1 00:00:00,090 --> 00:00:02,430 The following content is provided under a Creative 2 00:00:02,430 --> 00:00:03,820 Commons license. 3 00:00:03,820 --> 00:00:06,030 Your support will help MIT OpenCourseWare 4 00:00:06,030 --> 00:00:10,120 continue to offer high quality educational resources for free. 5 00:00:10,120 --> 00:00:12,660 To make a donation or to view additional materials 6 00:00:12,660 --> 00:00:16,620 from hundreds of MIT courses, visit MIT OpenCourseWare 7 00:00:16,620 --> 00:00:17,992 at ocw.mit.edu. 8 00:00:21,180 --> 00:00:22,680 WILLIAM BONVILLIAN: So I just want 9 00:00:22,680 --> 00:00:24,840 to go back through class five, because it's 10 00:00:24,840 --> 00:00:26,880 kind of foundational for the ideas 11 00:00:26,880 --> 00:00:28,690 that come up in this class. 12 00:00:28,690 --> 00:00:35,940 So just very quickly, David Hart taught us about the ideologies 13 00:00:35,940 --> 00:00:37,500 behind US innovation. 14 00:00:37,500 --> 00:00:41,280 And he takes a look at really the 1920s ideology 15 00:00:41,280 --> 00:00:43,620 around science and technology policy. 16 00:00:43,620 --> 00:00:50,970 And as we discussed, the same debates are with us. 17 00:00:50,970 --> 00:00:55,380 And the leading theologies, we could call them, 18 00:00:55,380 --> 00:00:58,980 are the associationalists, which we would now 19 00:00:58,980 --> 00:01:03,870 translate as public-private collaborations, 20 00:01:03,870 --> 00:01:08,350 versus conservative, which, you know, there 21 00:01:08,350 --> 00:01:13,450 is no federal governmental role except in the national security 22 00:01:13,450 --> 00:01:14,860 territory. 23 00:01:14,860 --> 00:01:17,380 And then the national security rationale, 24 00:01:17,380 --> 00:01:21,160 which I would argue is, do whatever 25 00:01:21,160 --> 00:01:26,710 it takes to establish national security based technologies. 26 00:01:26,710 --> 00:01:31,270 These ideologies fit the US than honestly fit other countries, 27 00:01:31,270 --> 00:01:33,550 but they are a significant part of the story 28 00:01:33,550 --> 00:01:37,990 about how policy has evolved in science and technology. 29 00:01:37,990 --> 00:01:42,610 Then we had a long dissertation on Alfred Loomis 30 00:01:42,610 --> 00:01:45,940 and the beginning of the Rad Lab at MIT, 31 00:01:45,940 --> 00:01:49,600 which we argued was really a foundational model for how 32 00:01:49,600 --> 00:01:52,720 the US R&D system is going to get organized. 33 00:01:52,720 --> 00:01:55,030 So that's taking place right here, 34 00:01:55,030 --> 00:01:59,800 and Loomis really designs a system 35 00:01:59,800 --> 00:02:09,580 that teaches us a lot about how we're going to organize R&D. 36 00:02:09,580 --> 00:02:15,850 So flat, non-hierarchical, team based, very cross disciplinary, 37 00:02:15,850 --> 00:02:19,840 collaborative, keep R&D out of uniform and out 38 00:02:19,840 --> 00:02:22,780 of uniform bureaucracies. 39 00:02:22,780 --> 00:02:25,270 Keep it out of the civil service. 40 00:02:25,270 --> 00:02:28,870 Create a kind of flat, non-hierarchical system 41 00:02:28,870 --> 00:02:32,401 that enables maximum exchange of ideas. 42 00:02:32,401 --> 00:02:35,110 Vannevar Bush at the end of the war 43 00:02:35,110 --> 00:02:39,490 writes The Endless Frontier, and that's 44 00:02:39,490 --> 00:02:42,040 the foundational document for US R&D. 45 00:02:42,040 --> 00:02:44,530 And what he's concerned about at the end of the war 46 00:02:44,530 --> 00:02:48,915 is salvaging some federal role in science. 47 00:02:48,915 --> 00:02:50,290 So the growth of the federal role 48 00:02:50,290 --> 00:02:54,350 in science in the course of World War II was profound. 49 00:02:54,350 --> 00:03:00,830 As I mentioned in class five, MIT 50 00:03:00,830 --> 00:03:02,948 receives 80 times more federal funding 51 00:03:02,948 --> 00:03:04,490 in the course of World War II than it 52 00:03:04,490 --> 00:03:06,740 does in all its previous 80 years of history. 