1 00:00:06,950 --> 00:00:09,910 We're speaking today with Eric Brynjolfsson, a professor here 2 00:00:09,910 --> 00:00:11,950 at MIT Sloan School of Management, 3 00:00:11,950 --> 00:00:15,520 the director of the MIT Initiative on the Digital 4 00:00:15,520 --> 00:00:18,520 Economy, and co-author of a bestselling book, 5 00:00:18,520 --> 00:00:21,510 The Second Machine Age, a book that really 6 00:00:21,510 --> 00:00:23,270 has gotten the conversation going 7 00:00:23,270 --> 00:00:27,290 about how important today's digital economy is, 8 00:00:27,290 --> 00:00:29,480 how the technologies that are coming along 9 00:00:29,480 --> 00:00:32,350 are going to have an enormous effect on the future of work. 10 00:00:32,350 --> 00:00:34,260 So Eric, thank you for joining us. 11 00:00:34,260 --> 00:00:35,260 It's a real pleasure. 12 00:00:35,260 --> 00:00:35,770 Good. 13 00:00:35,770 --> 00:00:36,810 Let's get started. 14 00:00:36,810 --> 00:00:39,880 Why don't you tell us why you think 15 00:00:39,880 --> 00:00:43,780 the current technological wave of innovation 16 00:00:43,780 --> 00:00:47,530 is as important as the first Industrial Revolution, 17 00:00:47,530 --> 00:00:50,035 with the steam engine and all the things that went with it. 18 00:00:50,035 --> 00:00:51,410 Well, you know, technologies make 19 00:00:51,410 --> 00:00:53,576 a huge difference in the living standards of people. 20 00:00:53,576 --> 00:00:56,010 For centuries, living standards were essentially stagnant 21 00:00:56,010 --> 00:00:58,870 until James Watt and others developed a better steam 22 00:00:58,870 --> 00:01:01,340 engine, and that ignited the Industrial Revolution. 23 00:01:01,340 --> 00:01:03,330 And ever since then, living standards 24 00:01:03,330 --> 00:01:07,710 have been growing about 2% per year, which adds up to a lot. 25 00:01:07,710 --> 00:01:09,810 What those technologies really did 26 00:01:09,810 --> 00:01:12,650 was they augmented and automated a lot 27 00:01:12,650 --> 00:01:17,280 of muscle power from humans and animals to machines. 28 00:01:17,280 --> 00:01:19,320 What we're seeing now is that machines 29 00:01:19,320 --> 00:01:21,400 are beginning to be able to do the same thing 30 00:01:21,400 --> 00:01:23,370 for our brains and our minds. 31 00:01:23,370 --> 00:01:26,240 We have computers and software and big data 32 00:01:26,240 --> 00:01:29,300 that are learning how to help us make decisions, 33 00:01:29,300 --> 00:01:31,490 how to extend our mental capacity. 34 00:01:31,490 --> 00:01:36,260 And that's at least as profound a difference as what the steam 35 00:01:36,260 --> 00:01:38,230 engine and, later, the internal combustion 36 00:01:38,230 --> 00:01:40,650 engine and other technologies did for our muscles. 37 00:01:40,650 --> 00:01:46,040 Well, it's very clear that technological changes like this 38 00:01:46,040 --> 00:01:49,650 are very good for the economy, but they also affect work. 39 00:01:49,650 --> 00:01:53,150 Tell us a little bit about how technologies affect 40 00:01:53,150 --> 00:01:55,970 work in what ways-- in positive ways, in negative ways-- 41 00:01:55,970 --> 00:01:57,521 and then we can go on from there. 42 00:01:57,521 --> 00:01:58,020 Sure. 43 00:01:58,020 --> 00:01:59,510 Well, the big headline is the first one 44 00:01:59,510 --> 00:02:01,500 you mentioned, that the pie is getting bigger. 45 00:02:01,500 --> 00:02:03,830 And so we have to keep sight of that, 46 00:02:03,830 --> 00:02:06,040 that basically these are technologies that create 47 00:02:06,040 --> 00:02:08,090 more abundance, more wealth. 