0:00:00.519,0:00:03.271 As it turns out, when tens of millions of people 0:00:03.271,0:00:05.599 are unemployed or underemployed, 0:00:05.599,0:00:09.726 there's a fair amount of interest in what technology might be doing to the labor force. 0:00:09.726,0:00:12.445 And as I look at the conversation, it strikes me 0:00:12.445,0:00:15.397 that it's focused on exactly the right topic, 0:00:15.397,0:00:18.375 and at the same time, it's missing the point entirely. 0:00:18.375,0:00:21.383 The topic that it's focused on, the question is whether or not 0:00:21.383,0:00:25.038 all these digital technologies are affecting people's ability 0:00:25.038,0:00:28.058 to earn a living, or, to say it a little bit different way, 0:00:28.058,0:00:30.336 are the droids taking our jobs? 0:00:30.336,0:00:32.304 And there's some evidence that they are. 0:00:32.304,0:00:36.657 The Great Recession ended when American GDP resumed 0:00:36.657,0:00:40.086 its kind of slow, steady march upward, and some other 0:00:40.101,0:00:43.035 economic indicators also started to rebound, and they got 0:00:43.035,0:00:45.897 kind of healthy kind of quickly. Corporate profits 0:00:45.897,0:00:49.173 are quite high. In fact, if you include bank profits, 0:00:49.173,0:00:51.285 they're higher than they've ever been. 0:00:51.285,0:00:54.557 And business investment in gear, in equipment 0:00:54.557,0:00:57.664 and hardware and software is at an all-time high. 0:00:57.664,0:01:01.045 So the businesses are getting out their checkbooks. 0:01:01.045,0:01:03.306 What they're not really doing is hiring. 0:01:03.306,0:01:07.007 So this red line is the employment-to-population ratio, 0:01:07.007,0:01:10.388 in other words, the percentage of working age people 0:01:10.388,0:01:12.279 in America who have work. 0:01:12.279,0:01:15.979 And we see that it cratered during the Great Recession, 0:01:15.979,0:01:18.843 and it hasn't started to bounce back at all. 0:01:18.843,0:01:21.350 But the story is not just a recession story. 0:01:21.350,0:01:24.347 The decade that we've just been through had relatively 0:01:24.347,0:01:27.740 anemic job growth all throughout, especially when we 0:01:27.740,0:01:30.675 compare it to other decades, and the 2000s 0:01:30.675,0:01:32.965 are the only time we have on record where there were 0:01:32.965,0:01:36.168 fewer people working at the end of the decade 0:01:36.168,0:01:39.228 than at the beginning. This is not what you want to see. 0:01:39.228,0:01:42.867 When you graph the number of potential employees 0:01:42.867,0:01:46.471 versus the number of jobs in the country, you see the gap 0:01:46.471,0:01:50.049 gets bigger and bigger over time, and then, 0:01:50.049,0:01:52.449 during the Great Recession, it opened up in a huge way. 0:01:52.449,0:01:56.859 I did some quick calculations. I took the last 20 years of GDP growth 0:01:56.859,0:02:00.155 and the last 20 years of labor productivity growth 0:02:00.155,0:02:02.897 and used those in a fairly straightforward way 0:02:02.897,0:02:05.523 to try to project how many jobs the economy was going 0:02:05.523,0:02:09.182 to need to keep growing, and this is the line that I came up with. 0:02:09.182,0:02:12.628 Is that good or bad? This is the government's projection 0:02:12.628,0:02:16.481 for the working age population going forward. 0:02:16.481,0:02:21.252 So if these predictions are accurate, that gap is not going to close. 0:02:21.252,0:02:24.653 The problem is, I don't think these projections are accurate. 0:02:24.653,0:02:28.009 In particular, I think my projection is way too optimistic, 0:02:28.009,0:02:31.365 because when I did it, I was assuming that the future 0:02:31.365,0:02:33.813 was kind of going to look like the past 0:02:33.813,0:02:37.252 with labor productivity growth, and that's actually not what I believe, 0:02:37.252,0:02:41.011 because when I look around, I think that we ain't seen nothing yet 0:02:41.011,0:02:44.296 when it comes to technology's impact on the labor force. 