Table 1

Eight human factors and ergonomics principles for healthcare AI

Situation awareness	Design options need to consider how AI can support, rather than erode, people’s situation awareness.
Workload	The impact of AI on workload needs to be assessed because AI can both reduce as well as increase workload in certain situations.
Automation bias	Strategies need to be considered to guard against people relying uncritically on the AI, for example, the use of explanation and training.
Explanation and trust	AI applications should explain their behaviour and allow users to query it in order to reduce automation bias and to support trust.
Human–AI teaming	AI applications should be capable of good teamworking behaviours to support shared mental models and situation awareness.
Training	People require opportunities to practise and retain their skill sets when AI is introduced, and they need to have a baseline understanding of how the AI works. Attention needs to be given to the design of effective training that is accessible and flexible. Staff should be provided with protected time to undertake training during their work hours.
Relationships between people	The impact on relationships needs to be considered, for example, whether staff will be working away from the patient as more and more AI is introduced.
Ethical issues	AI in healthcare raises ethical challenges including fairness and bias in AI models, protection of privacy, respect for autonomy, realisation of benefits and minimisation of harm.