Public support needed to tackle racial and other biases in AI for health care

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Members of the public are being asked to help remove biases based on race and other disadvantaged groups in artificial intelligence algorithms for health care.

Health researchers are calling for support to address how "minoritized" groups, who are actively disadvantaged by social constructs, would not see future benefits from the use of AI in health care. The team, led by the University of Birmingham and University Hospitals Birmingham write in Nature Medicine today on the launch of a consultation on a set of standards that they hope will reduce biases that are known to exist in AI algorithms.

There is growing evidence that some AI algorithms work less well for certain groups of people—particularly those in minoritized racial/. Some of this is caused by biases in the datasets used to develop AI algorithms. This means patients from Black and minoritized ethnic groups may receive inaccurate predictions, leading to misdiagnosis and the wrong treatments.

STANDING Together is an which will develop best-practice standards for health care datasets used in Artificial Intelligence, ensuring they are diverse, inclusive, and don't leave underrepresented or minoritized groups behind.

Dr. Xiaoxuan Liu from the Institute of Inflammation and Ageing at the University of Birmingham and co-lead of the STANDING Together project says that "by getting the data foundation right, STANDING Together ensures that 'no-one is left behind' as we seek to unlock the benefits of data driven technologies like AI. We have opened our Delphi study to the public so we can maximize our reach to communities and individuals. This will help us ensure the recommendations made by STANDING Together truly represent what matters to our diverse community."

Professor Alastair Denniston, Consultant Ophthalmologist at University Hospitals Birmingham and Professor in the Institute of Inflammation and Ageing at the University of Birmingham is co-lead of the project. Professor Denniston says that "as a doctor in the NHS, I welcome the arrival of AI technologies that can help us improve the health care we offer—diagnosis that is faster and more accurate, treatment that is increasingly personalized, and health interfaces that give greater control to the patient. But we also need to ensure that these technologies are inclusive. We need to make sure that they work effectively and safely for everybody who needs them."

Jacqui Gath, patient partner on the STANDING Together project says that "this is one of the most rewarding projects I have worked on, because it incorporates not only my great interest in the use of accurate validated data and interest in good documentation to assist discovery, but also the pressing need to involve minority and underserved groups in research that benefits them. In the latter group of course, are women."

More information: Ganapathi, S. et al, Tackling bias in AI datasets through the STANDING together initiative, Nature Medicine (2022). DOI: 10.1038/s41591-022-01987-w

Journal information: Nature Medicine
Citation: Public support needed to tackle racial and other biases in AI for health care (2022, September 26) retrieved 12 July 2024 from
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