When Vic Gundotra left Google in 2014, he thought he might retire, forever. But a lingering interest in wearable technology and machine learning led him to AliveCor, which lets users monitor their heart health from their smartphones.
Diving back into the fray of tech, Gundotra is now convinced that the potential of wearables and machine learning is just starting to be unlocked. AliveCor’s portable EKG sensor, Kardia, alerts users if their heartbeats are irregular — and now, the Mayo Clinic, an AliveCor investor, has begun identifying other signals in an EKG reading that a human might miss.
“No human doctor can look at your EKG and tell you with a high degree of accuracy what your potassium level is,” Gundotra said. “But the machines might be able to do something.”
Although he believes artificial intelligence will take some jobs away over time, Gundotra said people will always want human doctors “to tell them what’s going on.” He envisioned a near future where those doctors routinely enlist machines’ help and developing a good bedside manner becomes more important than ever.
“Today, you would never buy a car without airbags and antilock brakes,” he said. “In the next half-decade, no physician will practice without deep-learning, machine-learning systems by his side or her side.”
However, he noted that the collapse of blood-testing startup Theranos is an “unmitigated disaster” for health-tech, saying it undermined the confidence of both investors and consumers.
“It makes me angry, it makes me frustrated,” Gundotra said. “Yes, working with the FDA is challenging. Yes, it takes an extra nine months to a year to get things done. But those agencies are put in place to protect consumers and health care; you’ve gotta follow the rules. You’ve gotta do these things.”
“I do think, sometimes, Silicon Valley has a philosophy: ‘Move fast and break things,’” he added. “You can’t do that when it comes to people's health care. You tell someone their heart rhythm is normal and they die of a heart attack, that’s on you.”
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This article originally appeared on Recode.net.