 Live from the Congress Center in London, England, it's theCUBE at MIT and the Digital Economy, the second machine age. Brought to you by headline sponsor MIT. Hi everybody, welcome to London. This is Dave Vellante with Stu Miniman, and this is theCUBE. theCUBE goes out, we go to the events, we extract the signal from the noise, we're very pleased to be in London. The scene of the first machine age, but we're here to talk about the second machine age, Andrew McAfee and Eric Brynjalsen. Gentlemen, first of all, congratulations on this fantastic book. It's been getting great acclaim. It's a wonderful book if you haven't read it. Andrew, maybe you could hold it up for our audience here, the second machine age. And Dave, to start off, thanks to you for being able to pronounce both of our names correctly. That's just about unprecedented in the history of the second machine age. I could probably even spell them. Whoa. So anyway, welcome, really appreciate you guys coming on and appreciate the opportunity to talk about the book. So Andrew, I want to start with you. So why London? I mean, I talked about the first machine age. Why are we back here? One of the things we learned when we were writing the book is how big a deal technological progress is. And the way you learn that is by going back and looking at a lot of history and trying to understand what bent the curve of human history. If we look at how advanced our civilizations are, if we look at how many people there are in the world, if we look at GDP per capita around the world, amazingly enough, we have that data going back hundreds, sometimes thousands of years. And no matter what data you're looking at, you get the same story, which is that nothing happened until the Industrial Revolution. So for us, the start of the first machine age, for us it's a real thrill to come to London, to come to the UK, which was the birthplace of the Industrial Revolution in the first machine age to talk about the second. So Eric, I wonder if you could, two sort of main vectors that you can take away from the book. One is that machines have always replaced humans and maybe doing so at a different rate these days. But the other is the potential of continued innovation, even though many people say Moore's law is dead, you guys have come up with sort of a premise as to how innovation will continue to double. So boil it down for the lay person. What should we think about this book? Well, sure. I mean, let me just elaborate on what you just said. Technology has always been destroying jobs, but it's also always been creating jobs. You know, a couple of centuries ago, 90% of Americans worked in agriculture on farms. In 1900s down to about 41%, now it's less than 2%. All those people didn't simply become unemployed. Instead, new industries were invented by Henry Ford, Steve Jobs, Bill Gates, lots of other people, and people got rather unemployed, but they became redeployed. One of the concerns is, is are we doing that fast enough this time around? We see a lot of bounty being created by technology. Global poverty rates are falling, record wealth in the United States, record GDP per person, but not everyone's participating in that. Not everyone's sharing. The past 10, 15 years, we've actually, to our surprise, seen median income fall. That's the income of the person at the 50th percentile, even though the overall pie is getting bigger. And one of the reasons that we created the initiative on the digital economy was to try to crack that, not understand what exactly is going on, how is technology behaving differently this time around than earlier era's? And part of that has to do with some of the unique characteristics of digital goods. Well, and your point in the book is that normally median income tracks productivity, and it's not this time around. Should we be concerned about that? I think we should be concerned about it. That's different than trying to stop or halt the course of technology. That's absolutely not something we should do. We should be more concerned about that, right? We need to let technology move ahead. We need to let the innovation happen. And if we are concerned about some of the side effects or some of the consequences of that, fine, fine, let's deal with those. You bring up what I think is one of the most important side effects to have our eye on, which is exactly as you say. When we look back for a long time, the average worker was taking home more pay, a higher standard of living, decade after decade, as their productivity improved. To the point that we started to think about that as an economic law, your compensation is your marginal productivity. Fantastic. What we've noticed over the past couple decades, and I don't think it's a coincidence that we've noticed this as the computer age has accelerated, is that there's been a decoupling. The productivity continues to go up, but the wage that average income has stagnated. And dealing with that is one of our big challenges. So, what do you tell your students? Become a superstar? I mean, not everybody can become a superstar. Well, our students can't. Yeah, maybe they can, yeah, yeah, yeah, yeah, sure. They're all aspire to, right? And a lot of people focus on the way that technology has helped superstars reach global audiences. I had one student, he wrote an app in about two or three weeks, he tells me. And within a few months, he had reached a million people with that app. That's something that probably would have been impossible a couple of decades ago, but he was able to do that because he built it on top of