While artificial intelligence is already transforming health care by improving diagnostic accuracy and speeding the analysis of biological and genomics data to better understand disease, there are many ethical issues that should be considered. This was the message that Mayo Clinic bioethicist Richard Sharp, Ph.D., shared with attendees at the first Mayo Clinic Artificial Intelligence Symposium held in May at Mayo Clinic’s campus in Rochester, Minnesota.

“Artificial intelligence holds great potential in augmenting physicians’ and researchers’ ability to rapidly analyze data, speeding the pace of medical discovery and diagnostic accuracy. At the same time, its application in medicine raises many ethical questions that should be addressed as we move forward with this rapidly advancing technology,” says Dr. Sharp, director, Mayo Clinic Biomedical Ethics Research Program, and director, Mayo Clinic Center for Individualized Medicine Bioethics Program.

In his keynote presentation, Medicine and Artificial Intelligence: Ethical Tensions, Dr. Sharp raised these ethical issues to consider in the near term:

• How do researchers manage the problem of bias in source datasets?
• When using data generated from artificial intelligence in clinical practice, will physicians still be able to exercise their discretion by considering other factors that may impact whether a patient should receive a particular treatment?
• Who decides which evidence is sufficiently robust to drive a computer model?  Who develops consensus guidelines? How does this impact all stakeholders' ability to participate in the research process?  
• Will patients be willing to share personal data needed for artificial intelligence models to aid medical research and how can their privacy be protected?  

Symposium attendees from Mayo Clinic and institutions around the country gathered to learn about current and future opportunities for artificial intelligence in health care, including how it is being used in diagnostic imaging, clinical practice and genomics data analysis.

Read more highlights from the symposium.

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