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Psychological reactions to human versus robotic job replacement

Author

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  • Armin Granulo

    (Technical University of Munich)

  • Christoph Fuchs

    (Technical University of Munich)

  • Stefano Puntoni

    (Erasmus University Rotterdam)

Abstract

Advances in robotics and artificial intelligence are increasingly enabling organizations to replace humans with intelligent machines and algorithms1. Forecasts predict that, in the coming years, these new technologies will affect millions of workers in a wide range of occupations, replacing human workers in numerous tasks2,3, but potentially also in whole occupations1,4,5. Despite the intense debate about these developments in economics, sociology and other social sciences, research has not examined how people react to the technological replacement of human labour. We begin to address this gap by examining the psychology of technological replacement. Our investigation reveals that people tend to prefer workers to be replaced by other human workers (versus robots); however, paradoxically, this preference reverses when people consider the prospect of their own job loss. We further demonstrate that this preference reversal occurs because being replaced by machines, robots or software (versus other humans) is associated with reduced self-threat. In contrast, being replaced by robots is associated with a greater perceived threat to one’s economic future. These findings suggest that technological replacement of human labour has unique psychological consequences that should be taken into account by policy measures (for example, appropriately tailoring support programmes for the unemployed).

Suggested Citation

  • Armin Granulo & Christoph Fuchs & Stefano Puntoni, 2019. "Psychological reactions to human versus robotic job replacement," Nature Human Behaviour, Nature, vol. 3(10), pages 1062-1069, October.
  • Handle: RePEc:nat:nathum:v:3:y:2019:i:10:d:10.1038_s41562-019-0670-y
    DOI: 10.1038/s41562-019-0670-y
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    Cited by:

    1. Volkmar, Gioia & Fischer, Peter M. & Reinecke, Sven, 2022. "Artificial Intelligence and Machine Learning: Exploring drivers, barriers, and future developments in marketing management," Journal of Business Research, Elsevier, vol. 149(C), pages 599-614.
    2. Brice Corgnet, 2023. "An Experimental Test of Algorithmic Dismissals," Working Papers 2302, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    3. de Bellis, Emanuel & Venkataramani Johar, Gita, 2020. "Autonomous Shopping Systems: Identifying and Overcoming Barriers to Consumer Adoption," Journal of Retailing, Elsevier, vol. 96(1), pages 74-87.
    4. Chan, Nathan W. & Wolk, Leonard, 2020. "Cost-effective giving with multiple public goods," Journal of Economic Behavior & Organization, Elsevier, vol. 173(C), pages 130-145.
    5. Daniel Belanche & Luis V. Casaló & Carlos Flavián & Alfredo Pérez-Rueda, 2021. "The role of customers in the gig economy: how perceptions of working conditions and service quality influence the use and recommendation of food delivery services," Service Business, Springer;Pan-Pacific Business Association, vol. 15(1), pages 45-75, March.
    6. Dario Krpan & Jonathan E. Booth & Andreea Damien, 2023. "The positive–negative–competence (PNC) model of psychological responses to representations of robots," Nature Human Behaviour, Nature, vol. 7(11), pages 1933-1954, November.
    7. Amy Van Looy, 2022. "Employees’ attitudes towards intelligent robots: a dilemma analysis," Information Systems and e-Business Management, Springer, vol. 20(3), pages 371-408, September.
    8. Prem Borle & Kathrin Reichel & Susanne Voelter-Mahlknecht, 2021. "Is There a Sampling Bias in Research on Work-Related Technostress? A Systematic Review of Occupational Exposure to Technostress and the Role of Socioeconomic Position," IJERPH, MDPI, vol. 18(4), pages 1-22, February.
    9. Reich, Taly & Fulmer, Alexander G. & Dhar, Ravi, 2022. "In the face of self-threat: Why ambivalence heightens people’s willingness to act," Organizational Behavior and Human Decision Processes, Elsevier, vol. 168(C).

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