Evidence map›Paper›PMID 40550887›Full record

ArticleScientific reports2025

Artificial intelligence and the wellbeing of workers.

Osea Giuntella, Johannes Konig, Luca Stella

Abstract read
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. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

3 authors.

Osea GiuntellaDepartment of Economics, University of Pittsburgh and NBER, Pittsburgh, USA. osea.giuntella@pitt.edu.
Johannes KonigGerman Ministry of Finance, Berlin, Germany.
Luca StellaUniversity of Milan, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study explores the relationship between artificial intelligence (AI) and workers' well-being and health using longitudinal survey data from Germany (2000-2020). Using a measure of occupational exposure to AI, we explore an event study design and a difference-in-differences approach to compare AI-exposed and non-exposed workers. Before AI became widely available, there is no evidence of differential pre-trends in workers' well-being and health. We find no evidence of a sizeable negative impact of AI on workers' well-being and mental health. If anything, there is evidence of an improvement in health status and health satisfaction, which may be explained by the decline in job physical intensity. Overall, our results are consistent with the lack of negative effects of AI on the labor markets.

Indexed as

Artificial IntelligenceMental HealthOccupational ExposureOccupational HealthAdultFemaleGermanyHealth StatusHumansLongitudinal StudiesMaleMiddle AgedSurveys and QuestionnairesArtificial intelligenceFuture of workPhysical and mental healthWell-being

Identifiers

PMID40550887
PMCPMC12185714

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.