Thriving In the New Age of Automation

A second industrial revolution is upon us — and this time around, we’ll have to work with our machines, not just control them, to succeed

Interview with Erik Brynjolfsson

Brilliant machines will join the ranks of our "knowledge workers" in the coming years — replacing humans in thousands of jobs in every sector of the economy — but they will also unlock new opportunities for humans, too. Once only thought possible in the realm of science fiction, machines today are performing surgeries, flipping burgers and navigating cars through rush-hour traffic. Pundits often greet the rise of the robots with a mixture of awe and skepticism. From “machines are eating our jobs” to “they’ll ruin our economy,” assumptions about automation’s role in the workforce often overlook the opportunities that technology has only just begun to offer.

In their new book, “The Second Machine Age,” Erik Brynjolfsson and Andrew McAfee paint a different picture. The two MIT professors suggest that smart machines will have the potential to bring a dramatic economic growth spurt, rather than stagnation.

Brynjolfsson, director of the MIT Center for Digital Business, says that he’s “mindfully optimistic” about the future of technology: Optimistic because we’ll have unprecedented opportunities for innovation, but mindful because the unfolding relationship between humans and machines requires active participation on our part.

You say we’re in the midst of a second machine age. What is it about this particular moment in time that’s bringing us to a new inflection point in our economies and societies?

The best way to think of it is in comparison to the Industrial Revolution, or the first machine age. For most of recorded history, not much happened in terms of our economic well-being and welfare until the steam engine was invented along with a host of related technologies around the late 1700s. Since then our living standards have just soared. There was a real inflection point, and we’re far wealthier than our ancestors as a result. We have longer life spans and are better on just about every economic metric.

The first machine age relieved some of the limitations of our own human muscles for manipulating the world. The second machine age is about doing something similar for our cognitive capabilities.

The main thing the first machine age did was relieve some of the limitations of our own human muscles and animal muscles for manipulating the world. The second machine age is about doing something similar for our cognitive capabilities — for our brain’s mental capabilities — with technologies like computerization and Big Data, software and networking.

Andy McAfee and I think that’s going to be at least as big a deal as the first machine age. In the past 5 to 10 years, it has really started taking off in terms of how it’s affecting more — and more different kinds of — applications. Especially because of Big Data, and also because of Moore’s Law, which is this exponential doubling and redoubling of computer power every 18 months, we’re having an explosion of innovation.

How can a hybrid team of humans and computers be better than a homogenous group of either?

I picked up the Boston Globe today and on the front page there’s a story about a medical doctor who’s been using Google Glass at Beth Israel Deaconess Medical Center.

According to the story, he was able to identify a drug side effect, which he wouldn’t have detected without Google Glass, and found that this patient was allergic to a certain drug. He says that Google Glass basically helped him save this patient’s life by warning him about that. So it’s a good example of this racing with machines, of combing this vast database that a computer can have of drug interactions with the human knowledge of when to apply it and how to use it to save someone’s life.

There have also been a lot of technologies that just do a straight up replacement of humans with machines. We call that racing against the machine. That can create a lot of wealth, but it often leads to more concentration of income and income inequality. So even though it makes the pie bigger, it doesn’t necessarily mean that everyone benefits from that. We’d like to encourage people to think more aggressively about ways that you can use technology to, as we say, race with the machines to complement humans, not just substitute for humans.

Even as machines do creep into knowledge work, or develop fine motor skills, how should humans start to think of computers as teammates?

This is the big question going forward, and I have to confess to being genuinely uncertain about how this is going to play out in the future. In the past we’ve always been able to come up with new jobs as old jobs got replaced. Technology has been destroying jobs, but it also helped create opportunities for new jobs. Entrepreneurs like Henry Ford, Steve Jobs, Bill Gates and others helped invent whole new industries.

It’s a little bit harder for me to think of what those new industries are going to be, but that may just be a lack of imagination on my part. The way we’ve solved this problem in the past is that we’ve crowdsourced it. We’ve had tens of thousands or hundreds of thousands of entrepreneurs who have all sorts of ideas.

Think more aggressively about ways that you can use technology to race with the machines to complement humans, not just substitute for humans.

Some of them are wacky and fail, and others seem wacky but end up working out miraculously. Unfortunately, in the past 15 years we haven’t been doing that as rapidly and as effectively as we did in the past. New job creation isn’t keeping up, and so the share of the population that’s working has been falling and median income is lower now than it was in the 1990s. So I’m genuinely concerned about our ability to keep inventing those new jobs.

There are techno-utopians who say technology is going to solve all of our problems. There are others who look at job destruction and spin very pessimistic scenarios.

We call ourselves mindful optimists because we think that we can have a good outcome, but it’s going to require a lot of effort on our part. We actually can control our future to a much greater extent. Neither the optimistic nor the pessimistic scenario is inevitable.

As we say in the last line of the book, technology is not destiny. We shape our destiny. That’s a really important message for people to understand. That it’s not just a matter of sitting back and watching this technology unfold. It really should be more of an activist view.

 

Erik Brynjolfsson is the Schussel Family Professor of Management Science, a professor of information technology and director of the MIT Center for Digital Business at the MIT Sloan School of Management. He was among the first researchers to measure the productivity contributions of information and community technology (ICT) and the complementary role of organizational capital and other intangibles. His research also provided the first quantification of the value of online product variety, often known as the “Long Tail,” and developed pricing and bundling models for information goods.

Interview with Marguerite McNeal, an editor at Original9 Media in San Francisco.