AI and machine learning (ML) systems are revolutionising the provision of healthcare. Computer systems can now recognise heart attack victims through voice recognition, rapidly and accurately review mammograms to reduce unnecessary biopsies, and even detect subtle abnormalities within computed tomography (CT) imagery. Automating tedious tasks can free up time poor health professionals and reduce administrative errors, while real-time data can rapidly inform better decision-making.
But existing health inequalities could be exacerbated if factors such as algorithmic biases are unaccounted for. This has prompted NHS England to pilot an algorithmic impact assessment (AIA) in an attempt to combat the potential risks associated with AI in healthcare. Designed by the Ada Lovelace Institute, the AIA will mean researchers and developers will have to assess possible risks and biases posed by AI systems to patients and the public before they can access NHS data.
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