1,254
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Are we ahead of the trend or just following? The role of work and organizational psychology in shaping emerging technologies at work

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 120-129 | Received 10 Dec 2023, Accepted 22 Feb 2024, Published online: 23 Mar 2024

References

  • Anthony, C., Bechky, B. A., & Fayard, A.-L. (2023). “Collaborating” with AI: Taking a system view to explore the future of work. Organization Science, 34(5), 1672–1694. https://doi.org/10.1287/orsc.2022.1651
  • Avison, D., Baskerville, R., & Myers, M. (2001). Controlling action research projects. Information Technology & People, 14(1), 28–45. https://doi.org/10.1108/09593840110384762
  • Bainbridge, L. (1983). Ironies of automation. In G. Johannsen & J. E. Rijnsdorp (Eds.), Analysis, design and evaluation of man–machine systems (pp. 129–135). Pergamon. https://doi.org/10.1016/B978-0-08-029348-6.50026-9
  • Bankins, S., Ocampo, A. C., Marrone, M., Restubog, S. L. D., & Woo, S. E. (2023). A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice. Journal of Organizational Behavior, 45(2), 159–182. job.2735. https://doi.org/10.1002/job.2735
  • Baskerville, R. L., & Wood-Harper, A. T. (2016). A critical perspective on action research as a method for information systems research. In L. P. Willcocks, C. Sauer, & M. C. Lacity (Eds.), Enacting research methods in information systems: Volume 2 (pp. 169–190). Springer International Publishing. https://doi.org/10.1007/978-3-319-29269-4_7
  • Beer, P., & Mulder, R. H. (2020). The effects of technological developments on work and their implications for continuous vocational education and training: A systematic review. Frontiers in Psychology, 11, 918. https://doi.org/10.3389/fpsyg.2020.00918
  • Berg, J. M., Raj, M., & Seamans, R. (2023). Capturing Value from Artificial Intelligence. Academy of Management Discoveries, 9(4), 424–428. https://doi.org/10.5465/amd.2023.0106
  • Berkers, H. A., Rispens, S., & Le Blanc, P. M. (2023). The role of robotization in work design: A comparative case study among logistic warehouses. The International Journal of Human Resource Management, 34(9), 1852–1875. https://doi.org/10.1080/09585192.2022.2043925
  • Burrell, J. (2016). How the machine ‘thinks’: Understanding opacity in machine learning algorithms. Big Data & Society, 3(1), 205395171562251. https://doi.org/10.1177/2053951715622512
  • Chhillar, D., & Aguilera, R. V. (2022). An eye for artificial intelligence: Insights into the governance of artificial intelligence and vision for future research. Business & Society, 61(5), 1197–1241. https://doi.org/10.1177/00076503221080959
  • Clegg, C. W. (2000). Sociotechnical principles for system design. Applied Ergonomics, 31(5), 463–477. https://doi.org/10.1016/S0003-6870(00)00009-0
  • Colquitt, J. A., Greenberg, J., & Zapata-Phelan, C. P. (2005). What is organizational justice? A historical overview. In J. Greenberg,& J. A. Colquitt (Eds.), Handbook of organizational justice. Lawrence Erlbaum Associates Publishers.
  • de Winter, J. C. F., & Dodou, D. (2014). Why the Fitts list has persisted throughout the history of function allocation. Cognition, Technology & Work, 16(1), 1–11. https://doi.org/10.1007/s10111-011-0188-1
  • Emery, F. E. (1959). Characteristics of socio-technical systems: A critical review of theories and facts about the effects of technological change on the internal structure of work organisations; with special reference to the effects of higher mechanisation and automation. Tavistock Institute of Human Relations, Human Resources Centre.
  • Endsley, M. R. (1995). Toward a theory of situation awareness in dynamic systems. Human Factors: The Journal of the Human Factors & Ergonomics Society, 37(1), 32–64. https://doi.org/10.1518/001872095779049543
  • Endsley, M. R. (2017). From here to autonomy: Lessons learned from human–automation research. Human Factors: The Journal of the Human Factors & Ergonomics Society, 59(1), 5–27. https://doi.org/10.1177/0018720816681350
  • Endsley, M. R. (2023). Supporting human-AI teams: Transparency, explainability, and situation awareness. Computers in Human Behavior, 140, 107574. https://doi.org/10.1016/j.chb.2022.107574
  • Fitts, P. M. (1951). Human engineering for an effective air-navigation and traffic-control system. National Research Council.
