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Fairness and Responsibility in Human-AI interaction in medical settings
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AI has transformative potential in healthcare by delivering consistent, high-quality care for patients while relieving workload pressures in healthcare systems. Realisation of this potential has been challenged by issues of algorithmic trustworthiness, confidence and fairness around the use of AI for augmented clinical reasoning and decision making (CRDM). The UK NHS AI-Lab in partnership with Health Education England (HEE) have recently published a report highlighting the challenges around model bias, transparency, explainability and cognitive bias in the human-AI interaction for AI-augmented CRDM. Education on these issues is generally lacking amongst healthcare professionals, leading to reduced confidence and increased susceptibility to cognitive biases, which have the potential to exacerbate inequalities and reduce fairness.
This resource maps to capability ID 1.1.0.1.1 of domain 1of the Artificial Intelligence (AI) and Digital Healthcare Technologies Capability Framework
| Contributed by: | Artificial intelligence beyond the basics |
| Authored by: |
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| Licence: | Creative Commons: Attribution-NonCommercial-NoDerivatives 4.0 International More information on licences |
| First contributed: | 19 September 2024 |
| Audience access level: | Full user |
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