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Responsible AI: Medical Triage During COVID-19 and Beyond

This is a virtual event through Facebook Live. You do not need a Facebook account to watch.


In the past year, we explored how Artificial intelligence (AI) could revolutionize health care and the responsibilities associated with emerging developments. In this new series on Responsible AI, we examine multiple ways in which AI is bringing us to a "new normal," and the potential applications of AI for good.

You do not need a Facebook account to view this event.

Medical Triage During COVID-19 and Beyond

Episode 05: In this installment of our “Responsible AI” virtual series, supported by Hitachi, we return to the subject of AI in the context of health. We will examine in detail the use of AI during the pandemic as a tool used by hospitals for the purposes of triage. Medical personnel have used an AI-based algorithm to assign ventilators to patients, determine recovery probability, or calculate a prognosis score. These techniques raise many questions of a technical, ethical and moral sort, including with regard to the algorithms' reliability, fairness, accuracy, transparency, the consequences of false negative and false positive, and the need for a "human in the loop."

Join us on November 12, 2020, at 2:00 PM Eastern for a discussion between two experts in medical triage using AI both during and after the COVID-19. We will first explore how AI is being used in triage, comparing current uses in the context of the pandemic and its use before. Will discuss the likelihood that these applications implemented in a time of crisis, will be kept and used in hospital settings even when the threat of the virus is long gone? Is a "score" the way of the future in monitoring people's health?

The event will be available via the AAAS and Science Facebook pages.

Recordings from this series are archived on YouTube and made available on the AAAS website.


David Magnus, PhD, is Thomas A. Raffin Professor of Medicine and Biomedical Ethics, and Professor of Pediatrics, Medicine, and by Courtesy of Bioengineering at Stanford University. He is the Director of the Stanford Center for Biomedical Ethics, a member of the Stanford Hospital and Clinics Ethics Committee, is past President of the Association of Bioethics Program Directors and is the Editor-in-Chief of the American Journal of Bioethics. Dr. Magnus is currently the Vice-Chair of the IRB for the NIH Precision Medicine Initiative (“All of Us”). He is a member of Stanford’s IRB and Stem Cell Research Oversight Committee and has extensive experience as a research ethics consultant. His research focuses on a wide range of topics in bioethics, including research ethics, the ethics of comparative effectiveness research, transplant ethics, genetics/genomics, and issues in patient/physician communication and artificial intelligence and machine learning in medicine.

Karandeep Singh, MD, MMSc, is an Assistant Professor of Learning Health Sciences, Internal Medicine, Urology, and Information at the University of Michigan. He is a nephrologist with a background in biomedical informatics who uses machine learning methods to model electronic health record and registry data in support of a learning health system. Dr. Singh directs the Machine Learning for Learning Health Systems lab which focuses on using machine learning and biomedical informatics methods to understand and improve health at scale. His research spans multiple clinical domains including nephrology, urology, emergency medicine, obstetrics, and ophthalmology. He chairs the Michigan Medicine clinical intelligence committee, which focuses on implementation of machine learning models across the health system, and he serves on the Michigan Economic Development Corporation's Artificial Intelligence Advisory Board. He teaches a health data science course to over 60 graduate students every year. Dr. Singh completed his internal medicine residency at UCLA Medical Center, where he served as chief resident, and a nephrology fellowship in the combined Brigham and Women’s Hospital/Massachusetts General Hospital program in Boston, MA. He completed his medical education at the University of Michigan Medical School and holds a master’s degree in medical sciences in Biomedical Informatics from Harvard Medical School. He is board certified in internal medicine, nephrology, and clinical informatics.

Jessica Wyndham (Moderator) is the Director of the Scientific Responsibility, Human Rights and Law Program. She also serves as coordinator of the AAAS Science and Human Rights Coalition, a network of scientific, engineering, and health associations that recognize the role of science and technology in human rights. Her areas of expertise include the intersections of science, technology, human rights and ethics, the social responsibilities of scientists and engineers, and the role of professional scientific, engineering and health societies in the promotion and protection of human rights.

Articles from the Science Family of Journals

Artificial intelligence systems aim to sniff out signs of COVID-19 outbreaks (Cho, 2020)

Combating COVID-19—The role of robotics in managing public health and infectious diseases (Yang et al., 2020)

Artificial intelligence for global health (Hosny and Aerts, 2019)

AI in resource-poor health care systems (Alderton, 2019)

Medicine contends with how to use artificial intelligence (Couzin-Frankel, 2019)

Adversarial attacks on medical machine learning (Finlayson et al., 2019)

Health and societal implications of medical and technological advances (Dzau and Balatbat, 2018)

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