<< Machine learning is taking medical diagnosis by storm. From eye disease, breast and other cancers, to more amorphous neurological disorders, AI is routinely matching physician performance, if not beating them outright. Yet how much can we take those results at face value? When it comes to life and death decisions, when can we put our full trust in enigmatic algorithms—“black boxes” that even their creators cannot fully explain or understand? The problem gets more complex as medical AI crosses multiple disciplines and developers, including both academic and industry powerhouses such as Google, Amazon, or Apple, with disparate incentives. >>
<< This week, the two sides battled it out in a heated duel in one of the most prestigious science journals, Nature. >>
Shelly Fan. Can We Trust AI Doctors? Google Health and Academics Battle It Out. Oct 20, 2020.
Benjamin Haibe-Kains, George Alexandru Adam, et al. Transparency and reproducibility in artificial intelligence. Nature 586, E14–E16. doi: 10.1038/ s41586-020-2766-y. Oct 15, 2020
Emre Sezgin, Yungui Huang, et al. Readiness for voice assistants to support healthcare delivery during a health crisis and pandemic. npj Digit. Med. 3, 122. doi: 10.1038/ s41746-020-00332-0. Sep 16, 2020.
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