Automation has plenty of blue-collar jobs in its crosshairs. But it’s not just impacting the average worker.
Radiologists, who receive years of training and are some of the highest paid doctors, are among the first physicians who will have to adapt as artificial intelligence expands into health care.
Radiologists use medical images, such as X-rays, CT scans, MRIs, ultrasounds and PET scans, to diagnose and treat patients. The field has greatly improved patient care, but has also driven up health care costs.
Precise numbers are hard to come by, but most estimates place radiology as an $8 billion industry in the U.S. Globally, the market is expected to grow from $28 billion to $36 billion by 2021, according to research firm Marketsandmarkets.
The tech and radiology communities expect artificial intelligence to transform medical imaging, providing better services at lower costs. For example, if you’re getting an MRI, an AI program can improve the analysis, leading to better treatment.
“This is going to be transformational,” said Keith Dreyer, vice chairman of radiology computing and information sciences at Massachusetts General Hospital. “Every month there’s going to be a new algorithm that we’re going to use and integrate into our solutions. When you look back we’ll say, ‘How did I ever live without this?'”
Today radiologists face a deluge of data as they serve patients. When Jim Brink, radiologist in chief at Massachusetts General Hospital, entered the field in the late 1980s, radiologists had to examine 20 to 50 images for CT and Pet scans. Now, there can be as many as 1,000 images for one scan.
The work can be tedious, making it prone to error. The added imagery also makes it harder for radiologists to use their time efficiently. Brink expects artificial intelligence to act as a diagnostic aid, flagging specific images that a human should spend more time examining.
Related: Why U.S. workers are at a higher risk of automation
Arterys, a medical imaging startup, reads MRIs of the heart and measures blood flow through its ventricles. The process usually takes a human 45 minutes. Arterys can do it in 15 seconds.
The remarkable power of today’s computers has raised the question of whether humans should even act as radiologists. Geoffrey Hinton, a legend in the field of artificial intelligence, went so far as to suggest that schools should stop training radiologists.
Those on the front lines are less dramatic.
“There’s a misunderstanding that someone can program a bot that will take over everything the radiologist does,” said Carla Leibowitz, head of strategy and marketing at Arterys. “Radiologists still use the product and still make judgment calls. [We’re] trying to make products to make their lives easier.”
According to Dreyer, a radiologist spends about half the day examining images. The rest is spent communicating with patients and other physicians. There’s only so much that automated systems can take over.
“Our desire to have somebody in control, I don’t think that will go away anytime soon,” said General Leung, cofounder of MIMOSA Diagnostics, which is testing a smartphone device that uses AI to aid diabetics. “Someone’s always going to want a person to have made the decision.”
The future for radiologists may be similar to airline pilots. While planes generally fly on auotpilot, there’s still a human in the cockpit.
Related: Goodbye high seas, hello cubicle. Sailor, the next desk job.
Dreyer’s hospital is enthusiastically embracing the potential of AI to transform radiology. They’ve bulked up their computing power and are organizing their data to train algorithms. But there’s a long road ahead. Artificial intelligence will need to be able to respond to thousands of situations to match the image interpretation that a radiologist does. Right now, Massachusetts General Hospital is focusing on 25 of them.
“The foreseeable future is not going to be human vs. machine, but human plus machine vs. a human without a machine,” Dreyer said. “The human plus machine is going to win.”
The future of radiologists appears to offer a lesson for any worker concerned about automation. If you can’t beat the machines, join them.