0:02:44.296,0:02:48.294 Just in the past couple years, we've seen digital tools 0:02:48.294,0:02:52.700 display skills and abilities that they never, ever had before, 0:02:52.700,0:02:56.488 and that, kind of, eat deeply into what we human beings 0:02:56.488,0:02:59.744 do for a living. Let me give you a couple examples. 0:02:59.744,0:03:01.755 Throughout all of history, if you wanted something 0:03:01.755,0:03:04.679 translated from one language into another, 0:03:04.679,0:03:06.343 you had to involve a human being. 0:03:06.343,0:03:09.759 Now we have multi-language, instantaneous, 0:03:09.759,0:03:13.977 automatic translation services available for free 0:03:13.977,0:03:17.366 via many of our devices all the way down to smartphones. 0:03:17.366,0:03:19.750 And if any of us have used these, we know that 0:03:19.750,0:03:23.071 they're not perfect, but they're decent. 0:03:23.071,0:03:26.222 Throughout all of history, if you wanted something written, 0:03:26.222,0:03:29.637 a report or an article, you had to involve a person. 0:03:29.637,0:03:31.889 Not anymore. This is an article that appeared 0:03:31.889,0:03:35.119 in Forbes online a while back about Apple's earnings. 0:03:35.119,0:03:37.646 It was written by an algorithm. 0:03:37.646,0:03:40.901 And it's not decent, it's perfect. 0:03:40.901,0:03:43.863 A lot of people look at this and they say, "Okay, 0:03:43.863,0:03:46.212 but those are very specific, narrow tasks, 0:03:46.212,0:03:48.845 and most knowledge workers are actually generalists, 0:03:48.845,0:03:51.374 and what they do is sit on top of a very large body 0:03:51.374,0:03:54.030 of expertise and knowledge and they use that 0:03:54.030,0:03:57.103 to react on the fly to kind of unpredictable demands, 0:03:57.103,0:03:59.591 and that's very, very hard to automate." 0:03:59.591,0:04:01.568 One of the most impressive knowledge workers 0:04:01.568,0:04:03.977 in recent memory is a guy named Ken Jennings. 0:04:03.977,0:04:09.035 He won the quiz show "Jeopardy!" 74 times in a row, 0:04:09.035,0:04:11.663 took home three million dollars. 0:04:11.663,0:04:15.513 That's Ken on the right getting beat three to one by 0:04:15.513,0:04:20.317 Watson, the "Jeopardy!"-playing supercomputer from IBM. 0:04:20.317,0:04:22.181 So when we look at what technology can do 0:04:22.181,0:04:25.054 to general knowledge workers, I start to think 0:04:25.054,0:04:27.653 there might not be something so special about this idea 0:04:27.653,0:04:30.541 of a generalist, particularly when we start doing things 0:04:30.541,0:04:34.529 like hooking Siri up to Watson and having technologies 0:04:34.529,0:04:36.425 that can understand what we're saying 0:04:36.425,0:04:38.506 and repeat speech back to us. 0:04:38.506,0:04:41.344 Now, Siri is far from perfect, and we can make fun 0:04:41.344,0:04:44.363 of her flaws, but we should also keep in mind that 0:04:44.363,0:04:47.039 if technologies like Siri and Watson improve 0:04:47.039,0:04:50.820 along a Moore's Law trajectory, which they will, 0:04:50.820,0:04:53.404 in six years, they're not going to be two times better 0:04:53.404,0:04:58.222 or four times better, they'll be 16 times better than they are right now. 0:04:58.222,0:05:01.905 So I start to think that a lot of knowledge work is going to be affected by this. 0:05:01.905,0:05:05.459 And digital technologies are not just impacting knowledge work. 0:05:05.459,0:05:09.451 They're starting to flex their muscles in the physical world as well. 0:05:09.451,0:05:11.900 I had the chance a little while back to ride in the Google 0:05:11.900,0:05:17.426 autonomous car, which is as cool as it sounds. (Laughter) 0:05:17.426,0:05:20.453 And I will vouch that it handled the stop-and-go traffic 0:05:20.453,0:05:23.358 on U.S. 101 very smoothly. 0:05:23.358,0:05:25.323 There are about three and a half million people 0:05:25.323,0:05:27.532 who drive trucks for a living in the United States. 0:05:27.532,0:05:29.961 I think some of them are going to be affected by this 0:05:29.961,0:05:33.213 technology. And right now, humanoid robots are still 0:05:33.213,0:05:36.471 incredibly primitive. They can't do very much. 0:05:36.471,0:05:39.052 But they're getting better quite quickly, and DARPA, 0:05:39.052,0:05:42.203 which is the investment arm of the Defense Department, 0:05:42.203,0:05:43.868 is trying to accelerate their trajectory. 