar
• Coupe, T. 2019. “Automation, Job Characteristics and Job Insecurity.” International Journal of Manpower 40 (7): 1288–1304. https://doi.org/10.1108/IJM-12-2018-0418.
   Web of Science ®Google Scholar
• Di Fiore, A., S. Schneider, and E. Farri. 2018. “The 5 Things Your AI Unit Needs to Do.” Harvard Business Review. Accessed November 15, 2023. https://hbr.org/2018/01/the-5-things-your-ai-unit-needs-to-do.
   Google Scholar
• Ekuma, K. 2023. “Artificial Intelligence and Automation in Human Resource Development: A Systematic Review.” Human Resource Development Review 00 (0): 1–31. https://doi.org/10.1177/15344843231224009.
   Google Scholar
• Farias, G., and A. Varma. 2000. “Integrating Job Characteristics, Sociotechnical Systems and Reengineering: Presenting a Unified Approach to Work and Organization Design.” Organization Development Journal 18 (3): 1–11.
   Google Scholar
• Feffer, M. 2023. “HR Sees Technology As One Solution to Rising Costs.” HCM Technology Report. March 16. https://www.hcmtechnologyreport.com/hr-sees-technology-as-one-solution-to-rising-costs/.
   Google Scholar
• Gartner. 2023. “Gartner Says CIOs Must Prioritize Their AI Ambition and AI-Ready Scenarios for Next 12-24 Months.” https://www.gartner.com/en/newsroom/press-releases/2023-10-16-gartner-says-cios-must-prioritize-their-ai-ambition-and-ai-ready-scenarios-for-next-12-24-months.
   Google Scholar
• Gibson, D. E. 2004. “Role Models in Career Development: New Directions for Theory and Research.” Journal of Vocational Behavior 65 (1): 134–156.
   Web of Science ®Google Scholar
• Glikson, E., and A. W. Woolley. 2020. “Human Trust in Artificial Intelligence: Review of Empirical Research.” Academy of Management Annals 14 (2): 627–660. https://doi.org/10.5465/annals.2018.0057.
   Web of Science ®Google Scholar
• Graßmann, C., and C. C. Schermuly. 2021. “Coaching with Artificial Intelligence: Concepts and Capabilities.” Human Resource Development Review 20 (1): 106–126. https://doi.org/10.1177/1534484320982891.
   Web of Science ®Google Scholar
• Han, S. H., D. Hrubec, and S. H. Lee. 2014. “Changes of HRD Competencies Driven by Technology.” Proceedings of the 2014 Academy of Human Resource Development in the Americas, Houston, Texas.
   Google Scholar
• Harrison, P., L. Nichol, and J. Gold. 2020. “Redefining HRD Roles and Practice in the Machine Learning Revolution.” In The Future of HRD, Volume I, Innovation and Technology, edited by M. Loon, J. Steward, and S. Nachmias, 143–166. Switzerland: AG. Palgrave Macmillan. https://eprints.leedsbeckett.ac.uk/id/eprint/7285/1/RedefiningHRDRolesAndPracticeInTheMachineLearningRevolutionAM-GOLD.pdf.
   Google Scholar
• Heinlein, M., and N. Huchler. 2023. “Artificial Intelligence in the Practice of Work: A New Way of Standardising or a Means to Maintain Complexity?” Work Organisation, Labour and Globalisation 17 (1): 34–60. https://doi.org/10.13169/workorgalaboglob.17.1.0034.
   Google Scholar
• Høyland, S. A., K. A. Holte, L. J. Gressgård, K. Hansen, and A. Solberg. 2019. “Exploring Multiple Working Arrangements in Norwegian Engineering, Procurement, and Construction Industry from a Middle Manager and Supervisor Perspective: A Sociotechnical System Perspective.” Applied Ergonomics 76 (2): 73–81. https://doi.org/10.1016/j.apergo.2018.12.005.
   PubMedGoogle Scholar
• Hughes, C., L. Robert, K. Frady, and A. Arroyos. 2019. “Artificial Intelligence, Employee Engagement, Fairness, and Job Outcomes.” In Managing Technology and Middle- and Low-Skilled Employees (The Changing Context of Managing People), 61–68. Emerald Publishing Limited. https://doi.org/10.1108/978-1-78973-077-720191005.
   Google Scholar
• Humphrey, S. E., J. D. Nahrgang, and F. P. Morgeson. 2007. “Integrating Motivational, Social, and Contextual Work Design Features: A Meta-Analytic Summary and Theoretical Extension of the Work Design Literature.” Journal of Applied Psychology 92 (5): 1332–1356. https://doi.org/10.1037/0021-9010.92.5.1332.
   PubMed Web of Science ®Google Scholar
• Jarrahi, M. H. 2018. “Artificial Intelligence and the Future of Work: Human-AI Symbiosis in Organizational Decision Making.” Business Horizons 61 (4): 577–586. https://doi.org/10.1016/j.bushor.2018.03.007.