53 00:03:06,740 --> 00:03:08,960 And that story is not unique. 54 00:03:08,960 --> 00:03:11,750 Other universities are having comparable experiences. 55 00:03:11,750 --> 00:03:15,050 So that's when the federally funded research university 56 00:03:15,050 --> 00:03:17,450 begins. 57 00:03:17,450 --> 00:03:19,490 And that's, obviously, a foundational model 58 00:03:19,490 --> 00:03:21,560 in the US system. 59 00:03:21,560 --> 00:03:24,050 Vannevar Bush wants to salvage it. 60 00:03:24,050 --> 00:03:29,930 So in the midst of a kind of a huge rapid scale down 61 00:03:29,930 --> 00:03:33,050 to the defense establishment at the end of World War II where 62 00:03:33,050 --> 00:03:37,670 everything is being canceled, he works with Franklin Roosevelt 63 00:03:37,670 --> 00:03:42,160 to keep a federal government research 64 00:03:42,160 --> 00:03:43,675 focus in basic research. 65 00:03:46,180 --> 00:03:50,020 Peter Singer reminded us of how productive 66 00:03:50,020 --> 00:03:51,250 that system has been. 67 00:03:51,250 --> 00:03:55,120 So his paper on 22 examples of federal R&D 68 00:03:55,120 --> 00:04:01,630 that translated into major technology sectors-- 69 00:04:01,630 --> 00:04:07,300 so Peter argues that that basic R&D 70 00:04:07,300 --> 00:04:11,770 model has, in fact, yielded enormous technology 71 00:04:11,770 --> 00:04:12,880 development. 72 00:04:12,880 --> 00:04:14,620 That's not an easy thing to trace. 73 00:04:14,620 --> 00:04:18,190 Waht are the originating scientific advances 74 00:04:18,190 --> 00:04:21,140 in a 20 year project towards technology advance, 75 00:04:21,140 --> 00:04:22,570 or perhaps longer. 76 00:04:22,570 --> 00:04:26,140 But Peter kind of did what we called genealogical research 77 00:04:26,140 --> 00:04:28,870 to figure out what the core elements were. 78 00:04:28,870 --> 00:04:30,550 But it's there. 79 00:04:30,550 --> 00:04:35,200 So it's not that Vannevar Bush's basic research model in itself 80 00:04:35,200 --> 00:04:38,230 is bad or wrong. 81 00:04:38,230 --> 00:04:40,270 But it's an important one. 82 00:04:40,270 --> 00:04:43,120 And William Blanpied told us the story of NSF. 83 00:04:43,120 --> 00:04:46,570 So the second Vannevar Bush story is-- 84 00:04:46,570 --> 00:04:48,770 story one is support basic research. 85 00:04:48,770 --> 00:04:51,570 Story two, how are you going to organize science 86 00:04:51,570 --> 00:04:52,820 in the federal government? 87 00:04:52,820 --> 00:04:58,640 And his vision was there was going to be one tent. 88 00:04:58,640 --> 00:05:01,740 And science was going to fit under one tent. 89 00:05:01,740 --> 00:05:04,080 You wouldn't have a multitude of agencies. 90 00:05:04,080 --> 00:05:06,750 He was not successful in pushing that argument, remember. 91 00:05:06,750 --> 00:05:11,850 Because Harry Truman vetoed the National Science Foundation law 92 00:05:11,850 --> 00:05:14,240 that he proposed. 93 00:05:14,240 --> 00:05:16,650 Because Vannevar Bush wanted scientists alone 94 00:05:16,650 --> 00:05:20,640 to control science and left out a significant role 95 00:05:20,640 --> 00:05:22,810 for the executive branch. 96 00:05:22,810 --> 00:05:24,330 So it got vetoed. 97 00:05:24,330 --> 00:05:26,910 And therefore, NSF didn't really get stood up 98 00:05:26,910 --> 00:05:28,030 for another five years. 99 00:05:28,030 --> 00:05:31,590 So other agencies pop up in the void. 100 00:05:31,590 --> 00:05:33,220 So that, in turn, meant-- 101 00:05:33,220 --> 00:05:34,980 this kind of funny accident of time 102 00:05:34,980 --> 00:05:38,730 meant that the US was going to have a very decentralized 103 00:05:38,730 --> 00:05:41,880 system of a multitude of agencies working 104 00:05:41,880 --> 00:05:44,610 on science and research. 105 00:05:44,610 --> 00:05:47,940 That's how it happened. 