48 00:02:08,090 --> 00:02:10,990 And there's more wealth now than there ever has been in history, 49 00:02:10,990 --> 00:02:12,690 and global poverty is going down. 50 00:02:12,690 --> 00:02:13,960 So that's the good news. 51 00:02:13,960 --> 00:02:16,400 But the reality is that there's no economic law that 52 00:02:16,400 --> 00:02:19,030 says that everyone's going to benefit evenly from this. 53 00:02:19,030 --> 00:02:22,210 It's possible for some people to be made worse off. 54 00:02:22,210 --> 00:02:24,219 In fact, there's no economic reason 55 00:02:24,219 --> 00:02:26,010 that you couldn't have a majority of people 56 00:02:26,010 --> 00:02:29,654 be made worse off, even as other people get much, much better. 57 00:02:29,654 --> 00:02:31,070 Through most of history, there was 58 00:02:31,070 --> 00:02:34,380 a rising tide that lifted most boats, almost all boats. 59 00:02:34,380 --> 00:02:37,240 But in the past 20 years or so, there's 60 00:02:37,240 --> 00:02:40,310 been what we call a decoupling, where productivity 61 00:02:40,310 --> 00:02:43,700 has continued to grow, GDP per capita has continued to grow, 62 00:02:43,700 --> 00:02:47,160 but the median income, the 50th percentile and those below it, 63 00:02:47,160 --> 00:02:50,320 have seen their incomes stagnate or even fall. 64 00:02:50,320 --> 00:02:53,060 And that reflects the fact that these technologies 65 00:02:53,060 --> 00:02:55,770 don't affect everybody evenly. 66 00:02:55,770 --> 00:02:57,300 So let's play this out. 67 00:02:57,300 --> 00:03:00,560 How do you see these technologies affecting work 68 00:03:00,560 --> 00:03:02,100 in the future? 69 00:03:02,100 --> 00:03:04,834 Well, the technologies continue to advance, 70 00:03:04,834 --> 00:03:07,000 and they continue to affect different kinds of jobs. 71 00:03:07,000 --> 00:03:09,680 But what really matters is how we go about using them. 72 00:03:09,680 --> 00:03:12,580 What we've seen so far is that many of the technologies 73 00:03:12,580 --> 00:03:14,910 have been used to automate a lot of routine 74 00:03:14,910 --> 00:03:19,410 information-processing work, things like bank tellers, 75 00:03:19,410 --> 00:03:22,160 bookkeepers, a lot of middle managers. 76 00:03:22,160 --> 00:03:25,070 In fact, about 60% of Americans primarily 77 00:03:25,070 --> 00:03:27,850 do information-processing work, so that's a big category. 78 00:03:27,850 --> 00:03:29,992 And machines are very good at automating 79 00:03:29,992 --> 00:03:31,450 a lot of these, especially the more 80 00:03:31,450 --> 00:03:34,090 repetitive, routine information-processing tasks. 81 00:03:34,090 --> 00:03:37,632 It turns out that the people who do those jobs are typically 82 00:03:37,632 --> 00:03:39,340 in the middle of the income distribution, 83 00:03:39,340 --> 00:03:41,600 and what they've seen is that as machines get better 84 00:03:41,600 --> 00:03:44,010 at those tasks, there's less demand for humans 85 00:03:44,010 --> 00:03:45,290 to do the identical tasks. 86 00:03:45,290 --> 00:03:47,579 Or if they do still have jobs, they 87 00:03:47,579 --> 00:03:49,620 have to compete with machines that are doing them 88 00:03:49,620 --> 00:03:50,840 more and more cheaply. 89 00:03:50,840 --> 00:03:53,160 And that his pushed down wages. 90 00:03:53,160 --> 00:03:54,980 It's led to fewer job opportunities 91 00:03:54,980 --> 00:03:56,750 in those categories. 92 00:03:56,750 --> 00:03:59,810 At the same time, there's been growth in job opportunities 93 00:03:59,810 --> 00:04:02,170 at the other ends of the spectrum, what 94 00:04:02,170 --> 00:04:06,010 David Autor and other people call job polarization. 95 00:04:06,010 --> 00:04:09,210 At the high end, you get creative people 96 00:04:09,210 --> 00:04:11,294 or entrepreneurs are making, in some cases, 97 00:04:11,294 --> 00:04:12,460 more money than ever before. 98 00:04:12,460 --> 00:04:13,990 It's probably the best time in history. 99 00:04:13,990 --> 00:04:15,650 If you have some kind of special talent 100 00:04:15,650 --> 00:04:17,470 that could be replicated digitally, 101 00:04:17,470 --> 00:04:19,640 you might end up being a billionaire. 