   Web of Science ®Google Scholar
• Kim, S. 2022. “Working with Robots: Human Resource Development Considerations in Human-Robot Interaction.” Human Resource Development Review 21 (1): 48–74. https://doi.org/10.1177/15344843211068810.
   Web of Science ®Google Scholar
• Kochhar, R. 2023. Which U.S. Workers Are More Exposed to AI on Their Jobs? Pew Research Center. https://www.pewresearch.org/social-trends/2023/07/26/which-u-s-workers-are-more-exposed-to-ai-on-their-jobs/.
   Google Scholar
• Levine, J. 2022. “Combining Intelligence: How People and AI Can Collaborate.” Forbes Online. https://www.forbes.com/sites/forbesbusinesscouncil/2022/04/26/combining-intelligence-how-people-and-ai-can-collaborate/.
   Google Scholar
• Lim, W. M., A. Gunasekara, J. L. Pallant, J. I. Pallant, and E. Pechenkina. 2023. “Generative AI and the Future of Education: Ragnarök or Reformation? A Paradoxical Perspective from Management Educators.” The International Journal of Management Education 21 (2): 100790. https://doi.org/10.1016/j.ijme.2023.100790.
   Web of Science ®Google Scholar
• Liu, B., S. Mazumder, E. Robertson, and S. Grigsby. 2023. “AI Autonomy: Self-Initiated Open-World Continual Learning and Adaptation.” AI Magazine, May 21, 2023. https://doi.org/10.1002/aaai.12087.
   Google Scholar
• Makarius, E. E., D. Mukherjee, J. D. Fox, and A. K. Fox. 2020. “Rising with the Machines: A Sociotechnical Framework for Bringing Artificial Intelligence into the Organization.” Journal of Business Research 120 (3): 262–273. https://doi.org/10.1016/j.jbusres.2020.07.045.
   Google Scholar
• Meinhart, W. A. 1966. “Artificial Intelligence, Computer Simulation of Human Cognitive and Social Processes, and Management Thought.” Academy of Management Journal 9 (4): 294–307. https://doi.org/10.2307/254948.
   Web of Science ®Google Scholar
• Min, J., J. Lee, S. Ryu, and H. Lee. 2022. “The Effects of Interaction Between Team Climates and KMS Value Perception on Knowledge Activities: A Multilevel Socio‑Technical Systems Approach.” Information Technology and Management 23 (1): 1–21. https://doi.org/10.1007/s10799-021-00337-5.
   Web of Science ®Google Scholar
• Morgeson, F. P., and S. E. Humphrey. 2006. “The Work Design Questionnaire (WDQ): Developing and Validating a Comprehensive Measure for Assessing Job Design and the Nature of Work.” Journal of Applied Psychology 91 (6): 1321–1239. https://doi.org/10.1037/0021-9010.91.6.1321.
   PubMed Web of Science ®Google Scholar
• Morris, M. R., N. Fiedel, T. Warkentin, A. Dafoe, A. Faust, C. Farabet, and S. Legg. 2023. “Levels of AGI: Operationalizing Progress on the Path to AGI.” ArXiv. /abs/2311.02462. https://doi.org/10.48550/arXiv.2311.02462.
   Google Scholar
• Mulder, R. H., and P. Beer. 2020. “The Effects of New Technologies at Work on Work Outcomes and the Implications for Human Resource Development.” In The Future of HRD, Volume I, Innovation and Technology, edited by M. Loon, J. Steward, and S. Nachmias, 13–51. Switzerland AG: Palgrave Macmillan.
   Google Scholar
• Okolo, D., S. Kamarudin, and U. N. U. Ahmad. 2019. “Employing the Sociotechnical System Theory of Job Design for Technostress Intervention: An Integration of Technological and Social Job Characteristics.” Change Management 19 (1): 11–23. https://doi.org/10.18848/2327-798X/CGP/v19i01/11-23.
   Google Scholar
• Oldridge, L. 2020. “Technological Innovations in Care and Implications for Human Resource Development.” In The Future of HRD, Volume I, Innovation and Technology, edited by M. Loon, J. Steward, and S. Nachmias, 193–210. Switzerland AG: Palgrave Macmillan.
   Google Scholar
• Patel, B. N., L. Rosenberg, G. Willcox, D. Baltaxe, M. Lyons, J. Irvin, P. Rajpurkar, et al. 2019. “Human–Machine Partnership with Artificial Intelligence for Chest Radiograph Diagnosis.” NPJ Digital Medicine 2 (1): 111. https://doi.org/10.1038/s41746-019-0189-7.
   PubMedGoogle Scholar
• Pearce, C. L., J. A. Conger, and E. A. Locke. 2008. “Shared Leadership Theory.” The Leadership Quarterly 19 (5): 622–628. https://doi.org/10.1016/j.leaqua.2008.07.005.
