Evidence map›Paper›PMID 35994331›Full record

ArticleJournal of medical Internet research2022

The Adoption of Artificial Intelligence in Health Care and Social Services in Australia: Findings From a Methodologically Innovative National Survey of Values and Attitudes (the AVA-AI Study).

Sebastian Isbanner, Pauline O'Shaughnessy, David Steel, Scarlet Wilcock, Stacy Carter

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.7field-weighted citation impact, top 9% of its field
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

14 citing papers in PubMed, 44 citations in OpenAlex.

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  7. Understanding Public Judgements on Artificial Intelligence in Healthcare: Dialogue Group Findings From Australia.Health expectations : an international journal of public participation in health care and health policy · 2025
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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

5 authors at 3 institutions in 1 country.

Sebastian IsbannerSocial Marketing @ Griffith, Griffith Business School, Griffith University, Brisbane, Australia.ORCID 0000-0001-5842-2407
Pauline O'ShaughnessySchool of Mathematics and Applied Statistics, Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, Australia.ORCID 0000-0002-4741-3326
David SteelSchool of Mathematics and Applied Statistics, Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, Australia.ORCID 0000-0002-3137-9952
Scarlet WilcockAustralian Research Council Centre of Excellence for Automated Decision-Making and Society, The University of Sydney Law School, The University of Sydney, Sydney, Australia.ORCID 0000-0002-0011-1363
Stacy CarterAustralian Centre for Health Engagement Evidence and Values, Faculty of the Arts, Social Sciences and Humanities, University of Wollongong, Wollongong, Australia.ORCID 0000-0003-2617-8694
University of Wollongong · AUGriffith University · AUThe University of Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) for use in health care and social services is rapidly developing, but this has significant ethical, legal, and social implications. Theoretical and conceptual research in AI ethics needs to be complemented with empirical research to understand the values and judgments of members of the public, who will be the ultimate recipients of AI-enabled services.

objectiveThe aim of the Australian Values and Attitudes on AI (AVA-AI) study was to assess and compare Australians' general and particular judgments regarding the use of AI, compare Australians' judgments regarding different health care and social service applications of AI, and determine the attributes of health care and social service AI systems that Australians consider most important.

methodsWe conducted a survey of the Australian population using an innovative sampling and weighting methodology involving 2 sample components: one from an omnibus survey using a sample selected using scientific probability sampling methods and one from a nonprobability-sampled web-based panel. The web-based panel sample was calibrated to the omnibus survey sample using behavioral, lifestyle, and sociodemographic variables. Univariate and bivariate analyses were performed.

resultsWe included weighted responses from 1950 Australians in the web-based panel along with a further 2498 responses from the omnibus survey for a subset of questions. Both weighted samples were sociodemographically well spread. An estimated 60% of Australians support the development of AI in general but, in specific health care scenarios, this diminishes to between 27% and 43% and, for social service scenarios, between 31% and 39%. Although all ethical and social dimensions of AI presented were rated as important, accuracy was consistently the most important and reducing costs the least important. Speed was also consistently lower in importance. In total, 4 in 5 Australians valued continued human contact and discretion in service provision more than any speed, accuracy, or convenience that AI systems might provide.

conclusionsThe ethical and social dimensions of AI systems matter to Australians. Most think AI systems should augment rather than replace humans in the provision of both health care and social services. Although expressing broad support for AI, people made finely tuned judgments about the acceptability of particular AI applications with different potential benefits and downsides. Further qualitative research is needed to understand the reasons underpinning these judgments. The participation of ethicists, social scientists, and the public can help guide AI development and implementation, particularly in sensitive and value-laden domains such as health care and social services.

Indexed as

Artificial IntelligenceDelivery of Health CareAttitudeAustraliaHumansSocial Workartificial intelligencebioethicsconsumer health informaticssocial valuessocial welfaresurveys and questionnaires

Identifiers

PMID35994331
PMCPMC9446139
OpenAlexW4285817122

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.