  • Gasteiger, N., Hellou, M., & Ahn, H. S. (2023). Factors for personalization and localization to optimize Human–robot interaction: A literature review. International Journal of Social Robotics, 15(4), 689–701. https://doi.org/10.1007/s12369-021-00811-8
  • Grote, G. (2023). Shaping the development and use of artificial intelligence: How human factors and ergonomics expertise can become more pertinent. Ergonomics, 66(11), 1702–1710. https://doi.org/10.1080/00140139.2023.2278408
  • Grote, G., Ryser, C., Wāler, T., Windischer, A., & Weik, S. (2000). KOMPASS: A method for complementary function allocation in automated work systems. International Journal of Human-Computer Studies, 52(2), 267–287. https://doi.org/10.1006/ijhc.1999.0289
  • Hacker, W. (2003). Action regulation theory: A practical tool for the design of modern work processes? European Journal of Work and Organizational Psychology, 12(2), 105–130. https://doi.org/10.1080/13594320344000075
  • Hacker, W. (2022). Arbeitsgestaltung bei Digitalisierung: Merkmale menschzentrierter Gestaltung informationsverarbeitender Erwerbsarbeit. Zeitschrift Für Arbeitswissenschaft, 76(1), 90–98. https://doi.org/10.1007/s41449-022-00302-0
  • Hancock, P. A., & Scallen, S. F. (1996). The future of function allocation. Ergonomics in Design: The Quarterly of Human Factors Applications, 4(4), 24–29. https://doi.org/10.1177/106480469600400406
  • Hoff, K. A., & Bashir, M. (2015). Trust in automation: Integrating empirical evidence on factors that influence trust. Human Factors: The Journal of the Human Factors & Ergonomics Society, 57(3), 407–434. https://doi.org/10.1177/0018720814547570
  • Holman, D. (2013). Job types and job quality in Europe. Human Relations, 66(4), 475–502. https://doi.org/10.1177/0018726712456407
  • Humphrey, S. E., Nahrgang, J. D., & Morgeson, F. P. (2007). Integrating motivational, social, and contextual work design features: A meta-analytic summary and theoretical extension of the work design literature. The Journal of Applied Psychology, 92(5), 1332–1356. https://doi.org/10.1037/0021-9010.92.5.1332
  • Johnson, L. F., Smith, R. S., Smythe, J. T., & Varon, R. K. (2009). Challenge-based learning: An approach for our time. The New Media Consortium. https://www.learntechlib.org/p/182083/
  • Kaber, D. B., & Endsley, M. R. (2004). The effects of level of automation and adaptive automation on human performance, situation awareness and workload in a dynamic control task. Theoretical Issues in Ergonomics Science, 5(2), 113–153. https://doi.org/10.1080/1463922021000054335
  • Keegan, A., Brandl, J., & Aust, I. (2019). Handling tensions in human resource management: Insights from paradox theory. German Journal of Human Resource Management: Zeitschrift für Personalforschung, 33(2), 79–95. https://doi.org/10.1177/2397002218810312
  • Landers, R. N., & Marin, S. (2021). Theory and technology in organizational psychology: A review of technology integration paradigms and their effects on the validity of theory. Annual Review of Organizational Psychology and Organizational Behavior, 8(1), 235–258. https://doi.org/10.1146/annurev-orgpsych-012420-060843
  • Langer, M., & König, C. J. (2021). Introducing a multi-stakeholder perspective on opacity, transparency and strategies to reduce opacity in algorithm-based human resource management. Human Resource Management Review, 33(1), 100881. https://doi.org/10.1016/j.hrmr.2021.100881
  • Langer, M., & König, C. J. (2023). Introducing a multi-stakeholder perspective on opacity, transparency and strategies to reduce opacity in algorithm-based human resource management. Human Resource Management Review, 33(1), 100881. https://doi.org/10.1016/j.hrmr.2021.100881
  • Langer, M., König, C. J., & Busch, V. (2021). Changing the means of managerial work: Effects of automated decision support systems on personnel selection tasks. Journal of Business and Psychology, 36(5), 751–769. https://doi.org/10.1007/s10869-020-09711-6
  • Langer, M., & Landers, R. N. (2021). The future of artificial intelligence at work: A review on effects of decision automation and augmentation on workers targeted by algorithms and third-party observers. Computers in Human Behavior, 123, 106878. https://doi.org/10.1016/j.chb.2021.106878
