We Are Entering The Era Of Robot Doctors

We Are Entering The Era Of Robot Doctors

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Young woman doctor holding a red heart, isolated on white (Credit: Shutterstock/lenetstan)
Young woman doctor holding a red heart, isolated on white (Credit: Shutterstock/lenetstan)

Doctors look to be the next profession to be turned upside down by automation.

The economic definition of technology is the replacement of labor with capital. Firms take an expensive and arguably less reliable labor input — a human — and exchange it for a more durable, automated and cost-efficient machine.

The phenomena is already taking place in the service and financial industries. As campaigns to raise the minimum wage, like the “Fight for $15,” wage on around the nation, businesses are exchanging employees for machines. McDonald’s, for example, rolled out self-service kiosks that allow customers to order and pay for their food.

The medical industry is starting to delve into machine intelligence. For instance, one of the top research hospitals in the U.S. is employing machine intelligence to analyze some 10 billion genetic images. Another medical startup is using machine deep learning technology to to analyze radio images. The startup’s technology is up to 50 percent more effective at judging malignant tumors than professional human radiologists, The Economist reports.

It could be just a matter of time before biomedical engineers are conjuring ways to expand machine learning into areas traditionally filled by physicians.

Health insurance companies and health care benefit firms, like Anthem, are also looking into ways to employ machine learning to streamline the process of bringing products to customers, Deloitte University Press reports.

There are, however, some inherent risks when moving to automation. The rewards are rather obvious: cheaper costs of maintaining labor of the long-term, increased speed and efficiency, and they could identify things that the human eye misses.

The risks are also substantial. Technology is largely susceptible to hacking, creating possible identity theft problems for the patient. Experts also note that a possible risk is that it isn’t always easy to determine why a machine made a decision. There is currently no clear, concise way of determining how a machine calculated its decision.

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