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Anxiety buffers and the threat of extreme automation: a terror management theory perspective

Author

Listed:
  • Frank Goethals

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Jennifer Ziegelmayer

Abstract

Purpose The advent of extreme automation from new technologies such as artificial intelligence portends a massive increase in unemployment. The psychological impact of this threat on the workforce is critically important. This paper aims to examine the functioning of individuals' anxiety buffers in response to this threat. Design/methodology/approach A two-stage mixed-methods design is used. In stage 1, qualitative data are gathered through semi-structured interviews. In stage 2, quantitative data are collected through two experiments to assess the psychological impact of exposure to the threat. Findings Exposure to the threat of extreme automation reduces self-esteem, faith in the worldview and attachment security. When self-esteem and attachment security are under attack, they are ineffective as anxiety buffers, and anxiety levels increase. Additionally, there is a distal effect such that during a period of distraction, the threatened anxiety buffers are reinforced and return to their normal levels. Research limitations/implications This study is limited to a homogenous culture in which work is highly salient. Future research should include other cultures, other methods of exposure and further examine the distal effects. Originality/value The study examines the previously underexplored issue of individuals' psychological response to the impending changes in the workforce because of technological advancements.

Suggested Citation

  • Frank Goethals & Jennifer Ziegelmayer, 2021. "Anxiety buffers and the threat of extreme automation: a terror management theory perspective," Post-Print hal-03267646, HAL.
  • Handle: RePEc:hal:journl:hal-03267646
    DOI: 10.1108/ITP-06-2019-0304
    as

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