Table 1

Stakeholder perceptions of clinical AI applications

Positive perceptionsNegative perceptions
Improved diagnostic accuracy; fewer errors3 5
More efficient work flows4 5 17 18
Less time spent on administrative and other mundane tasks3 13
Synthesis of clinical information15 18
Updating of clinical records14
More time spent with patients5
Improved access to care3
Liability for AI-mediated errors3
Insufficient training and continuing professional development in AI3 5 7 8 12
Reputational loss and reduced demand for specialist opinion9 18
Potential erosion of empathetic communication with patients13 18
Risk of privacy breaches and loss of confidentiality of patient information17
Lack of proof of efficacy of AI applications in clinical settings3 29
Lack of explainability16
Second opinions to clinicians21 22 25
Improved access to care23
Dehumanisation of the clinician–patient relationship18 19
Threat to shared decision-making involving patients22
Low trustworthiness of AI advice19 20 23
Insufficient clinician and regulatory oversight21
Uncertainty around fairness and equity in treatment allocation26
Healthcare executives
Improved operational efficiency, cybersecurity, analytic capacity, cost savings27Uncertainty around patient satisfaction, access to care, improved patient outcomes27
Industry professionals
Shared many of the positive attitudes listed above27–29Limited access to high quality data for model development29
Unresolved legal liability question29
Lack of explicit and robust regulatory frameworks29
Low levels of funding for independent, investigator-led research in AI29
  • AI, artificial intelligence.