Here is a composite of several brief excerpts from interviews of several thought leaders conducted by Rik Kirkland for The McKinsey Quarterly, published by McKinsey & Company. The rapid advance of machine learning presents an economic paradox: productivity is rising, but employment may not. What are the probable implications? The article is accompanied by a video. To read the complete article, check out other resources, learn more about the firm, obtain subscription information, and register to receive email alerts, please click here.

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As machine learning advances at exponential rates, many highly skilled jobs once considered the exclusive domain of humans are increasingly being carried out by computers. Whether that’s good or bad depends on whom you talk to. Technologists and economists tend to split into two camps, the technologists believing that innovation will cure all ills, the economists fretting that productivity gains will further divide the haves from the have-nots.

To set the context for the debate and to examine potential policy implications for pressing social questions, McKinsey’s Rik Kirkland conducted a series of interviews in January at the World Economic Forum’s annual meeting in Davos. Among those interviewed were Nobel Prize–winning economist Robert Shiller, author of Finance and the Good Society (Princeton University Press, 2012), among other books; data scientist Jeremy Howard; and professor Erik Brynjolfsson, of the Massachusetts Institute of Technology, who, along with Andrew McAfee, is the author of The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies (W.W. Norton & Company, 2014). This edited transcript captures and combines highlights from those conversations.

Workforce at risk?

The Quarterly: Erik, your new book focuses in part on the social and policy implications of what you’re calling “the Second Machine Age.” Can you set the context for these issues?

Erik Brynjolfsson: Brynjolfsson: In our book, The Second Machine Age, we call it the great paradox of the Second Machine Age. The paradox is that even though we’ve had record levels of wealth creation, employment hasn’t kept up. Even though we have record productivity, US median incomes are lower now than they were in the 1990s. There’s been a decoupling of the two. As we researched the book, we found two disparate groups that tend to focus on either productivity or inequality.

On the one hand, there are the techno-optimists, who often have a utopian view of the world. This group thinks that technology will solve all our problems. In fairness, innovation has never been faster, and technology has solved an amazing set of problems. The conclusion this group sometimes draws from that is “just let technology do its thing and the rest will take care of itself.” People in the second group, which is largely composed of economists, tend to have a pessimistic view of both the present and, perhaps more disturbingly, the future. They point out that median income is lower now than it was in the 1990s, that unemployment has been struggling, that the economy, by many metrics, has been performing quite poorly. They believe that we’ll have less economic growth in the future than we did in the past.

As you try to reconcile those two groups—the utopians versus the dystopians, or “stagnationists”—you can end up concluding that, in many ways, they are both right, about the facts, at least, if not the conclusions. We do have innovation, but that doesn’t mean everyone’s necessarily going to be taken care of. We have stagnating median income, but that doesn’t mean innovation has slowed down.

In fact, the dirty secret of economics is that it’s possible for technology to make the pie bigger—and that’s exactly what it’s been doing. Record wealth. But at the same time there’s no law that everybody’s going to benefit from technology. Some people, even a majority, may be worse off. Ever since the Industrial Revolution, we’ve experienced a rising tide that has helped most people. But in the past 15 or 20 years or so, those trends have diverged. We have what my coauthor, Andy McAfee, and I call the Great Decoupling. Productivity has continued to grow steeply and innovation has been strong, but median income and employment have stagnated.

The Quarterly: Jeremy, how big a deal are machine-learning algorithms for employment and the workforce? And what should we do about it?

Jeremy Howard: I think it is important to think about the policy implications here. Government leaders need to be aware that, right now, computers are as good as or better than humans at most of the tasks people involved in information-processing jobs do. That is 65 percent of the American workforce. So is this wonderful or is this a tragedy? It actually depends entirely on how governments respond. Scenario number one is a disparity in economic power, in which the folks with the data and the algorithms have—and add all of—the economic value, and the rest of the workforce adds little or none.

That scenario could create an awful social disruption. Scenario number two is to accept that in this new world, there’s a large group of people who can’t really add economic value anymore, but that doesn’t mean they don’t get to live a decent human life. So we have to start thinking about the policy implications—like a basic living wage, which Germany will be introducing, or a negative income tax, which has been off the agenda for decades but deserves to be back on it. I think people should start to think about these policy implications because the point at which we need to make decisions will be upon us suddenly.

The Quarterly: Bob Shiller, you’ve devoted research time to the implications of technology for peoples’ livelihoods, and have discussed them in your recent book. How do you see the problem?

Robert Shiller: I think it’s the most important problem facing the world today. It’s associated with income inequality, but it may be more than that. Since we tend to define ourselves by our intellectual talents, it’s also a question of personal identity. Who am I? Intellectual talents are being replaced by computers. That’s a frightening thing for most people. It’s an issue with deep philosophical implications.

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Here is a direct link to the complete interview.

Erik Brynjolfsson is the Schussel Family Professor of Management Science at the Massachusetts Institute of Technology’s Sloan School of Management. Jeremy Howard is a research scientist at the University of San Francisco. Robert Shiller is the Sterling Professor of Economics at Yale University, a Nobel laureate in economics, and the author of many books, most recently Finance and the Good Society (Princeton University Press, 2012). This interview was conducted by Rik Kirkland, senior managing editor of McKinsey Publishing, who is based in McKinsey’s New York office.