  • Langer, M., Oster, D., Speith, T., Hermanns, H., Kästner, L., Schmidt, E., Sesing, A., & Baum, K. (2021). What do we want from explainable artificial intelligence (XAI)? – a stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research. Artificial Intelligence, 296, 103473. https://doi.org/10.1016/j.artint.2021.103473
  • Larson, L., & DeChurch, L. (2020). Leading teams in the digital age: Four perspectives on technology and what they mean for leading teams. The Leadership Quarterly, 31(1), 1–18. https://doi.org/10.1016/j.leaqua.2019.101377
  • Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors: The Journal of the Human Factors & Ergonomics Society, 46(1), 50–80. https://doi.org/10.1518/hfes.46.1.50.30392
  • Makarius, E. E., Mukherjee, D., Fox, J. D., & Fox, A. K. (2020). Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization. Journal of Business Research, 120, 262–273. https://doi.org/10.1016/j.jbusres.2020.07.045
  • Matza, L. S., Stewart, K. D., Lloyd, A. J., Rowen, D., & Brazier, J. E. (2021). Vignette-Based Utilities: Usefulness, Limitations, and Methodological Recommendations. Value in Health, 24(6), 812–821. https://doi.org/10.1016/j.jval.2020.12.017
  • McBride, S. E., Rogers, W. A., & Fisk, A. D. (2014). Understanding human management of automation errors. Theoretical Issues in Ergonomics Science, 15(6), 545–577. https://doi.org/10.1080/1463922X.2013.817625
  • Mitchell, S., Potash, E., Barocas, S., D’Amour, A., & Lum, K. (2021). Algorithmic fairness: Choices, assumptions, and definitions. Annual Review of Statistics and Its Application, 8(1), 141–163. https://doi.org/10.1146/annurev-statistics-042720-125902
  • Morgeson, F. P., & Campion, M. A. (2003). Work Design. In I. B. Weiner (Ed.), Handbook of psychology (1st ed., pp. 423–452). Wiley. https://doi.org/10.1002/0471264385.wei1217
  • Mosier, K. L., Skitka, L. J., Burdick, M. D., & Heers, S. T. (1996). Automation Bias, Accountability, and Verification Behaviors. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 40(4), 204–208. https://doi.org/10.1177/154193129604000413
  • Mumford, E. (1983). Participative systems design: Practice and – ProQuest. Journal of Occupational Behaviour, 4(1), 47–57.
  • Nelson, A. J., & Irwin, J. (2014). ‘Defining what we do – all over again’: Occupational identity, technological change, and the Librarian/Internet-search relationship. The Academy of Management Journal, 57(3), 892–928. https://doi.org/10.5465/amj.2012.0201
  • Norcross, J. C., Hailstorks, R., Aiken, L. S., Pfund, R. A., Stamm, K. E., & Christidis, P. (2016). Undergraduate study in psychology: Curriculum and assessment. American Psychologist, 71(2), 89–101. https://doi.org/10.1037/a0040095
  • Parasuraman, R., & Manzey, D. H. (2010). Complacency and bias in human use of automation: An attentional integration. Human Factors: The Journal of the Human Factors & Ergonomics Society, 52(3), 381–410. https://doi.org/10.1177/0018720810376055
  • Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000). A model for types and levels of human interaction with automation. IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, 30(3), 286–297. https://doi.org/10.1109/3468.844354
  • Parker, S. K., Andrei, D. M., & Van den Broeck, A. (2019). Poor work design begets poor work design: Capacity and willingness antecedents of individual work design behavior. The Journal of Applied Psychology, 104(7), 907–928. https://doi.org/10.1037/apl0000383
  • Parker, S. K., & Grote, G. (2022). Automation, algorithms, and beyond: Why work design matters more than ever in a digital world. Applied Psychology, 71(4), 1171–1204. https://doi.org/10.1111/apps.12241
  • Parker, S. K., Morgeson, F. P., & Johns, G. (2017). One hundred years of work design research: Looking back and looking forward. The Journal of Applied Psychology, 102(3), 403–420. https://doi.org/10.1037/apl0000106