106 00:05:47,940 --> 00:05:51,060 And Blanpied lays out that debate for us. 107 00:05:51,060 --> 00:05:56,100 We then looked at Donald Stokes as the kind of closing reading 108 00:05:56,100 --> 00:05:57,790 last week. 109 00:05:57,790 --> 00:05:59,930 And Stokes's book, Pasteur's Quadrant 110 00:05:59,930 --> 00:06:04,430 is something of a classic in the science policy literature. 111 00:06:04,430 --> 00:06:10,040 And Stokes argues that Vannevar Bush saddled the country 112 00:06:10,040 --> 00:06:13,230 with a disconnected system. 113 00:06:13,230 --> 00:06:18,510 All very well and good, but he missed a crucial quadrant. 114 00:06:18,510 --> 00:06:24,090 He missed the quadratic of use-based fundamental research. 115 00:06:24,090 --> 00:06:27,640 In other words, you have an idea about what you want to achieve. 116 00:06:27,640 --> 00:06:29,760 But you use basic research to get there. 117 00:06:29,760 --> 00:06:32,970 He argues that Pasteur's quadrant-- 118 00:06:32,970 --> 00:06:36,690 because Pasteur is out to save kids in France from bad milk, 119 00:06:36,690 --> 00:06:38,910 he knows what he wants. 120 00:06:38,910 --> 00:06:44,250 But he goes back and develops microbiology to get there. 121 00:06:44,250 --> 00:06:47,550 So Stokes's argument is Vannevar Bush 122 00:06:47,550 --> 00:06:51,240 focuses us on curiosity driven basic research. 123 00:06:51,240 --> 00:06:56,210 He missed use-based basic research. 124 00:06:56,210 --> 00:06:59,060 And that was a big gap in the system. 125 00:06:59,060 --> 00:07:03,460 So what that meant in the US was that we would 126 00:07:03,460 --> 00:07:05,500 be good at the basic research. 127 00:07:05,500 --> 00:07:07,580 We would have a disconnected system. 128 00:07:07,580 --> 00:07:10,450 It would be hard to do the implementation 129 00:07:10,450 --> 00:07:13,697 stages to achieve the technology advances here. 130 00:07:13,697 --> 00:07:15,280 And we have seen that again and again. 131 00:07:15,280 --> 00:07:19,540 The US would often originate the foundational technologies. 132 00:07:19,540 --> 00:07:21,830 I was just working on lithium ion batteries. 133 00:07:21,830 --> 00:07:24,510 A lot of those early advances came out of the US. 134 00:07:24,510 --> 00:07:26,110 It was not commercialized here. 135 00:07:26,110 --> 00:07:32,720 So Vannevar Bush, of course, understood connected science, 136 00:07:32,720 --> 00:07:36,500 because he created that in World War II, a brilliantly connected 137 00:07:36,500 --> 00:07:37,168 model. 138 00:07:37,168 --> 00:07:38,960 I would argue that what he was trying to do 139 00:07:38,960 --> 00:07:43,280 was salvage what he could at the end of the war. 140 00:07:43,280 --> 00:07:47,120 But Stokes critiques him essentially 141 00:07:47,120 --> 00:07:49,820 argues that we got a disconnected system out 142 00:07:49,820 --> 00:07:51,110 of this. 143 00:07:51,110 --> 00:07:54,320 And that was very problematic for the ability of the US 144 00:07:54,320 --> 00:07:58,400 to stand up subsequent follow on technology advances. 145 00:07:58,400 --> 00:08:01,160 And we've seen that again and again. 146 00:08:01,160 --> 00:08:06,950 So that's a look at some of the foundational issues on how 147 00:08:06,950 --> 00:08:11,150 we organize science and R&D in our system. 148 00:08:11,150 --> 00:08:16,640 And today, we're going to take a really deep look 149 00:08:16,640 --> 00:08:20,670 at what we could call the valley of death problem. 150 00:08:20,670 --> 00:08:22,680 In other words, it's precisely this problem 151 00:08:22,680 --> 00:08:25,110 that Stokes talked about, the disconnect 152 00:08:25,110 --> 00:08:30,270 between the research stage and late stage development. 