Here are 3 problems with DeepMind’s AI breakthrough, including poor accuracy at predicting acute kidney injuries

| | August 14, 2019
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DeepMind CEO Demis Hassabis. Image: Google
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[Google-affiliated artificial intelligence] DeepMind claimed its biggest healthcare breakthrough to date: that artificial intelligence (A.I.) can predict acute kidney injury (AKI) up to two days before it happens.

Beyond the headlines and the hope in the DeepMind papers, however, are three sober facts.

First, nothing has actually been predicted — and certainly not before it happens. Rather, what has happened is that DeepMind has taken a windfall dataset of historic incidents of kidney injury in American veterans, plus around 9,000 data-points for each person in the set, and has used a neural network to figure out a pattern between the two.

Second, that predictive pattern only works some of the time. The accuracy rate is 55.8% overall, with a much lower rate the earlier the prediction is made, and the system generates two false positives for every accurate prediction.

Third, and most strikingly of all: the study was conducted almost exclusively on men — or rather, a dataset of veterans that is 93.6% male. Given the A.I. field’s crisis around lack of diversity and amplification of bias and discrimination, that fact is very important — and astonishingly understated.

Read full, original post: DeepMind’s Latest A.I. Health Breakthrough Has Some Problems

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