Wales Study Identifies ML Adoption Barriers
Researchers conducted an online survey in Wales from December 4, 2024, to March 4, 2025, collecting responses from 309 participants (179 public, 130 health professionals) to identify end-user barriers and facilitators to ML in health care. Respondents prioritized evidence of effectiveness and maintaining human control, with skeptical participants emphasizing autonomy. The study recommends transparent, ongoing evaluations and preserving clinician–patient contact while automating limited tasks.
Key Points
- 1Found 309 respondents; 209 supportive, 31 opposed, 69 uncertain about health care AI
- 2Highlighted priority for evidence of effectiveness and human control over automated processes
- 3Advise developers to provide transparent evaluations and preserve clinician oversight in deployments
Scoring Rationale
Relevant, peer-reviewed regional survey offering actionable implementation guidance, limited by Wales-specific sample and moderate novelty.
Sources
Public references used for this report.
Practice with real Health & Insurance data
90 SQL & Python problems · 15 industry datasets
250 free problems · No credit card
See all Health & Insurance problems