102 00:04:19,640 --> 00:04:22,670 On the other hand, the other end of the spectrum 103 00:04:22,670 --> 00:04:24,930 has also seen some growth, and those 104 00:04:24,930 --> 00:04:29,150 are jobs that require a lot of dexterity or physical tasks 105 00:04:29,150 --> 00:04:31,300 or interpersonal skills, things that machines 106 00:04:31,300 --> 00:04:32,320 aren't very good at. 107 00:04:32,320 --> 00:04:34,720 The thing is, often those jobs don't pay very well. 108 00:04:34,720 --> 00:04:36,770 And just to be specific, those are the kinds 109 00:04:36,770 --> 00:04:40,860 of jobs like a waiter or a gardener 110 00:04:40,860 --> 00:04:43,080 or a janitor, those kinds of tasks. 111 00:04:43,080 --> 00:04:46,140 So what is your advice, then, to workers 112 00:04:46,140 --> 00:04:48,940 facing this world of changing technology? 113 00:04:48,940 --> 00:04:51,150 What should they do in order to be 114 00:04:51,150 --> 00:04:53,530 able to prosper in this world? 115 00:04:53,530 --> 00:04:55,750 Well, what you'd like to try to do 116 00:04:55,750 --> 00:04:59,180 is strengthen those areas where humans have 117 00:04:59,180 --> 00:05:00,306 an advantage over machines. 118 00:05:00,306 --> 00:05:02,596 You don't really want to be competing against machines. 119 00:05:02,596 --> 00:05:04,580 Ideally, you'd like to do things were machines 120 00:05:04,580 --> 00:05:06,120 can leverage your talents. 121 00:05:06,120 --> 00:05:07,944 Data scientists are more in demand 122 00:05:07,944 --> 00:05:09,360 than ever before, because machines 123 00:05:09,360 --> 00:05:11,250 have created an abundance of data, 124 00:05:11,250 --> 00:05:12,580 but they can't analyze it. 125 00:05:12,580 --> 00:05:15,380 They can't even ask the right questions themselves. 126 00:05:15,380 --> 00:05:16,870 You need humans to do that. 127 00:05:16,870 --> 00:05:18,990 And so if you have those kinds of skills, 128 00:05:18,990 --> 00:05:20,390 you're more valuable than ever. 129 00:05:20,390 --> 00:05:22,650 And Silicon Valley, and now companies 130 00:05:22,650 --> 00:05:24,550 throughout the country and the world, 131 00:05:24,550 --> 00:05:27,830 are greatly demanding those kinds of workers. 132 00:05:27,830 --> 00:05:29,960 And so there's a set of categories around that. 133 00:05:29,960 --> 00:05:32,501 I mentioned earlier, if you have some kind of special talents 134 00:05:32,501 --> 00:05:35,180 or creativity, machines aren't very creative. 135 00:05:35,180 --> 00:05:39,790 People who can sing well or who can invent new businesses, 136 00:05:39,790 --> 00:05:44,470 as entrepreneurs, many kinds of scientists, artists, 137 00:05:44,470 --> 00:05:46,940 if you're a great writer or write books, 138 00:05:46,940 --> 00:05:48,990 those are things that are probably 139 00:05:48,990 --> 00:05:50,870 more valuable now than before. 140 00:05:50,870 --> 00:05:53,670 Another big category that's gotten to be more valuable is-- 141 00:05:53,670 --> 00:05:55,480 I touched on it earlier-- is some of these interpersonal 142 00:05:55,480 --> 00:05:56,120 skills-- 143 00:05:56,120 --> 00:05:58,310 nurturing and caring. 144 00:05:58,310 --> 00:06:01,750 I don't think it would have been very motivating 145 00:06:01,750 --> 00:06:04,930 if, at the half time of the football games last weekend, 146 00:06:04,930 --> 00:06:06,760 the coach had been a robot coach. 147 00:06:06,760 --> 00:06:08,830 You need a human to do that. 148 00:06:08,830 --> 00:06:11,770 And that means that leadership, team work, 149 00:06:11,770 --> 00:06:12,860 those kinds of things. 150 00:06:12,860 --> 00:06:15,500 We still connect with other people a lot better, 151 00:06:15,500 --> 00:06:17,030 and we will for some time. 152 00:06:17,030 --> 00:06:19,780 And I think all those skills, from the creative ones 153 00:06:19,780 --> 00:06:22,650 to the interpersonal, the teamwork, the nurturing skills, 154 00:06:22,650 --> 00:06:23,890 they can all be developed. 