the Facebook platform, which is on top of the internet and a lot of other innovations that came before. So in some ways, it's never been easier to become a superstar and to reach literally, not just millions, but even billions of people. But that's not the only successful path in the second machine age. There's also other categories where machines just aren't very good yet. One of the ones that comes to mind is interpersonal skills, whether that's coaching or picking up on other cues from people, nurturing people, caring for people. And there are a whole set of professions around those categories as well. You don't have to be some superstar programmer to be successful in those categories. And there are millions of jobs that are needed in those categories for to take care of other people. So I think there's going to be a lot of ways to be successful in the second machine age. I think that's really important because the one takeaway that I don't like from people who have looked at our work is that only the amazing entrepreneurs or the people with 140 plus IQs are going to be successful in the second machine age. It's just not correct, as Eric says. The ability to negotiate, the ability to be empathetic to somebody, the ability to care for somebody, machines are lousy of these. They remain really important things to do. They remain economically valuable things to do. But I'm concerned that they won't remain lousy if I'm a student listening. You said in your book, self-driving cars, decade ago, even five years ago, so it can happen. So how do we predict what computers will and won't be good at? We basically don't. Our track record at doing that is actually fairly lousy. The mantra that I've learned is that objects in the future are closer than they appear. And the stuff that seemed like complete sci-fi are never going to happen, keeps on happening. Now that said, I am still going to be blown away the first time I see a computer-written novel that works, that I find compelling. That seems like a very human skill, but we are starting to see technologies that are good at recognizing human emotions, that can compose music, that can do art and paintings that I find pretty compelling. So, never say never is another word. Yeah, right, if I look some of the examples lately, basic news, computers can do that really well. IBM, the Watson machine can make recipes that we would have never thought of, things that would be creative. Andy, in the technology space, decade ago, computer science is where you tell everybody to go into today. Is data scientists still a hot opportunity for people to go in in the technology space? Where is there some good opportunity? Whether or not that's what the job title on the business card is that's going to be hot. Being a numerate person, being able to work with large amounts of data in particular, being able to work with huge amounts of data in a digital environment, in a computer, that skill's not going anywhere. You can think of jobs in three categories that's related to technology. There are ones that are substitutes, racing against machines. There are ones that are complements, that are using technology, and there are ones that just aren't really affected yet by technology. The first category you definitely want to stay away from, you know, a lot of routine information processing work, those are things machines can do well. Prepare yourself for a job as a payroll clerk. It's a really bad piece of advice. And we see that those jobs are disappearing both in terms of the numbers of employment and the wages that they get. The second category, jobs that complement, data scientists is a great example of that, or somebody who's an app writer or a YouTube, those are things that technology makes your skills more and more valuable. And then there's this huge middle category, we talked earlier about interpersonal skills, a lot of physical tasks still, where machines just really can't touch them too much. Those are also categories that so far have held up. I didn't know it. Middle school football coach is a job that's gonna be around, a human job that's gonna be around for a long time to come, because I have not seen a piece of technology that can inspire a group of 12 or 13 year olds to go out there and play together as a team. Now, Eric has actually been a middle school football coach, and he actually used a lot of technology to help him get good at that job, to the point where you were pretty successful middle school football coach. Yeah, we won a lot of games, and part of it was that we could learn from technology, we were able to break down films in ways that people never could have previously at the middle school level. This technology has made a lot of things much cheaper now than were available. So it was learning to be competitive versus learning how to teach kids to play football, is that right, or was it both? Well, actually, one of the most important things in being a coach is that interpersonal connection. That's one of the things I liked the most about it, and that's something I think no robot could do. I think it'd be a long, long time if ever that an inspiring half-time speech could be given by a robot, and get the kids to go out and give her Bryn Jolson. Well, to me, the most interesting example, I didn't realize this until I read your book, is that the best chess player in the world is not a computer, it's a computer and a human. So those, to me, seem to be the greatest opportunities for innovation. We call it racing with machines, and we want to emphasize that that's where