New perspective argues pursuing fair AI for healthcare requires cross-disciplinary collaboration to translate methods into real-world benefits.
Pursuing fair artificial intelligence for healthcare requires collaboration between experts across disciplines, says a global team of scientists led by Duke-NUS Medical School in a new perspective published inWhile AI has demonstrated potential for healthcare insights, concerns around bias remain."A fair model is expected to perform equally well across subgroups like age, gender and race.
He added,"Differences detected between groups are frequently treated as biases to be mitigated in AI research. However, in the medical context, we must discern between meaningful differences and true biases requiring correction." Overall, the authors argue that pursuing fair AI for healthcare requires collaboration between experts in AI, medicine, ethics and beyond."Achieving fairness in the use of AI in healthcare is an important but highly complex issue. Despite extensive developments in fair AI methodologies, it remains challenging to translate them into actual clinical practice due to the nature of healthcare -- which involves biological, ethical and social considerations.
Professor Patrick Tan, Senior Vice-Dean for Research at Duke-NUS, commented,"This global cooperation exemplifies the cross-disciplinary dialogues required to advance fair AI techniques for enhancing healthcare. We hope this collaborative effort spanning Singapore, Europe, and the US provides valuable perspectives to inspire further multinational partnerships towards equitable and unbiased AI.
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