0:05:43.868,0:05:48.551 So, in short, yeah, the droids are coming for our jobs. 0:05:48.551,0:05:52.431 In the short term, we can stimulate job growth 0:05:52.431,0:05:55.375 by encouraging entrepreneurship and by investing 0:05:55.375,0:05:58.423 in infrastructure, because the robots today still aren't 0:05:58.423,0:06:00.163 very good at fixing bridges. 0:06:00.163,0:06:03.528 But in the not-too-long-term, I think within the lifetimes 0:06:03.528,0:06:07.097 of most of the people in this room, we're going to transition 0:06:07.097,0:06:10.033 into an economy that is very productive but that 0:06:10.033,0:06:12.837 just doesn't need a lot of human workers, 0:06:12.837,0:06:14.392 and managing that transition is going to be 0:06:14.392,0:06:17.131 the greatest challenge that our society faces. 0:06:17.131,0:06:19.893 Voltaire summarized why. He said, "Work saves us 0:06:19.893,0:06:25.170 from three great evils: boredom, vice and need." 0:06:25.170,0:06:27.741 But despite this challenge, I'm personally, 0:06:27.741,0:06:30.790 I'm still a huge digital optimist, and I am 0:06:30.790,0:06:33.977 supremely confident that the digital technologies that we're 0:06:33.977,0:06:37.533 developing now are going to take us into a utopian future, 0:06:37.533,0:06:40.566 not a dystopian future. And to explain why, 0:06:40.566,0:06:43.088 I want to pose kind of a ridiculously broad question. 0:06:43.088,0:06:45.438 I want to ask what have been the most important 0:06:45.438,0:06:47.761 developments in human history? 0:06:47.761,0:06:50.494 Now, I want to share some of the answers that I've gotten 0:06:50.494,0:06:52.671 in response to this question. It's a wonderful question 0:06:52.671,0:06:54.838 to ask and to start an endless debate about, 0:06:54.838,0:06:57.159 because some people are going to bring up 0:06:57.159,0:07:00.619 systems of philosophy in both the West and the East that 0:07:00.619,0:07:03.752 have changed how a lot of people think about the world. 0:07:03.752,0:07:06.588 And then other people will say, "No, actually, the big stories, 0:07:06.588,0:07:09.011 the big developments are the founding of the world's 0:07:09.011,0:07:12.293 major religions, which have changed civilizations 0:07:12.293,0:07:14.932 and have changed and influenced how countless people 0:07:14.932,0:07:17.936 are living their lives." And then some other folk will say, 0:07:17.936,0:07:21.463 "Actually, what changes civilizations, what modifies them 0:07:21.463,0:07:23.626 and what changes people's lives 0:07:23.626,0:07:27.538 are empires, so the great developments in human history 0:07:27.538,0:07:30.373 are stories of conquest and of war." 0:07:30.373,0:07:32.963 And then some cheery soul usually always pipes up 0:07:32.963,0:07:38.651 and says, "Hey, don't forget about plagues." (Laughter) 0:07:38.651,0:07:41.554 There are some optimistic answers to this question, 0:07:41.554,0:07:43.451 so some people will bring up the Age of Exploration 0:07:43.451,0:07:45.399 and the opening up of the world. 0:07:45.399,0:07:47.501 Others will talk about intellectual achievements 0:07:47.501,0:07:49.776 in disciplines like math that have helped us get 0:07:49.776,0:07:53.086 a better handle on the world, and other folk will talk about 0:07:53.086,0:07:54.783 periods when there was a deep flourishing 0:07:54.783,0:07:58.585 of the arts and sciences. So this debate will go on and on. 0:07:58.585,0:08:01.424 It's an endless debate, and there's no conclusive, 0:08:01.424,0:08:04.676 no single answer to it. But if you're a geek like me, 0:08:04.676,0:08:07.574 you say, "Well, what do the data say?" 0:08:07.574,0:08:10.385 And you start to do things like graph things that we might 0:08:10.385,0:08:14.488 be interested in, the total worldwide population, for example, 0:08:14.488,0:08:17.129 or some measure of social development, 0:08:17.129,0:08:19.640 or the state of advancement of a society, 0:08:19.640,0:08:23.473 and you start to plot the data, because, by this approach, 0:08:23.473,0:08:26.090 the big stories, the big developments in human history, 0:08:26.090,0:08:28.951 are the ones that will bend these curves a lot. 0:08:28.951,0:08:30.863 So when you do this, and when you plot the data, 0:08:30.863,0:08:33.661 you pretty quickly come to some weird conclusions. 