153 00:08:30,270 --> 00:08:32,120 And we're going to-- 154 00:08:32,120 --> 00:08:33,679 the Branscomb and Auerswald reading 155 00:08:33,679 --> 00:08:36,620 will lay that valley of death problem out. 156 00:08:36,620 --> 00:08:39,409 And then we'll talk about actually 157 00:08:39,409 --> 00:08:44,250 how the US is actually on the side running 158 00:08:44,250 --> 00:08:48,380 all parallel universe of much more connected defense 159 00:08:48,380 --> 00:08:49,830 research. 160 00:08:49,830 --> 00:08:51,850 It's a very different system. 161 00:08:51,850 --> 00:08:56,090 So we have two very different innovation systems 162 00:08:56,090 --> 00:08:57,840 that the federal government is supporting. 163 00:08:57,840 --> 00:08:59,490 And we'll go through those two models. 164 00:09:02,230 --> 00:09:05,957 So who's got got Branscomb and Auerswald, which of you three? 165 00:09:05,957 --> 00:09:06,790 Matthew, you got it? 166 00:09:06,790 --> 00:09:07,290 OK. 167 00:09:10,390 --> 00:09:15,100 That's Lew Branscomb, a noted professor at the Kennedy 168 00:09:15,100 --> 00:09:18,460 School, now emeritus. 169 00:09:18,460 --> 00:09:21,150 He was vice president and chief scientist at IBM. 170 00:09:21,150 --> 00:09:25,270 He was a director of NIST, a noted physicist working 171 00:09:25,270 --> 00:09:28,300 in the atomic molecular fields. 172 00:09:28,300 --> 00:09:31,990 He won the National Science Foundation's Vannevar Bush 173 00:09:31,990 --> 00:09:36,400 award, appropriately enough, which is its top award. 174 00:09:36,400 --> 00:09:39,550 A remarkable and lovely and wonderful guy, and a real kind 175 00:09:39,550 --> 00:09:45,160 of statesperson of science who used to help young kids like me 176 00:09:45,160 --> 00:09:48,250 and help us learn the system. 177 00:09:48,250 --> 00:09:53,060 And his colleague, Phil Auerswald, 178 00:09:53,060 --> 00:09:56,990 is now on his third or fourth book, 179 00:09:56,990 --> 00:10:01,023 and has gone into the field of innovation policy 180 00:10:01,023 --> 00:10:02,690 in a deep way, and is a real contributor 181 00:10:02,690 --> 00:10:03,730 in that field as well. 182 00:10:03,730 --> 00:10:06,680 So Phil is a spokesman in his own right at this point. 183 00:10:06,680 --> 00:10:08,360 He teaches at George Mason University, 184 00:10:08,360 --> 00:10:11,810 which has a strong science and technology policy group. 185 00:10:14,620 --> 00:10:16,510 So those are our authors. 186 00:10:16,510 --> 00:10:21,370 And let me just go to the charts. 187 00:10:21,370 --> 00:10:24,880 This is a chart that was used in the House Science Committee. 188 00:10:24,880 --> 00:10:28,580 And it wasn't-- the term, valley of death, between, again, 189 00:10:28,580 --> 00:10:32,280 research and later stage development-- 190 00:10:32,280 --> 00:10:35,220 that wasn't a term that Branscomb and Auerswald 191 00:10:35,220 --> 00:10:36,420 invented. 192 00:10:36,420 --> 00:10:39,600 It kind of came into currency, however, 193 00:10:39,600 --> 00:10:42,870 in the time period in which they're writing. 194 00:10:42,870 --> 00:10:46,350 And the idea here is-- it's a very simple one, 195 00:10:46,350 --> 00:10:49,350 that you've got one set of institutions 196 00:10:49,350 --> 00:10:52,400 working on basic research. 197 00:10:52,400 --> 00:10:54,800 You've got another set of institutions working 198 00:10:54,800 --> 00:11:00,670 on the later stage, applied side, later stage development 199 00:11:00,670 --> 00:11:02,810 in particular. 200 00:11:02,810 --> 00:11:06,790 And there are very few bridging mechanisms in our system 201 00:11:06,790 --> 00:11:10,190 across this gap between the two. 202 00:11:10,190 --> 00:11:16,790 So as we tried to understand innovation 20 years ago, 203 00:11:16,790 --> 00:11:19,760 this was the major idea in the system. 204 00:11:19,760 --> 00:11:22,030 And it comes right out of Stokes's thinking. 205 00:11:22,030 --> 00:11:23,530 We're seeing this. 206 00:11:23,530 --> 00:11:26,770 And what's happening at the time is 207 00:11:26,770 --> 00:11:32,490 that Japan has created this brilliant quality manufacturing 208 00:11:32,490 --> 00:11:33,750 system. 