   Web of Science ®Google Scholar
• Pietronudo, M. C., G. Croidieu, and F. Schiavone. 2022. “A Solution Looking for Problems? A Systematic Literature Review of the Rationalizing Influence of Artificial Intelligence on Decision-Making in Innovation Management.” Technological Forecasting and Social Change 182 (2): 1218–1228. https://doi.org/10.1016/j.techfore.2022.121828.
   Google Scholar
• Raisch, S., and S. Krakowski. 2021. “Artificial Intelligence and Management: The Automation–Augmentation Paradox.” Academy of Management Review 46 (1): 192–210. https://doi.org/10.5465/amr.2018.0072.
   Web of Science ®Google Scholar
• Rotatori, D., E. J. Lee, and S. Sleeva. 2021. “The Evolution of the Workforce During the Fourth Industrial Revolution.” Human Resource Development International 24 (1): 92–103. https://doi.org/10.1080/13678868.2020.1767453.
   Web of Science ®Google Scholar
• Satori, L., and A. Theodorou. 2022. “A Sociotechnical Perspective for the Future of AI: Narratives, Inequalities, and Human Control.” Ethics and Information Technology 24 (4): 1–22. https://doi.org/10.1007/s10676-022-09624-3.
   Google Scholar
• Siruri, M. A., and S. M. A. Muathe. 2014. “A Critical Review of Literature on Job Designs in Sociotechnical Systems.” Global Journal of Commerce and Management Perspective 3 (6): 44–49.
   Google Scholar
• Sturm, T., J. P. Gerlach, L. Pumplun, N. Mesbah, F. Peters, C. Tauchert, N. Nan, and P. Buxmann. 2021. “Coordinating Human and Machine Learning for Effective Organization Learning.” MIS Quarterly 45 (3): 3) pp.1581–1602. https://doi.org/10.25300/MISQ/2021/16543.
   Web of Science ®Google Scholar
• Su, Z., G. Togay, and A. M. Coté. 2021. “Artificial Intelligence: A Destructive and Yet Creative Force in the Skilled Labour Market.” Human Resource Development International 24 (3): 341–352. https://doi.org/10.1080/13678868.2020.1818513.
   Web of Science ®Google Scholar
• Swanson, R. A. 2001. “Human Resource Development and Its Underlying Theory.” Human Resource Development International 4 (3): 299–312. https://doi.org/10.1080/13678860110059311.
   Google Scholar
• Thite, M. 2022. “Digital Human Resource Development: Where Are We? Where Should We Go and How Do We Go There?” Human Resource Development International 25 (1): 87–103. https://doi.org/10.1080/13678868.2020.1842982.
   Web of Science ®Google Scholar
• Torraco, R. J., and H. Lundgren. 2020. “What HRD Is Doing-What HRD Should Be Doing: The Case for Transforming HRD.” Human Resource Development Review 19 (1): 39–65. https://doi.org/10.1177/1534484319877058.
   Web of Science ®Google Scholar
• Watkins, K. 2000. “Aims, Roles and Structures for Human Resource Development.” Advances in Developing Human Resources 2 (3): 54–59. https://doi.org/10.1177/152342230000200308.
   Google Scholar
• Whitehouse. 2022. The Impact of Artificial Intelligence on the Future of Workforces in the European Union and the United States of America. https://www.whitehouse.gov/wp-content/uploads/2022/12/TTC-EC-CEA-AI-Report-12052022-1.pdf.
   Google Scholar
• Williams, M. D., N. P. Rana, and Y. K. Dwivedi. 2015. “The Unified Theory of Acceptance and Use of Technology (UTAUT): A Literature Review.” Journal of Enterprise Information Management 28 (3): 443–488. https://doi.org/10.1108/JEIM-09-2014-0088.
   Web of Science ®Google Scholar
• Wilson, H., M. P. Tucker, C. Hannibal, and Z. Qu. 2020. “Learning Together, Learning Apart: Integrated Action Learning Through a Socio-Technical Systems Lens.” Action Learning: Research and Practice 18 (1): 5–19. https://doi.org/10.1080/14767333.2020.1843403.
   Web of Science ®Google Scholar
• Yorks, L., D. Rotatori, S. Sung, and S. Justice. 2020. “Workplace Reflection in the Age of AI: Materiality, Technology, and Machines.” Advances in Developing Human Resources 22 (3): 308–319. https://doi.org/10.1177/1523422320927299.
   Web of Science ®Google Scholar
• Yu, X., S. Xu, and M. Ashton. 2023. “Antecedents and Outcomes of Artificial Intelligence Adoption and Application in the Workplace: The Socio-Technical System Theory Perspective.” Information Technology & People 36 (1): 454–474. https://doi.org/10.1108/ITP-04-2021-0254.
   Web of Science ®Google Scholar
• Zou, J., and L. Schiebinger. 2018. “AI Can Be Sexist and Racist — It’s Time to Make it Fair.” Nature 559: 324–326. https://doi.org/10.1038/d41586-018-05707-8.
   PubMedGoogle Scholar