From AI Conundrum to Economic Security

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Authors: Harald Knudsen
Cited by: 0

Abstract

Issues of economic growth and decoupling, and of economic inequality in time and space are in chapter 13 linked to the question of employment at a time of AI-robotization and automation. While the green transition will demand more manpower, general trends of automation, and the additional impact of AI for productivity is predicted to lessen the demand for human work-power. Less demand for human work will drive bottom wages below subsistence and result in direct unemployment of both blue-collar and white-collar workers. Researchers tend to disagree about the timing and extent of AI-unemployment. Some argue that AI will generate so much economic growth, as to absorb the unemployed and eliminate the threat. The Leibnizian reductio ad absurdum form of argument is used to highlight consequences, by pointing to an extreme case, that of near full unemployment as a result of AI and automation. In the extreme case of super-high AI-assisted productivity growth, it will take enormous growth to create full employment and keep wages above subsistence. Sustained high economic growth, unless absolutely decoupled, will lead to a dramatic and unacceptable increase of the environmental burden. Decoupling at a high scale of growth will most likely be impossible, and full employment without threatening the planet will be extremely challenging, suggesting a fundamental choice between introducing some form of universal guaranteed minimum income, or the collapse of human civilization. For the presentation of solutions and hope, three metaphors are introduced in Part Three, one for top-down reforms and megaprojects, one for bottom-up popular engagement, and one for a fundamental transformative change of relations – bringing in a cause for hope.

Fields of Study & Subjects

Labor market dynamics and wage inequality Economic Theory and Policy Economic Development and Digital Transformation

Publication details

Journal / source
CRC Press eBooks
Pages
205–223
Publication date
26 February 2026
Language
EN
Document type
Book chapter