209 00:11:33,750 --> 00:11:36,570 It amounts to a real innovation wave in itself. 210 00:11:36,570 --> 00:11:39,750 The US misses it and then loses leadership 211 00:11:39,750 --> 00:11:42,180 on two huge industrial sectors, autos 212 00:11:42,180 --> 00:11:46,530 and consumer electronics as a result of getting this wrong. 213 00:11:49,080 --> 00:11:54,280 So this is another chart of the same thing. 214 00:11:54,280 --> 00:11:57,800 This is more of a pipeline chart. 215 00:11:57,800 --> 00:12:02,277 And arguably, Vannevar Bush set up the pipeline model 216 00:12:02,277 --> 00:12:03,860 where the federal role was going to be 217 00:12:03,860 --> 00:12:09,380 dump basic research into the end of this innovation pipeline. 218 00:12:09,380 --> 00:12:11,480 Mysterious things will occur. 219 00:12:11,480 --> 00:12:13,850 Great products will emerge at the end. 220 00:12:13,850 --> 00:12:15,860 That's essentially the organizational model 221 00:12:15,860 --> 00:12:19,430 for US civilian R&D. 222 00:12:19,430 --> 00:12:21,500 This is a way to try and understand 223 00:12:21,500 --> 00:12:24,170 what's going on within that pipeline 224 00:12:24,170 --> 00:12:28,340 and who the actors are that can influence different stages, who 225 00:12:28,340 --> 00:12:30,380 can do the bridging. 226 00:12:30,380 --> 00:12:33,980 And what Branscomb and Auerswald set out is-- 227 00:12:33,980 --> 00:12:35,060 there's basic research. 228 00:12:35,060 --> 00:12:38,420 There's the proof of concept invention stage. 229 00:12:38,420 --> 00:12:41,840 Then there's technology development. 230 00:12:41,840 --> 00:12:44,120 Then you move on to product development and production 231 00:12:44,120 --> 00:12:45,990 and marketing. 232 00:12:45,990 --> 00:12:48,385 And then helping at these different stages 233 00:12:48,385 --> 00:12:49,260 are different actors. 234 00:12:49,260 --> 00:12:51,660 So the basic research agency's here. 235 00:12:51,660 --> 00:12:55,110 And maybe they'll help you get to the proof of concept stage. 236 00:12:55,110 --> 00:12:57,210 But they're not going to reach beyond that. 237 00:12:57,210 --> 00:13:01,920 But then angel investors, sometimes corporate allies, 238 00:13:01,920 --> 00:13:04,290 sometimes the small business innovation research 239 00:13:04,290 --> 00:13:05,730 program that we've talked about-- 240 00:13:05,730 --> 00:13:09,360 that might help you move from here to here. 241 00:13:09,360 --> 00:13:12,660 Venture capital, they point out, doesn't really 242 00:13:12,660 --> 00:13:14,860 come to bear in this stage. 243 00:13:14,860 --> 00:13:17,670 Venture capital, as we talked about in the first class, 244 00:13:17,670 --> 00:13:21,240 is really only interested in supporting your technology 245 00:13:21,240 --> 00:13:25,020 if it's only about two years away from actual production. 246 00:13:25,020 --> 00:13:26,970 So they're not going to help you, 247 00:13:26,970 --> 00:13:30,120 by and large, with the exception of the biotech area, 248 00:13:30,120 --> 00:13:34,590 bridge across this kind of gap territory. 249 00:13:34,590 --> 00:13:37,440 When you get to here, there's corporate venture, and equity, 250 00:13:37,440 --> 00:13:39,310 and commercial debt that will help you. 251 00:13:39,310 --> 00:13:42,030 But they argue that this is the gap in the system. 252 00:13:42,030 --> 00:13:47,620 But they also note, it's not a pipeline. 253 00:13:47,620 --> 00:13:50,310 It's much more complicated. 254 00:13:50,310 --> 00:13:56,400 And in the end, they adopt this phrase, a Darwinian sea 255 00:13:56,400 --> 00:13:58,500 between a struggle for life and a sea 256 00:13:58,500 --> 00:14:01,380 of technical and entrepreneurship risk. 257 00:14:01,380 --> 00:14:05,970 Because things don't move smoothly down the pipeline. 