0:08:33.661,0:08:36.584 You conclude, actually, that none of these things 0:08:36.584,0:08:41.536 have mattered very much. (Laughter) 0:08:41.536,0:08:45.562 They haven't done a darn thing to the curves. (Laughter) 0:08:45.562,0:08:49.146 There has been one story, one development 0:08:49.146,0:08:51.752 in human history that bent the curve, bent it just about 0:08:51.752,0:08:55.798 90 degrees, and it is a technology story. 0:08:55.798,0:08:58.757 The steam engine, and the other associated technologies 0:08:58.757,0:09:01.688 of the Industrial Revolution changed the world 0:09:01.688,0:09:04.112 and influenced human history so much, 0:09:04.112,0:09:06.195 that in the words of the historian Ian Morris, 0:09:06.195,0:09:10.272 they made mockery out of all that had come before. 0:09:10.272,0:09:13.185 And they did this by infinitely multiplying the power 0:09:13.185,0:09:16.322 of our muscles, overcoming the limitations of our muscles. 0:09:16.322,0:09:18.844 Now, what we're in the middle of now 0:09:18.844,0:09:21.763 is overcoming the limitations of our individual brains 0:09:21.763,0:09:24.836 and infinitely multiplying our mental power. 0:09:24.836,0:09:28.536 How can this not be as big a deal as overcoming 0:09:28.536,0:09:31.064 the limitations of our muscles? 0:09:31.064,0:09:34.442 So at the risk of repeating myself a little bit, when I look 0:09:34.442,0:09:37.271 at what's going on with digital technology these days, 0:09:37.271,0:09:40.097 we are not anywhere near through with this journey, 0:09:40.097,0:09:42.771 and when I look at what is happening to our economies 0:09:42.771,0:09:45.424 and our societies, my single conclusion is that 0:09:45.424,0:09:48.952 we ain't seen nothing yet. The best days are really ahead. 0:09:48.952,0:09:50.708 Let me give you a couple examples. 0:09:50.708,0:09:54.936 Economies don't run on energy. They don't run on capital, 0:09:54.936,0:09:58.716 they don't run on labor. Economies run on ideas. 0:09:58.716,0:10:01.236 So the work of innovation, the work of coming up with 0:10:01.236,0:10:03.662 new ideas, is some of the most powerful, 0:10:03.662,0:10:05.477 some of the most fundamental work that we can do 0:10:05.477,0:10:09.493 in an economy. And this is kind of how we used to do innovation. 0:10:09.493,0:10:13.271 We'd find a bunch of fairly similar-looking people 0:10:13.271,0:10:16.682 — (Laughter) — 0:10:16.682,0:10:19.211 we'd take them out of elite institutions, we'd put them into 0:10:19.211,0:10:22.157 other elite institutions, and we'd wait for the innovation. 0:10:22.157,0:10:26.167 Now — (Laughter) — 0:10:26.167,0:10:28.748 as a white guy who spent his whole career at MIT 0:10:28.748,0:10:35.114 and Harvard, I got no problem with this. (Laughter) 0:10:35.114,0:10:37.730 But some other people do, and they've kind of crashed 0:10:37.730,0:10:40.266 the party and loosened up the dress code of innovation. 0:10:40.266,0:10:41.190 (Laughter) 0:10:41.190,0:10:44.834 So here are the winners of a Top Coder programming challenge, 0:10:44.834,0:10:47.736 and I assure you that nobody cares 0:10:47.736,0:10:51.330 where these kids grew up, where they went to school, 0:10:51.330,0:10:53.818 or what they look like. All anyone cares about 0:10:53.818,0:10:56.639 is the quality of the work, the quality of the ideas. 0:10:56.639,0:10:58.805 And over and over again, we see this happening 0:10:58.805,0:11:01.151 in the technology-facilitated world. 0:11:01.151,0:11:03.607 The work of innovation is becoming more open, 0:11:03.607,0:11:07.385 more inclusive, more transparent, and more merit-based, 0:11:07.385,0:11:10.354 and that's going to continue no matter what MIT and Harvard 0:11:10.354,0:11:14.034 think of it, and I couldn't be happier about that development. 