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Address health inequities among human beings is an ethical matter of urgency, whether or not to develop more powerful AI
  1. Hongnan Ye
  1. Beijing Alumni Association of China Medical University, Beijing, China
  1. Correspondence to Hongnan Ye, Beijing Alumni Association of China Medical University, Beijing, China; juventus_buffon{at}126.com

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In their article,1 Jecker et al highlight a widespread and hotly debated issue in the current application of artificial intelligence (AI) in medicine: whether we should develop more powerful AI. There are many perspectives on this question. I would like to address it from the perspective of the fundamental purpose of medicine. Since its inception, medicine has been dedicated to alleviating human suffering and ensuring health equity. For thousands of years, we have made great efforts and conducted many investigations to eliminate human suffering and have achieved remarkable results. However, the reality of achieving health equity falls far short of expectations. The WHO considers health equity to be a fundamental human right, meaning that there should be no unjustified, avoidable or remediable differences among the population as a whole, whether those differences result from social, economic, demographic or geographic factors, or from other forms of inequality such as gender, race, disability or sexual orientation.2 Health equity means reducing and ultimately eliminating disparities in health outcomes between vulnerable groups and others, caused by health risk factors and difficulties in accessing quality health services. This means that we must strive to reduce structural social bias. It is well known that the traditional healthcare system is riddled with various health inequities. …

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Footnotes

  • Contributors HY is the sole author and solely responsible for the content of this manuscript.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; internally peer reviewed.

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