258 00:14:05,970 --> 00:14:08,538 You'll get to proof of concept stage 259 00:14:08,538 --> 00:14:10,080 and realize you've got to rethink it. 260 00:14:10,080 --> 00:14:11,185 You go back here. 261 00:14:11,185 --> 00:14:12,810 And then maybe you get to here and then 262 00:14:12,810 --> 00:14:14,910 you realize, well, I'm not going to be able to get 263 00:14:14,910 --> 00:14:15,868 to product development. 264 00:14:15,868 --> 00:14:17,080 I've got to go back to there. 265 00:14:17,080 --> 00:14:19,530 In other words, it's a much more convoluted process 266 00:14:19,530 --> 00:14:23,290 with a lot of iterations and feedback in that system. 267 00:14:23,290 --> 00:14:27,297 So they argue, in the end, it's more like this. 268 00:14:27,297 --> 00:14:29,130 The innovation and new business on one side, 269 00:14:29,130 --> 00:14:31,200 research and invention on the other, 270 00:14:31,200 --> 00:14:34,740 and this kind of struggle, in a Darwinian sense, 271 00:14:34,740 --> 00:14:38,040 going on between the two. 272 00:14:38,040 --> 00:14:42,690 But frankly, a pipeline model is much more convenient and easy 273 00:14:42,690 --> 00:14:44,550 to understand, even though we should all 274 00:14:44,550 --> 00:14:49,230 know that it overstates the model, 275 00:14:49,230 --> 00:14:51,210 that it's really more like a Darwinian sea. 276 00:14:54,700 --> 00:14:57,640 And then they go through what are the funding sources 277 00:14:57,640 --> 00:15:01,630 and note, really pretty limited funding sources 278 00:15:01,630 --> 00:15:04,120 that are available for that bridge 279 00:15:04,120 --> 00:15:05,290 over the valley of death. 280 00:15:05,290 --> 00:15:08,380 It's a pretty limited panoply. 281 00:15:08,380 --> 00:15:10,960 So why don't we leave that there. 282 00:15:10,960 --> 00:15:14,730 And I'll turn it over to you, Matthew. 283 00:15:14,730 --> 00:15:18,130 AUDIENCE: I think the summary was pretty comprehensive. 284 00:15:18,130 --> 00:15:21,490 So I mean, most of the questions that I had really 285 00:15:21,490 --> 00:15:24,640 focused on that stage theory, that early stage technology 286 00:15:24,640 --> 00:15:26,140 development. 287 00:15:26,140 --> 00:15:27,820 As you could say, it's the Darwinian sea 288 00:15:27,820 --> 00:15:29,410 or the valley of death. 289 00:15:29,410 --> 00:15:36,070 And one of the questions I wanted to ask here 290 00:15:36,070 --> 00:15:39,460 was-- we saw a lot previously about metrics 291 00:15:39,460 --> 00:15:42,660 to measure how much we're putting into basic research. 292 00:15:42,660 --> 00:15:44,890 And then we also have all the economic indicators 293 00:15:44,890 --> 00:15:47,230 on the other side. 294 00:15:47,230 --> 00:15:49,720 Right now, is there any good way to measure just 295 00:15:49,720 --> 00:15:53,770 how effective a country is at actually translating 296 00:15:53,770 --> 00:15:55,540 technologies that are being developed 297 00:15:55,540 --> 00:15:58,170 into commercialized products? 298 00:16:08,500 --> 00:16:10,250 AUDIENCE: Could you rephrase the question? 299 00:16:10,250 --> 00:16:11,610 AUDIENCE: Sure, yeah. 300 00:16:11,610 --> 00:16:17,650 So I mean, could you imagine any good way to-- 301 00:16:17,650 --> 00:16:21,095 or any good metric to measure just how effective-- or would 302 00:16:21,095 --> 00:16:25,820 it even make sense to measure how effective a country is 303 00:16:25,820 --> 00:16:28,870 kind of traversing that valley of death? 304 00:16:28,870 --> 00:16:30,680 Because there's a lot of metrics in terms 305 00:16:30,680 --> 00:16:34,530 of just how much we're spending on one side on basic research. 306 00:16:34,530 --> 00:16:38,480 And then on the other side you have economic indicators, 307 00:16:38,480 --> 00:16:39,535 productivity. 