people should be focusing. I think there's been a lot of attention on how machines can replace humans, but the bigger opportunity is how humans and machines can work together to do things that could never have been done before. In games like chess, we see that possibility, but even more interestingly, is when they're making new discoveries in neuroscience, or new kinds of business models like Uber and others, where we are seeing value creation in ways that were just not possible previously. And that chess example is going to spill over into the rest of the economy very, very quickly. I think about medicine and medical diagnosis. I believe that work needs to be a huge amount more digital and automated than it is today. I want Dr. Watson as my primary care physician, but I do think that the real opportunities are going to be to combine digital diagnosis, digital pattern recognition with the unique skills and abilities of a human doctor. Let's bring those two skill sets together. Well, the stat in your book is it would take a physician 160 hours a week to stay on top of reading, to stay on top of all the new publications and materials. But there's no amount of time that Watson could learn how to do the empathy that requires to communicate that and learn from a patient. So humans and machines have complementary skills. Machines are strong in some categories, humans and others, and that's why a team of humans and computers can be still powerful. That's the killer combo. Since the book came out, we found another great example related to automation and medicine and science. There's a really clever experiment that the IBM Watson team did with the team out of Baylor. They fed the technology a couple hundred thousand papers related to one area of gene expression and proteins, and they said, why don't you predict what the next molecules are we should look at to get this desired response out? And the computer said, okay, we think these nine are the next ones that are going to be good candidates. What they did that was so clever, they only gave the computer papers that had been published through 2003. So then we have 12 years to see if those hypotheses turned out to be correct. The computer was batting about 700. So people say that technology can never be creative. I think coming up with a good scientific hypothesis is an example of creative work. Let's make that work a lot more digital as well. So I got a question from the crowd here. The first industrial revolution really helped build up a lot of the cities. The question is with the speed and reach of the internet and everything, is this really going to help distribute the population more, what is the digital economy? I don't think so, we want to come to cities, not just because it's the only way to communicate with somebody, we actually want to be face to face with them. We want to hang out with them. Urbanization is a really, really powerful trend, even as our technologies have gotten more powerful. I don't think that's going to reverse, but I do think that if you want to get away from the city, at least for a period of time and go contemplate and be out in the world, you can now do that and not lose touch. The social and distributed workforce isn't going to drive that away. It's a real phenomenon, but it's not going to mean that cities are going to depopulate. Well, the cities have two unique capabilities. One is the entertainment and that you'd like to socialize with people in a face to face way most of the time, although people do it online as well. The other is that there's still a lot of types of communication that are best done in person. And in fact, real estate value suggests that being able to be close to other experts in your field, whether it's in Silicon Valley, Hollywood, Wall Street, is still a valuable asset. Eric and I travel a ton, not always together, and we can get a lot of our work done via email and via digital tools. When it comes time to actually get together and think about the next article or the next book, we need to be in the same room with the whiteboard doing it all at school. I wonder if we can come back to the roots of innovation. Moore's Law is Gordon Moore, sort of put it forth. 50th anniversary next week. Yeah, and it's coming to an end in terms of, it actually has ended in terms of the way it's doubling every 18 months. But it looks like we still have some runway, but experts can predict, and you guys made it to the point in your book, that people always underestimate human's ability to do the things that people think they can't do, but the real innovation is coming from this notion of combinatorial technologies. That's where we're going to see that continued exponential growth. What gives you confidence that that curve will continue? If you look at innovation as the work, not of coming up on some brand new Eureka, but as putting together existing building blocks in a new and powerful way, then you should get really optimistic because the number of building blocks out there in the world is only going up with iPhones and sensors and bandwidth and all these different new tools and the ability to tap into more brains around the world to allow more people to try to do that recombination. That ability is only increasing as well. I'm massively optimistic about innovation. Yeah, that's a fundamental break from the common attitude that we hear that we're using up all the low hanging fruit, that innovation, there's some fixed stock of it and first we get the easy innovations and then it gets harder and harder to innovate. We fundamentally