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Artificial intelligence in healthcare: a qualitative study exploring consumer perspectives.
Vicki Hobson-Green1, Quita Olsen2, Clair Sullivan2,3
1Griffith University, Brisbane, Australia.
BMC Medical Ethics
|July 3, 2026
Summary
Healthcare consumers desire AI integration that prioritizes clear communication, equity, and human interaction. Ensuring transparency and preserving the human element are key to building trust in artificial intelligence in healthcare.
Area of Science:
- Health Informatics
- Artificial Intelligence in Medicine
- Qualitative Health Research
Background:
- Real-world adoption of artificial intelligence (AI) in healthcare is hindered by consumer acceptance uncertainties.
- Existing ethical frameworks need augmentation with consumer perspectives for value-aligned AI integration.
- Understanding healthcare consumer views is crucial for ethical AI implementation.
Purpose of the Study:
- To investigate healthcare consumers' perspectives on the integration of artificial intelligence (AI) in healthcare.
- To identify key values and preferences of consumers regarding AI in clinical settings.
Main Methods:
- Cross-sectional qualitative study utilizing online focus groups.
- Participants included adult healthcare consumers and caregivers in Queensland, Australia.
- Analysis employed deductive and inductive thematic analysis guided by World Health Organisation (WHO) ethical principles.
Main Results:
- Nineteen themes emerged across six WHO ethical principles regarding AI in healthcare.
- Inclusiveness, equity, and transparency, explainability, intelligibility were the most frequently discussed principles.
- Consumers emphasized the need for clear communication, equity, transparency, and maintaining human interaction in care.
Conclusions:
- Successful AI integration in healthcare hinges on sustaining consumer trust and preserving human connection.
- Findings can inform a values-based framework for safe, ethical, and consumer-centered AI implementation.
- Developing a social license is essential for guiding AI adoption in healthcare.
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