Originally published March 14, 2019
Here is an excerpt:
What are the best examples of how AI can work in medicine?
We’re seeing rapid uptake of algorithms that make radiologists more accurate. The other group already deriving benefit is ophthalmologists. Diabetic retinopathy, which is a terribly underdiagnosed cause of blindness and a complication of diabetes, is now diagnosed by a machine with an algorithm that is approved by the Food and Drug Administration. And we’re seeing it hit at the consumer level with a smart-watch app with a deep learning algorithm to detect atrial fibrillation.
Is that really artificial intelligence, in the sense that the machine has learned about medicine like doctors?
Artificial intelligence is different from human intelligence. It’s really about using machines with software and algorithms to ingest data and come up with the answer, whether that data is what someone says in speech, or reading patterns and classifying or triaging things.
What worries you the most about AI in medicine?
I have lots of worries. First, there’s the issue of privacy and security of the data. And I’m worried about whether the AI algorithms are always proved out with real patients. Finally, I’m worried about how AI might worsen some inequities. Algorithms are not biased, but the data we put into those algorithms, because they are chosen by humans, often are. But I don’t think these are insoluble problems.
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