disagree with that view. In fact, every innovation we create creates more building blocks for additional innovations and if you look historically, most of the breakthroughs have been achieved by combining previously existing innovations. So that makes us optimistic that we'll have more and more of those building blocks going forward. People say that we've rung all of the benefit out of the internal combustion engine, for example, and it's all just rounding error for here. No, a completely autonomous car is not rounding error. That's the new thing that's going to change our lives, it's going to change our cities, it's going to change our supply chains and it's making an entirely new use case out of that internal combustion engine. So you used the example of Waze in the book, really the software obviously was involved but it really was sensors and it was social media and mobile phones and networks and just these combinations of technologies for innovation. None of which was an invention of the Waze team, none of which was original, they just put those elements together in a really powerful way. So that's, I mean, the value of Waze is enormous. We're just scratching the surface. So we could talk about sort of what you guys expect going forward. I know it's hard to predict for the future. Well, another really important thing about Waze is in addition to the way it combined and recombined existing components, it's available for free on my phone and a GPS would have cost hundreds of dollars a few years ago and it wouldn't have been nearly as good at Waze and a decade before that it would have been infinitely expensive. You couldn't get it at any price and this is a really important phenomenon of the digital economy that I think is underappreciated is that so much of what we get is now available at zero cost. Our GDP measures are all the goods and services that are bought and sold. If they have zero price, they show up as a zero in GDP. Wikipedia. Right, Wikipedia. But that doesn't mean it has zero value. Yeah, Waze. Yeah, that doesn't mean it has zero value. It's still quite valuable to us and more and more I think our metrics are not capturing the real essence of the digital economy. One of the things we're doing at the initiative on the digital economy is to understand better what the right metrics will be for seeing this kind of growth. I wonder if you could talk about in the context of what you just said the competitiveness. So if I eat a piece of fruit, it disappears. It's mine but in the digital economy it's different. I wonder if you could explain that. And one of the ways it's different we'll use Waze as an example here again is network effects become really, really powerful. So Waze gets more valuable to me the more other Wazers there are out there in the world. They provide more traffic information. They let me know where the potholes and the construction are. So network effects lead to really kind of different competitive dynamics. They tend to lead toward more winner take all situations. They tend to lead toward things that look more like monopolies and that tends to freak some people out. I'm a little more calm about that because one of the things we also know from observing the high tech industries is that today's near monopolist is yesterday's also ran. We just see that over and over because complacency and inertia are so deadly there's always some disruptor coming up even in the high tech industries to make the incumbents nervous. Right, open source. Yeah, well open source and that's a perfect example of how some of the characteristics of goods in the digital economy are fundamentally different from earlier eras. In microeconomics we talk about rival and excludable goods and that's what you need for a competitive equilibrium. Digital goods are non-rival and non-excludable. You can go back to your microeconomics textbook for more detail on that but in essence what it means is that these goods can be freely copied at almost zero cost. Each copy is a perfect replica of the original. They can be transmitted anywhere on the planet almost instantaneously and that leads to a very different kind of economics than what we've had for the previous few hundred years. Are you doing work to quantify that? I mean, is that sort of... Yeah, well we're quantifying the effect on the economy more broadly but there's also very profound effects on business and the kinds of business models that work. You mentioned open source as an example. There are platform economics. Marshall Van Alstine, one of the experts in the field is speaking here today about that maybe we'll get a chance to talk to him a little bit later. You can sometimes make a lot of money by giving stuff away for free and gaining from complimentary goods. These are things that we can work. That's how we started. Yeah, well there you go. And that wouldn't work for you. You could only do that for a little while. You were a drug dealer. You could do that for a little while and then you'd get people addicted and then you'd start charging them a lot. There's a really different business model in the second machine age which is just give stuff away for free. You can make enough off other ancillary streams like advertising to have a large, very, very successful business. Okay, I wonder if we could sort of end the two things. I want to, first I want to talk about the constraints. What is the constraints to taking advantage of that innovation curve in the next era? Well, that's a great question. And less and less of the constraint is technological. More and