Consider robots your team members in a relay race

How can you compete against robots? Thomas H. Davenport and Julia Kirby, writing in the June issue of the Harvard Business Review, have some ideas. Before listing them, they outline what they call the three eras of automation. First, in the 19th century, machines began taking on dirty and dangerous jobs. In the 20th century, automation took over dull, routine service jobs and clerical chores. Now, in the third era, machines are taking on what I’ll call the fun jobs—they are making decisions, and they can often make better choices faster than humans can.

Asking what jobs machines will take over next might be the wrong question, Davenport and Kirby suggest. They pose a new question: “What new feats might people achieve if they had better thinking machines to assist them?” They add, “We could reframe the threat of automation as an opportunity for augmentation.”

Davenport and Kirby offer five ways of achieving augmentation:

Step up to higher intellectual ground. “There will always be jobs for people who are capable of more big-picture thinking and a higher level of abstraction than computers are,” they write. “In essence this is the same advice that has always been offered and taken as automation has encroached on human work: Let the machine do the things that are beneath you, and take the opportunity to engage with higher-order concerns.” If you choose to step up, they advise, get an M.B.A. or Ph.D. and gain a broad perspective.

Step aside and focus on interpersonal and other of what the psychologist Howard Gardner calls “multiple intelligences,” which computers can’t readily emulate. Davenport and Kirby note that Apple chief designer Jonathan Ive can’t download his taste into a computer. If you choose to step aside, you’ll need to develop your multiple intelligences beyond IQ, possibly through apprenticeships.

Step in and monitor and modify decisions made by computer. Computers frequently make bad decisions. Davenport and Kirby cite the case of Ben Bernanke—a computer rejected his application to refinance his mortgage in 2014 because his million-dollar book contract and planned lucrative lecture-circuit stint were considered too risky, compared with his previous eight-year job as chair of the Federal Reserve. If you want to step in, make sure you have a strong STEM background and update your business-domain expertise.

Step narrowly into a specialty that wouldn’t be economical to automate. Davenport and Kirby cite the case of Gary Joyal, who connects buyers and sellers of Dunkin’ Donuts franchises. It might be possible to automate Joyal’s expertise, they write, but it would not be economical to do so. If you identify such a niche, they write, focus on it with passion.

The final way of achieving augmentation, they write, is to step forward. If you can’t beat the robots, build them, or at least develop applications for them. If you choose this path, you’ll need to stay at the cutting edge of computer science, artificial intelligence, and data analytics.

Whichever step you choose, the goal is to treat machines as partners—not competitors in a zero-sum game. Davenport and Kirby conclude, “By emphasizing augmentation, we can remove the threat of automation and turn the race with the machine into a relay rather than a dash. Those who are able to smoothly transfer the baton to and from a computer will be the winners.”

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