Can AI Improve Health Without Perpetuating Bias?

The Dose

Inhoud geleverd door The Commonwealth Fund. Alle podcastinhoud, inclusief afleveringen, afbeeldingen en podcastbeschrijvingen, wordt rechtstreeks geüpload en geleverd door The Commonwealth Fund of hun podcastplatformpartner. Als u denkt dat iemand uw auteursrechtelijk beschermde werk zonder uw toestemming gebruikt, kunt u het hier beschreven proces https://nl.player.fm/legal volgen.

1+ y ago 31:30

MP3•Thuis aflevering

On this week’s episode of The Dose, host Joel Bervell speaks with Dr. Ziad Obermeyer, from the University of California Berkeley’s School of Public Health, about the potential of AI in informing health outcomes — for better and for worse.

Obermeyer is the author of groundbreaking research on algorithms, which are used on a massive scale in health care systems — for instance, to predict who is likely to get sick and then direct resources to those populations. But they can also entrench racism and inequality into the system.

“We've accumulated so much data in our electronic medical records, in our insurance claims, in lots of other parts of society, and that’s really powerful,” Obermeyer says. “But if we aren’t super careful in what lessons we learn from that history, we’re going to teach algorithms bad lessons, too.”

Citations

Dr. Ziad Obermeyer

Dissecting racial bias in an algorithm used to manage the health of populations

Nightingale Open Science

107 afleveringen

#Health Industry #Health and Well-Being #Health Care #Healthcare #Policy #Non-Profit #Business #Fitness #Government #Commonwealth Funds