155 00:06:23,890 --> 00:06:26,090 And I would encourage people to work harder 156 00:06:26,090 --> 00:06:27,990 at developing those kinds of skills. 157 00:06:27,990 --> 00:06:31,110 Become a better salesperson, negotiator, nurturing, 158 00:06:31,110 --> 00:06:34,180 caring for people, nursing. 159 00:06:34,180 --> 00:06:36,310 Those are all things that I expect to grow, 160 00:06:36,310 --> 00:06:37,940 even as machines take care of more 161 00:06:37,940 --> 00:06:41,210 and more of the routine, repetitive kinds of tasks. 162 00:06:41,210 --> 00:06:45,030 So that's great advice to the workforce. 163 00:06:45,030 --> 00:06:46,910 Let's talk a bit about the people who are 164 00:06:46,910 --> 00:06:48,820 designing these technologies. 165 00:06:48,820 --> 00:06:54,420 How can we encourage more technological design 166 00:06:54,420 --> 00:06:57,940 that complements work, that utilizes these skills, that 167 00:06:57,940 --> 00:07:00,220 thinks about ways to enhance them 168 00:07:00,220 --> 00:07:04,910 or to work with them to drive productivity 169 00:07:04,910 --> 00:07:06,246 and economic performance? 170 00:07:06,246 --> 00:07:07,870 Well, I'm glad you asked that question, 171 00:07:07,870 --> 00:07:09,286 because most people don't even get 172 00:07:09,286 --> 00:07:10,706 as far as asking that question. 173 00:07:10,706 --> 00:07:12,330 I think there's a widespread assumption 174 00:07:12,330 --> 00:07:14,150 out there that technology just happens, 175 00:07:14,150 --> 00:07:16,600 and there's nothing you can do to shape the path of it. 176 00:07:16,600 --> 00:07:19,300 The reality is that you can encourage people 177 00:07:19,300 --> 00:07:23,580 to have technologies that create more inclusive innovation, that 178 00:07:23,580 --> 00:07:25,800 helps people more broadly, or that 179 00:07:25,800 --> 00:07:28,940 mostly focuses on substituting for people, for that matter. 180 00:07:28,940 --> 00:07:31,670 And we, as a society and as individuals, 181 00:07:31,670 --> 00:07:33,490 can shape the direction of technology 182 00:07:33,490 --> 00:07:36,160 to quite a significant extent. 183 00:07:36,160 --> 00:07:39,810 One of the things we can do is change around our tax policy 184 00:07:39,810 --> 00:07:42,130 and our government policies. 185 00:07:42,130 --> 00:07:44,250 One of the oldest rules of economics 186 00:07:44,250 --> 00:07:47,350 is if you want less of something, you tax it. 187 00:07:47,350 --> 00:07:49,350 If you want more of something, you subsidize it. 188 00:07:49,350 --> 00:07:52,650 Right now, ironically, we are taxing work. 189 00:07:52,650 --> 00:07:57,400 If two entrepreneurs come up with a billion-dollar idea, 190 00:07:57,400 --> 00:07:59,510 and one of them involves employing lots of people 191 00:07:59,510 --> 00:08:01,630 and one of them doesn't, our current tax system 192 00:08:01,630 --> 00:08:04,620 will put more taxes on the one that employs more people, 193 00:08:04,620 --> 00:08:06,510 and that's probably not we want to do. 194 00:08:06,510 --> 00:08:09,919 Conversely, we don't tax pollution, carbon, congestion, 195 00:08:09,919 --> 00:08:11,460 things that we'd like to see less of. 196 00:08:11,460 --> 00:08:12,918 So we could rejigger the tax system 197 00:08:12,918 --> 00:08:15,130 to tax the things that we don't want more, 198 00:08:15,130 --> 00:08:22,460 and then we'll have less of them, and lower the taxes, 199 00:08:22,460 --> 00:08:24,410 or even subsidize, work. 200 00:08:24,410 --> 00:08:26,510 And I think that would guide entrepreneurs 201 00:08:26,510 --> 00:08:28,120 to be more creative about inventing 202 00:08:28,120 --> 00:08:31,650 things that have less pollution and more widespread labor. 203 00:08:31,650 --> 00:08:35,210 The Earned Income Tax Credit is a good example, but too small. 204 00:08:35,210 --> 00:08:36,816 Could be expanded at that. 205 00:08:36,816 --> 00:08:38,190 Another kind of thing we could do 206 00:08:38,190 --> 00:08:42,030 is just recognize reward and motivate people. 