Evidence map›Paper›PMID 41001915›Full record

ArticleHealth promotion international2025

Towards a digital planetary health perspective: generative AI and the digital determinants of health.

Deborah Lupton

Abstract read
In one paragraph

Article in Health promotion international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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

1 author.

Deborah LuptonVitalities Lab, Centre for Social Research in Health, Social Policy Research Centre, ARC Centre for Automated Decision-Making and Society, Goodsell Building, University of New South Wales (UNSW) Sydney, Kensington, NSW, 2052, Australia.ORCID 0000-0003-2658-4430

Funding

Australian Research Council Centre of Excellence for Automated Decision-Making and Society CE200100005
6 · The paper itself

Abstract

The digital determinants of health have recently attracted attention in the medical and public health literature, but the environmental aspects of these determinants have rarely been considered. This Perspectives article calls for applying a planetary health lens to the digital determinants of health, with a focus on the impacts of novel generative AI technologies on the natural world. The argument is founded on the principle that human and planetary health are intertwined and that digital technologies such as generative AI affect the health of both humans and the other living things in ecosystems. The article discusses proposals of how generative AI tools can contribute to action on the climate, loss of biodiversity and pollution crises but also highlights how the expansion of generative AI infrastructure and operation has exacerbated the problems of e-waste, greenhouse gas emissions and major burdens on energy and water resources. It is argued that for progress to be made in improving human and planetary health, those working in health promotion and other public health domains must acknowledge that human and planetary health are interdependent, so that we can refer to the 'digital determinants of human and planetary health'. The article highlights this interdependence and the importance of fighting for multispecies justice and the rights of nature to promote the mutual flourishing of humans and the natural world. Actions are proposed that can be taken at the organization and community level to make visible and counter the impacts of generative AI on human and planetary health.

Indexed as

Artificial IntelligenceDigital TechnologyGlobal HealthPublic HealthEcosystemHumansdeterminants of healthdigital healthenvironmental healthgenerative AImultispecies justiceplanetary healthsocial justice

Identifiers

PMID41001915
PMCPMC12464675

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.