Title |
What generative AI means for trust in health communications
|
---|---|
Published in |
Journal of Communications in Healthcare, November 2023
|
DOI | 10.1080/17538068.2023.2277489 |
Pubmed ID | |
Authors |
Adam G. Dunn, Ivy Shih, Julie Ayre, Heiko Spallek |
Abstract |
ABSTRACTLarge language models are fundamental technologies used in interfaces like ChatGPT and are poised to change the way people access and make sense of health information. The speed of uptake and investment suggests that these will be transformative technologies, but it is not yet clear what the implications might be for health communications. In this viewpoint, we draw on research about the adoption of new information technologies to focus on the ways that generative artificial intelligence (AI) tools like large language models might change how health information is produced, what health information people see, how marketing and misinformation might be mixed with evidence, and what people trust. We conclude that transparency and explainability in this space must be carefully considered to avoid unanticipated consequences. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Australia | 4 | 36% |
United States | 3 | 27% |
Unknown | 4 | 36% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 45% |
Scientists | 3 | 27% |
Science communicators (journalists, bloggers, editors) | 2 | 18% |
Practitioners (doctors, other healthcare professionals) | 1 | 9% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 20 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 3 | 15% |
Unspecified | 2 | 10% |
Student > Ph. D. Student | 2 | 10% |
Student > Doctoral Student | 1 | 5% |
Other | 1 | 5% |
Other | 1 | 5% |
Unknown | 10 | 50% |
Readers by discipline | Count | As % |
---|---|---|
Unspecified | 2 | 10% |
Nursing and Health Professions | 1 | 5% |
Business, Management and Accounting | 1 | 5% |
Computer Science | 1 | 5% |
Immunology and Microbiology | 1 | 5% |
Other | 4 | 20% |
Unknown | 10 | 50% |