207 00:08:42,030 --> 00:08:45,030 One of the things that I've learned over the past few years 208 00:08:45,030 --> 00:08:47,330 is how much people can be motivated 209 00:08:47,330 --> 00:08:49,490 by having a prize and a goal in front of them. 210 00:08:49,490 --> 00:08:51,660 I've been watching the DARPA Robotics 211 00:08:51,660 --> 00:08:53,930 Challenge, the DARPA Grand Challenge that 212 00:08:53,930 --> 00:08:55,640 led to the driverless car. 213 00:08:55,640 --> 00:08:57,620 And I see my colleagues in engineering, 214 00:08:57,620 --> 00:09:00,412 grad students, professors working nights and weekends 215 00:09:00,412 --> 00:09:02,870 to solve this challenge that has been put in front of them. 216 00:09:02,870 --> 00:09:05,170 And many times, they do come around 217 00:09:05,170 --> 00:09:07,550 to making huge strides in that. 218 00:09:07,550 --> 00:09:09,920 Why don't we try to reward and motivate 219 00:09:09,920 --> 00:09:13,090 business leaders and economists to reinvent 220 00:09:13,090 --> 00:09:15,150 the businesses and economy the same way 221 00:09:15,150 --> 00:09:17,820 that technologists have been reinventing the technology? 222 00:09:17,820 --> 00:09:20,140 And in fact, here at MIT, we're launching something 223 00:09:20,140 --> 00:09:23,140 called the Inclusive Innovation Competition, which 224 00:09:23,140 --> 00:09:25,690 is designed specifically to recognize those business 225 00:09:25,690 --> 00:09:29,060 models that use technology to create broad, 226 00:09:29,060 --> 00:09:30,190 shared prosperity. 227 00:09:30,190 --> 00:09:34,370 We call it shared prosperity for the many, not just the few. 228 00:09:34,370 --> 00:09:36,070 It's just getting launched, but we 229 00:09:36,070 --> 00:09:39,720 think this is going to be a good way to recognize and highlight 230 00:09:39,720 --> 00:09:40,830 people who have done that. 231 00:09:40,830 --> 00:09:42,280 I think that's a great idea, and I 232 00:09:42,280 --> 00:09:45,130 hope that it creates a lot of attention, 233 00:09:45,130 --> 00:09:49,380 and that we get lots of people really thinking along 234 00:09:49,380 --> 00:09:55,630 these ways, because I think it's the genius of people-- 235 00:09:55,630 --> 00:09:59,560 using technologies to address important problems that 236 00:09:59,560 --> 00:10:01,940 will help make progress. 237 00:10:01,940 --> 00:10:03,550 Yeah, and we all have choices. 238 00:10:03,550 --> 00:10:05,560 We can shape the future in that direction. 239 00:10:05,560 --> 00:10:06,990 And why don't we encourage people 240 00:10:06,990 --> 00:10:09,370 who are doing it in a way that does create this shared 241 00:10:09,370 --> 00:10:10,960 prosperity? 242 00:10:10,960 --> 00:10:13,640 So let me ask this final question, because it's 243 00:10:13,640 --> 00:10:15,260 obviously on everybody's mind. 244 00:10:15,260 --> 00:10:18,560 And that is, from time to time in history, 245 00:10:18,560 --> 00:10:21,160 as you know better than I, people have worried 246 00:10:21,160 --> 00:10:23,490 that technology is going to replace work, 247 00:10:23,490 --> 00:10:24,870 it's going to be the end of work, 248 00:10:24,870 --> 00:10:26,500 we're not going to have enough jobs. 249 00:10:26,500 --> 00:10:30,010 And that's an issue on people's mind today. 250 00:10:30,010 --> 00:10:32,140 How do you think about that problem, given 251 00:10:32,140 --> 00:10:34,720 all of the innovation that's going on 252 00:10:34,720 --> 00:10:36,620 and that could come down the road? 253 00:10:36,620 --> 00:10:39,760 Well, down the road, I could certainly 254 00:10:39,760 --> 00:10:42,611 imagine technology creating kind of a Star Trek economy. 