Horizon scanning

Healthcare workers’ confidence in AI

We have partnered with the NHS AI Lab to research factors influencing healthcare workers’ confidence in AI-driven technologies and how their confidence can be developed through education and training. We have published two reports in relation to this research.

Report one - Understanding healthcare workers’ confidence in AI

The first report argues that confidence in AI used in healthcare can be increased by establishing its trustworthiness through the governance and robust implementation of these technologies.

In the context of clinical decision making, once trustworthiness in AI technologies has been established, high confidence in AI-derived information may not always be desirable. For example, a clinician may accept an AI recommendation uncritically, potentially due to time pressure or limited experience in the clinical task - a tendency referred to as automation bias.

Report two - Developing healthcare workers' confidence in AI

The second report determines educational and training requirements, and presents pathways for education and training offerings to develop the workforce’s confidence in AI.

The report calls for the fundamentals of AI to be added to training courses for all health and care professionals, and for more advanced specialist training for other health and care staff depending on their roles and responsibilities whether in procurement, implementation or if they may be using AI in clinical practice.

The AI Roadmap

Working with Unity Insights, the AI Roadmap (and interactive dashboard) was published in January 2021 which refines a database of 240 AI technologies which are ready or almost ready for deployment. The roadmap helps to provide evidence for prioritisation through an assessment of: 

  • Which clinical area and workforce groups will be affected by the technology 

  • Likely time to deployment 

  • Impact of the primary workforce group, pathway and system.