308 00:16:39,535 --> 00:16:40,910 AUDIENCE: Well, one idea for that 309 00:16:40,910 --> 00:16:44,885 could be the sheer number of startups that are produced, 310 00:16:44,885 --> 00:16:47,540 which was something that I think one of the later readings 311 00:16:47,540 --> 00:16:48,700 had mentioned. 312 00:16:48,700 --> 00:16:50,995 Or you could just look at the success rate of startups. 313 00:16:50,995 --> 00:16:52,370 So how long does it take for them 314 00:16:52,370 --> 00:16:58,080 on average to foreclose, or just to go bankrupt, or to just-- 315 00:16:58,080 --> 00:17:00,680 how many of them do so? 316 00:17:00,680 --> 00:17:03,020 And how many of them are able to actually produce 317 00:17:03,020 --> 00:17:03,920 a viable product? 318 00:17:03,920 --> 00:17:04,640 Et cetera. 319 00:17:04,640 --> 00:17:08,819 You could measure something along the lines of that. 320 00:17:08,819 --> 00:17:14,040 AUDIENCE: Longevity and percentage of-- 321 00:17:14,040 --> 00:17:18,280 make it through first year, five year, 10 year. 322 00:17:18,280 --> 00:17:20,280 AUDIENCE: And I think it would be important also 323 00:17:20,280 --> 00:17:23,880 to measure how much of that value 324 00:17:23,880 --> 00:17:25,880 you actually capture as a country. 325 00:17:25,880 --> 00:17:27,839 You have countries like Israel where 326 00:17:27,839 --> 00:17:29,760 you have tons and tons of startups, 327 00:17:29,760 --> 00:17:31,543 but they all end up getting exported. 328 00:17:31,543 --> 00:17:33,960 They don't stay in the country, because all of the venture 329 00:17:33,960 --> 00:17:36,855 financing is in the US. 330 00:17:36,855 --> 00:17:39,230 WILLIAM BONVILLIAN: There's another possible measure too, 331 00:17:39,230 --> 00:17:39,730 Matthew. 332 00:17:39,730 --> 00:17:41,640 It's probably on your list. 333 00:17:41,640 --> 00:17:43,710 Patents. 334 00:17:43,710 --> 00:17:49,170 And patents have to list the scientific research 335 00:17:49,170 --> 00:17:51,448 on which they draw. 336 00:17:51,448 --> 00:17:53,490 So you can actually go into the patent literature 337 00:17:53,490 --> 00:17:55,500 and understand the scientific advances 338 00:17:55,500 --> 00:17:57,630 behind the patent application. 339 00:17:57,630 --> 00:18:01,260 But of course, many patents sit completely unused. 340 00:18:01,260 --> 00:18:02,790 They go on the shelf. 341 00:18:02,790 --> 00:18:05,520 So it's just-- the total number of patents 342 00:18:05,520 --> 00:18:07,870 doesn't necessarily tell you much. 343 00:18:07,870 --> 00:18:10,020 AUDIENCE: Look at the citations on the patents-- 344 00:18:10,020 --> 00:18:11,937 WILLIAM BONVILLIAN: Yeah, but it does tell you 345 00:18:11,937 --> 00:18:14,520 what the early stage research was, often, that's behind them. 346 00:18:14,520 --> 00:18:17,040 And look, the amount of early stage research 347 00:18:17,040 --> 00:18:20,730 that's being cited in patent applications 348 00:18:20,730 --> 00:18:22,800 has been growing profoundly. 349 00:18:22,800 --> 00:18:25,770 So we know that some of this research 350 00:18:25,770 --> 00:18:30,570 is getting out of the left hand side of the pipeline 351 00:18:30,570 --> 00:18:32,820 out the end of it. 352 00:18:32,820 --> 00:18:36,217 So it's important from that perspective. 353 00:18:41,090 --> 00:18:41,990 Other indicators? 354 00:18:47,678 --> 00:18:50,010 AUDIENCE: I think there's also something 355 00:18:50,010 --> 00:18:54,090 to say for maybe the economic impact per capita. 356 00:18:54,090 --> 00:18:57,510 Really assessing, how much does the innovation 357 00:18:57,510 --> 00:19:01,290 end up impacting the country's well-being? 358 00:19:01,290 --> 00:19:04,140 And how do individuals-- whether or not 359 00:19:04,140 --> 00:19:07,440 individuals benefit from it who are regular citizens, rather 360 00:19:07,440 --> 00:19:10,068 than just the industry capturing that profit. 