0:11:14.034,0:11:16.484 I hear once in a while, "Okay, I'll grant you that, 0:11:16.484,0:11:19.871 but technology is still a tool for the rich world, 0:11:19.871,0:11:22.585 and what's not happening, these digital tools are not 0:11:22.585,0:11:25.940 improving the lives of people at the bottom of the pyramid." 0:11:25.940,0:11:28.604 And I want to say to that very clearly: nonsense. 0:11:28.604,0:11:32.042 The bottom of the pyramid is benefiting hugely from technology. 0:11:32.042,0:11:34.682 The economist Robert Jensen did this wonderful study 0:11:34.682,0:11:37.850 a while back where he watched, in great detail, 0:11:37.850,0:11:41.231 what happened to the fishing villages of Kerala, India, 0:11:41.231,0:11:44.244 when they got mobile phones for the very first time, 0:11:44.244,0:11:46.975 and when you write for the Quarterly Journal of Economics, 0:11:46.975,0:11:49.872 you have to use very dry and very circumspect language, 0:11:49.872,0:11:52.344 but when I read his paper, I kind of feel Jensen is trying 0:11:52.344,0:11:55.365 to scream at us, and say, look, this was a big deal. 0:11:55.365,0:11:59.418 Prices stabilized, so people could plan their economic lives. 0:11:59.418,0:12:03.541 Waste was not reduced; it was eliminated. 0:12:03.541,0:12:06.012 And the lives of both the buyers and the sellers 0:12:06.012,0:12:08.510 in these villages measurably improved. 0:12:08.510,0:12:12.226 Now, what I don't think is that Jensen got extremely lucky 0:12:12.226,0:12:14.580 and happened to land in the one set of villages 0:12:14.580,0:12:17.092 where technology made things better. 0:12:17.092,0:12:19.695 What happened instead is he very carefully documented 0:12:19.695,0:12:22.387 what happens over and over again when technology 0:12:22.387,0:12:25.651 comes for the first time to an environment and a community. 0:12:25.651,0:12:29.615 The lives of people, the welfares of people, improve dramatically. 0:12:29.615,0:12:31.971 So as I look around at all the evidence, and I think about 0:12:31.971,0:12:34.447 the room that we have ahead of us, I become a huge 0:12:34.447,0:12:37.271 digital optimist, and I start to think that this wonderful 0:12:37.271,0:12:40.326 statement from the physicist Freeman Dyson 0:12:40.326,0:12:44.904 is actually not hyperbole. This is an accurate assessment of what's going on. 0:12:44.904,0:12:47.350 Our digital -- our technologies are great gifts, 0:12:47.350,0:12:50.511 and we, right now, have the great good fortune 0:12:50.511,0:12:54.036 to be living at a time when digital technology is flourishing, 0:12:54.036,0:12:55.694 when it is broadening and deepening and 0:12:55.694,0:12:59.035 becoming more profound all around the world. 0:12:59.035,0:13:02.253 So, yeah, the droids are taking our jobs, 0:13:02.253,0:13:06.066 but focusing on that fact misses the point entirely. 0:13:06.066,0:13:09.319 The point is that then we are freed up to do other things, 0:13:09.319,0:13:11.977 and what we are going to do, I am very confident, 0:13:11.977,0:13:15.040 what we're going to do is reduce poverty and drudgery 0:13:15.040,0:13:17.704 and misery around the world. I'm very confident 0:13:17.704,0:13:20.736 we're going to learn to live more lightly on the planet, 0:13:20.736,0:13:24.217 and I am extremely confident that what we're going to do 0:13:24.217,0:13:27.138 with our new digital tools is going to be so profound 0:13:27.138,0:13:30.029 and so beneficial that it's going to make a mockery 0:13:30.029,0:13:31.762 out of everything that came before. 0:13:31.762,0:13:34.500 I'm going to leave the last word to a guy who had 0:13:34.500,0:13:36.278 a front row seat for digital progress, 0:13:36.278,0:13:38.843 our old friend Ken Jennings. I'm with him. 0:13:38.843,0:13:40.204 I'm going to echo his words: 0:13:40.204,0:13:44.175 "I, for one, welcome our new computer overlords." (Laughter) 0:13:44.175,0:13:47.104 Thanks very much. (Applause)