Google's medical AI was super accurate in a lab. Real life was a different story. IAM Network

But an accuracy assessment from a lab goes only so far. It says nothing of how the AI will perform in the chaos of a real-world environment, and this is what the Google Health team wanted to find out. Over several months they observed nurses conducting eye scans and interviewed them about their experiences using the new system. When it worked well, the AI did speed things up. But it sometimes failed to give a result at all. Like most image recognition systems, the deep-learning model had been trained on high-quality scans; to ensure accuracy, it was designed to reject images that fell below a certain threshold of quality.