255 00:10:42,611 --> 00:10:44,610 And I don't think that's necessarily a bad thing 256 00:10:44,610 --> 00:10:47,440 if technology's able to take care of all of our basic needs 257 00:10:47,440 --> 00:10:48,000 for us. 258 00:10:48,000 --> 00:10:50,090 But the more immediate issue is not 259 00:10:50,090 --> 00:10:51,640 that technology is going to eliminate 260 00:10:51,640 --> 00:10:54,330 all the jobs, but the types of jobs that are affected. 261 00:10:54,330 --> 00:10:58,090 The reality is that technology's always been destroying jobs. 262 00:10:58,090 --> 00:10:59,450 It's always been creating jobs. 263 00:10:59,450 --> 00:11:01,770 But most importantly, it's been changing the mix. 264 00:11:01,770 --> 00:11:04,450 And what we're seeing recently, as I touched on earlier, 265 00:11:04,450 --> 00:11:07,504 is that mix is changing in a way that a lot of people 266 00:11:07,504 --> 00:11:09,420 are being made worse off, and other people are 267 00:11:09,420 --> 00:11:11,000 being made much better off. 268 00:11:11,000 --> 00:11:14,180 And we want to try to shape the direction of the technology. 269 00:11:14,180 --> 00:11:16,980 We want to also give people the skills and education 270 00:11:16,980 --> 00:11:18,790 so they can adapt to the new kinds of jobs 271 00:11:18,790 --> 00:11:19,710 that are available. 272 00:11:19,710 --> 00:11:21,560 And if we do that, I think we're going 273 00:11:21,560 --> 00:11:24,474 to be able to have that kind of world of shared prosperity. 274 00:11:24,474 --> 00:11:26,390 The technology will march on, and we shouldn't 275 00:11:26,390 --> 00:11:27,770 try to stop the technology. 276 00:11:27,770 --> 00:11:29,400 That's how we get that bigger pie, 277 00:11:29,400 --> 00:11:30,820 that growth that I mentioned. 278 00:11:30,820 --> 00:11:32,400 But we can direct it. 279 00:11:32,400 --> 00:11:34,590 In the earlier industrial revolutions, 280 00:11:34,590 --> 00:11:37,710 when the steam engine and other technologies came along, 281 00:11:37,710 --> 00:11:39,640 we adapted our institutions. 282 00:11:39,640 --> 00:11:41,760 We invented mass public education, 283 00:11:41,760 --> 00:11:43,690 first at the primary level, and then later 284 00:11:43,690 --> 00:11:44,940 at the secondary level. 285 00:11:44,940 --> 00:11:48,220 We invented social security and a whole bunch of other policies 286 00:11:48,220 --> 00:11:51,240 that helped smooth that transition 287 00:11:51,240 --> 00:11:53,200 to a new kind of work force and cushioned 288 00:11:53,200 --> 00:11:55,580 the people who otherwise would have been left behind. 289 00:11:55,580 --> 00:11:57,580 We're going to have to reinvent education again. 290 00:11:57,580 --> 00:11:58,996 And this time, we're going to have 291 00:11:58,996 --> 00:12:01,490 to do our best to shape the technology that 292 00:12:01,490 --> 00:12:03,590 is aligned with our values. 293 00:12:03,590 --> 00:12:06,120 Ultimately, it's not what the technology does to us. 294 00:12:06,120 --> 00:12:07,840 Technology is a tool. 295 00:12:07,840 --> 00:12:10,940 It's always been a tool, whether it's a hammer or an enterprise 296 00:12:10,940 --> 00:12:12,380 resource planning system. 297 00:12:12,380 --> 00:12:15,770 We have more powerful tools now than we ever had before, 298 00:12:15,770 --> 00:12:18,470 and that means we have more power to shape the future 299 00:12:18,470 --> 00:12:19,690 than we ever did before. 300 00:12:19,690 --> 00:12:22,300 But it starts with understanding that we have that power, 301 00:12:22,300 --> 00:12:25,181 and aligning our actions with our values. 302 00:12:25,181 --> 00:12:27,430 Well, Eric, I think that's a really important message, 303 00:12:27,430 --> 00:12:31,530 and one that I'm delighted that we can deliver in this class 304 00:12:31,530 --> 00:12:33,760 and in other settings where people can really 305 00:12:33,760 --> 00:12:34,510 make a difference. 306 00:12:34,510 --> 00:12:35,886 So thanks for joining us today. 307 00:12:35,886 --> 00:12:37,010 It's a tremendous pleasure. 308 00:12:37,010 --> 00:12:39,010 Thanks a lot, Tom.