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

Frank Goethals (IESEG School of Management, Lille, France) (LEM-CNRS UMR 9221, Lille, France)
Jennifer L. Ziegelmayer (IESEG School of Management, Lille, France)

Information Technology & People

ISSN: 0959-3845

Article publication date: 15 January 2021

Issue publication date: 17 January 2022

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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.

Keywords

Citation

Goethals, F. and Ziegelmayer, J.L. (2022), "Anxiety buffers and the threat of extreme automation: a terror management theory perspective", Information Technology & People, Vol. 35 No. 1, pp. 96-118. https://doi.org/10.1108/ITP-06-2019-0304

Publisher

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Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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