Evidence map›Paper›PMID 40681611›Full record

ArticleScientific reports2025

Generative AI may create a socioeconomic tipping point through labour displacement.

Jo-An Occhipinti, William Hynes, Ante Prodan, Harris Eyre, Roy Green, Sharan Burrow, Marcel Tanner, John Buchanan, Goran Ujdur, Frederic Destrebecq and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Jo-An OcchipintiMental Wealth Initiative, Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Building M02C, Level 4, 94 Mallet Street, Camperdown, NSW, Australia. jo-an.occhipinti@sydney.edu.au.
William HynesWorld Bank, Paris, France.
Ante ProdanMental Wealth Initiative, Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Building M02C, Level 4, 94 Mallet Street, Camperdown, NSW, Australia.
Harris EyreBaker Institute for Public Policy, Rice University, Houston, USA.
Roy GreenUniversity of Technology Sydney, Sydney, Australia.
Sharan BurrowVisiting Professor in Practice, London School of Economics Grantham Institute, London, UK.
Marcel TannerSwiss Academies of Arts and Sciences, Bern, Switzerland.
John BuchananMental Wealth Initiative, Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Building M02C, Level 4, 94 Mallet Street, Camperdown, NSW, Australia.
Goran UjdurMental Wealth Initiative, Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Building M02C, Level 4, 94 Mallet Street, Camperdown, NSW, Australia.
Frederic DestrebecqEuropean Brain Council, Brussels, Belgium.
Christine SongMental Wealth Initiative, Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Building M02C, Level 4, 94 Mallet Street, Camperdown, NSW, Australia.
Steven CarnevalePoint Cypress Ventures, San Francisco, CA, USA.
Ian B HickieMental Wealth Initiative, Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Building M02C, Level 4, 94 Mallet Street, Camperdown, NSW, Australia.
Mark HeffernanSchool of Computer, Data and Mathematical Sciences, Western Sydney University, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Work is fundamental to societal prosperity and mental health, providing financial security, a sense of identity and purpose, and social integration. Job insecurity, underemployment and unemployment are well-documented risk factors for mental health issues and suicide. The emergence of generative artificial intelligence (AI) has catalysed debate on job displacement and its corollary impacts on individual and social wellbeing. Some argue that many new jobs and industries will emerge to offset the displacement, while others foresee a widespread decoupling of economic productivity from human input threatening jobs on an unprecedented scale. This study explores the conditions under which both may be true and examines the potential for a self-reinforcing cycle of recessionary pressures that would necessitate sustained government intervention to maintain job security and economic stability. A system dynamics model was developed to undertake ex ante analysis of the effect of AI-capital deepening on labour underutilisation and demand in the economy using Australian data as a case study. Results indicate that even a moderate increase in the AI-capital-to-labour ratio could increase labour underutilisation to double its current level, decrease per capita disposable income by 26% (95% interval, 20.6-31.8%), and decrease the consumption index by 21% (95% interval, 13.6-28.3%) by mid-2050. To prevent a reduction in per capita disposable income due to the estimated increase in underutilization, at least a 10.8-fold increase in the new job creation rate would be necessary. Results demonstrate the feasibility of an AI-capital-to-labour ratio threshold beyond which even high rates of new job creation cannot prevent declines in consumption. The precise threshold will vary across economies, emphasizing the urgent need for empirical research tailored to specific contexts. This study underscores the need for cross-sectoral government measures to ensure a smooth transition to an AI-dominated economy to safeguard the Mental Wealth of nations.

Indexed as

Artificial IntelligenceEmploymentAustraliaHumansIncomeMental HealthSocioeconomic FactorsUnemploymentArtificial intelligenceEconomic policyRecessionSystem dynamicsWellbeing

Identifiers

PMID40681611
PMCPMC12274502

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.