  • Parker, S. K., Van Den Broeck, A., & Holman, D. (2017). Work design influences: A synthesis of multilevel factors that affect the design of jobs. Academy of Management Annals, 11(1), 267–308. https://doi.org/10.5465/annals.2014.0054
  • Phillips, E., Ososky, S., Grove, J., & Jentsch, F. (2011). From tools to teammates: Toward the development of appropriate mental models for intelligent robots. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 55(1), 1491–1495. https://doi.org/10.1177/1071181311551310
  • Reverberi, C., Rigon, T., Solari, A., Hassan, C., Cherubini, P., & Cherubini, A. (2022). Experimental evidence of effective human–AI collaboration in medical decision-making. Scientific Reports, 12(1), 14952. https://doi.org/10.1038/s41598-022-18751-2
  • Richter, A., Heinrich, P., Stocker, A., & Schwabe, G. (2018). Digital work design: The interplay of human and computer in future work practices as an interdisciplinary (grand) challenge. Business & Information Systems Engineering, 60(3), 259–264. https://doi.org/10.1007/s12599-018-0534-4
  • Seeber, I., Waizenegger, L., Seidel, S., Morana, S., Benbasat, I., & Lowry, P. B. (2020). Collaborating with technology-based autonomous agents: Issues and research opportunities. Internet Research, 30(1), 1–18. https://doi.org/10.1108/INTR-12-2019-0503
  • Simon, H. A. (1996). The sciences of the artificial (third edition ed.). MIT Press.
  • Strohmeier, S. (2009). Concepts of e-HRM consequences: A categorisation, review and suggestion. The International Journal of Human Resource Management, 20(3), 528–543. https://doi.org/10.1080/09585190802707292
  • Symon, G., & Clegg, C. (2005). Constructing identity and participation during technological change. Human Relations, 58(9), 1141–1166. https://doi.org/10.1177/0018726705058941
  • Tenenbaum, L. M. (2022, December 1). Introducing High School Students to Human Factors Engineering. https://www.apa.org/ed/precollege/psychology-teacher-network/introductory-psychology/human-factors-engineering
  • Trist, E. L. (1981). The evolution of socio-technical systems: A conceptual framework and an action research program. Ontario Ministry of Labour, Ontario Quality of Working Life Centre.
  • Trist, E. L., & Bamforth, K. W. (1951). Some social and psychological consequences of the longwall method of coal-getting: An examination of the psychological situation and defences of a work group in relation to the social structure and technological content of the work system. Human Relations, 4(1), 3–38. https://doi.org/10.1177/001872675100400101
  • Tyre, M. J., & Orlikowski, W. J. (1994). Windows of opportunity: Temporal patterns of technological adaptation in organizations. Organization Science, 5(1), 98–118. https://doi.org/10.1287/orsc.5.1.98
  • Ulfert, A.-S., Antoni, C. H., & Ellwart, T. (2022). The role of agent autonomy in using decision support systems at work. Computers in Human Behavior, 126, 106987. https://doi.org/10.1016/j.chb.2021.106987
  • Ulfert, A.-S., Georganta, E., Centeio Jorge, C., Mehrotra, S., & Tielman, M. L. (2023). Shaping a multidisciplinary understanding of team trust in human-AI teams: A theoretical framework. European Journal of Work and Organizational Psychology, 1–14. https://doi.org/10.1080/1359432X.2023.2200172
  • van Zoelen, E. M., van den Bosch, K., & Neerincx, M. (2021). Becoming team members: Identifying interaction patterns of mutual adaptation for human-robot Co-learning. Frontiers in Robotics and AI, 8, 8. https://doi.org/10.3389/frobt.2021.692811
  • Wächter, H., Modrow-Thiel, B., & Roßmann, G. (1989). Prospektive Arbeitsgestaltung – Das Verfahren ATAA. German Journal of Human Resource Management: Zeitschrift für Personalforschung, 3(4), 277–296. https://doi.org/10.1177/239700228900300402
  • Waterson, P. E., Older Gray, M. T., & Clegg, C. W. (2002). A sociotechnical method for designing work systems. Human Factors: The Journal of the Human Factors & Ergonomics Society, 44(3), 376–391. https://doi.org/10.1518/0018720024497628
  • Wolffgramm, M., Tijink Saxion, T., Disberg- Van Geloven, M., & Corporaal, S. (2021). A collaborative robot in the classroom: Designing 21st Century engineering education together. Education Theory and Practice, 21(16), 177–187.