more of the constraint is our ability as individuals to cope with the change. Because instead there's a race between technology and education. And an even more profound constraint is the ability of our organizations and our culture to adapt. We really see that as a bottleneck and at the MIT Sloan School, we're very much focused on trying to relieve those constraints. We've got some brilliant technologists that are inventing the future on the technology side but we've got to keep up with our business models, our economic systems and that's not happening fast enough. So let's think about where the technologies aren't and the constraints aren't and are. As Eric says, access to technology is vanishing as a constraint. Access to capital is vanishing as a constraint. At least to demonstrate or to start showing that you've got a good idea. Because of the cloud, because of Moore's law, a small team or a lone innovator can demonstrate the power of their idea and then ramp it up. So those are really vanishing. The constraints are mindset constraints, are institutional constraints and unfortunately increasingly, I believe regulatory constraints. Our colleague, Larry Lessig, has a great way to phrase the choice. He says, with our policies, with our regulations, we can protect the future from the past or we can protect the past from the future. That choice is really, really easy, right? The future is a better place. Let's protect that from the incumbents and the inertia of the past. So that leads us to sort of some of the proposals that you guys made in terms of how we can approach this. Good news is capitalism is not something that you're very much in favor of, you're not attacking. No Politburo, I think, was one of your comments. And some of the other things, actually I found pretty practical, although not likely, but practical, paying teachers more and more. Those are two different things, right? Yes, but still, feasible, certainly intellectually. But what have you seen in terms of the reaction to your proposals and do you have any confidence that public policy will begin to shape in a way that encourages you? We have confidence that the conversation is shifting. So just from the publication date to now, we've noticed there's a lot more willingness to engage with these ideas, with the ideas that tech progress is racing ahead, but leaving some people behind and more people behind in an economic sense over a time. So we've talked to politicians, we've talked to policy makers, we've talked to think tanks. That conversation is progressing. And if we want to change our government, if we want to change our policies, I think it has to start with changing the conversation. It's a bottom-up phenomenon. Any is exactly right. And that's really one of the key things that we learn. When we talk to our political science friends, they remind us that in America and other democracies, leaders are really followers. And they follow public opinion. And the people are the leaders. So we're not going to be able to get changes in our policies until we change the overall conversation. We get people recognizing the issues that are underway here. And I wouldn't be too quick to dismiss some of these bigger changes we described as possible in the book. I mean, historically, there have been some huge changes. The concept of mass public education was a pretty radical idea when it was introduced, the concept of social security. More recently, the concept of marriage equality was something I think people wouldn't have imagined maybe a decade or two ago. So you can have some big changes in the political conversation if it starts with what the people want. And ultimately, the leaders will follow. It's easy to get dismayed about the log jam in Washington. And I get dismayed once in a while. But I think back a decade ago, somebody had told me that gay marriage and legal marijuana would be pretty widespread in America. I would have laughed in their face. And I'm straight and I don't smoke dope. I think these are both fantastic developments and they came because the conversation shifted. Not because we had a gay pot smoker in the White House. Gentlemen, listen, thank you very much. First of all, for writing this great book. Yeah, Dave, I got one last question. So I understand you guys are working on your topic for your next book. Can you give us a little bit of a... some thoughts as to what you're thinking? Do we tip the hand? Well, sure, I think that it's no mystery that we teach at a business school and we spend a lot of time interacting with business leaders. And as we've mentioned in the discussion here, there have been some huge changes in the kind of business models that are successful in the Second Machine Age. We want to elaborate on those, describe not just what we're seeing when we talk to business leaders, but also what the economic theory says about what will and what won't work. So Second Machine Age is our attempt at like a big idea book. Let's write the business guide to the Second Machine Age. Awesome. Excellent. Well, first of all, the book is a big idea. A lot of big ideas in the book with excellent examples and some prescription, I think, for moving forward. So thank you for writing that book and congratulations on its success. Really appreciate you guys coming in theCUBE. Good luck today. And we look forward to talking to you in the future. Thanks for having us. It's been a real pleasure. Thank you. All right, keep it right there, everybody. We'll be right back. We're live from London. This is MIT IDE. This is theCUBE. Right back.