Artificial intelligence is everywhere. And increasingly, it’s becoming a critical part of healthcare. Doctors use it to try to suss out symptoms of deadly infections like sepsis; companies like Google are developing apps to help you identify ailments just by uploading some pics.
But AI is only as good as the data sets fed into these systems. And when the data sets are flawed, or the results are not properly interpreted, the software can misidentify symptoms (or fail to identify them entirely). In some cases, this may even result in false positives, or exacerbate already stark racial disparities in the healthcare system.
This week on Gadget Lab, WIRED senior writer Tom Simonite joins us to talk about the blind spots in medical AI and what happens when tech companies put these algorithms into their users’ hands.
Read Tom’s story about the flaws in the AI that predicts sepsis here. Read his story about Google’s new dermatology app. Read more about the racial bias in AI systems (and how those algorithms might be fixed). Also check out Lauren’s story about how the internet doesn’t let you forget.
Tom Simonite can be found on Twitter @tsimonite. Lauren Goode is @LaurenGoode. Michael Calore is @snackfight. Bling the main hotline at @GadgetLab. The show is produced by Boone Ashworth (@booneashworth). Our theme music is by Solar Keys.
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