361 00:19:10,068 --> 00:19:12,360 I think there's something to be said about establishing 362 00:19:12,360 --> 00:19:16,080 a metric for impact as well that's based specifically 363 00:19:16,080 --> 00:19:18,900 on per capita or per citizen in order 364 00:19:18,900 --> 00:19:21,660 to make it sort of comparable to other countries 365 00:19:21,660 --> 00:19:24,820 and the resources that they have available to them or not. 366 00:19:24,820 --> 00:19:26,820 AUDIENCE: So you're saying non-monetary results. 367 00:19:26,820 --> 00:19:29,730 AUDIENCE: No, I think they can be monetary results too. 368 00:19:29,730 --> 00:19:31,410 I mean, the regression analysis is 369 00:19:31,410 --> 00:19:32,950 going to be more complicated. 370 00:19:32,950 --> 00:19:35,310 But I feel like if you do measures of well-being, 371 00:19:35,310 --> 00:19:38,250 both on economic impact and also on well-being sort 372 00:19:38,250 --> 00:19:40,437 of statistical measurements on, say, like-- 373 00:19:40,437 --> 00:19:42,270 I mean, I know people measure happiness now. 374 00:19:42,270 --> 00:19:43,860 That could be a really interesting impact. 375 00:19:43,860 --> 00:19:45,390 And I know that you could do that-- 376 00:19:45,390 --> 00:19:49,170 for example, when we need biotech, the people who you're 377 00:19:49,170 --> 00:19:51,180 impacting, do they feel like their lives 378 00:19:51,180 --> 00:19:53,220 any better as a result of your invention, 379 00:19:53,220 --> 00:19:58,045 in addition to the economic benefits of your advance. 380 00:19:58,045 --> 00:19:59,490 AUDIENCE: Yeah, I would say no. 381 00:19:59,490 --> 00:20:00,948 I think it was polio, that somebody 382 00:20:00,948 --> 00:20:03,078 discovered it, and then just kind of gave it away. 383 00:20:03,078 --> 00:20:04,120 So that has a big impact. 384 00:20:04,120 --> 00:20:07,530 You make a lot of money, but it was important to [INAUDIBLE].. 385 00:20:07,530 --> 00:20:09,390 WILLIAM BONVILLIAN: The issue here 386 00:20:09,390 --> 00:20:12,750 is that often that social impact is 387 00:20:12,750 --> 00:20:17,460 going to take a very long time to evolve at scale. 388 00:20:17,460 --> 00:20:23,480 So if you're willing to take a long-term look to reach 389 00:20:23,480 --> 00:20:26,210 a level of a reasonable assessment, 390 00:20:26,210 --> 00:20:28,442 it's going to be a very extended period. 391 00:20:28,442 --> 00:20:30,397 AUDIENCE: It's such a difficult metric. 392 00:20:30,397 --> 00:20:32,730 AUDIENCE: What metric do you have for measuring it, too? 393 00:20:32,730 --> 00:20:35,760 Because you can say, oh, I have x amount of Apple stock, 394 00:20:35,760 --> 00:20:37,570 and I've made x amount of dollars. 395 00:20:37,570 --> 00:20:41,600 And that's improved my assets over this many years. 396 00:20:41,600 --> 00:20:44,280 WILLIAM BONVILLIAN: Well, you're driving at its societal impact, 397 00:20:44,280 --> 00:20:44,850 right? 398 00:20:44,850 --> 00:20:45,780 AUDIENCE: But then how do you measure-- 399 00:20:45,780 --> 00:20:46,950 AUDIENCE: But it could also be specifically 400 00:20:46,950 --> 00:20:47,910 in technical advances. 401 00:20:47,910 --> 00:20:50,670 Like I wouldn't say necessarily, from an investment 402 00:20:50,670 --> 00:20:54,300 standpoint, that I would care so much 403 00:20:54,300 --> 00:20:57,180 about the happiness of the stakeholder or the shareholder, 404 00:20:57,180 --> 00:20:58,530 specifically. 405 00:20:58,530 --> 00:21:00,240 AUDIENCE: But I was going to go on 406 00:21:00,240 --> 00:21:02,210 to say, how do I measure how much this 407 00:21:02,210 --> 00:21:05,340 has improved my life, when you get 408 00:21:05,340 --> 00:21:08,295 into issues with measurement. 409 00:21:08,295 --> 00:21:09,750 It's complicated. 410 00:21:09,750 --> 00:21:11,760 AUDIENCE: When it comes to a measurement, 411 00:21:11,760 --> 00:21:14,095 like you can have the best invention, but you don't win. 412 00:21:14,095 --> 00:21:14,970 You know what I mean? 413 00:21:14,970 --> 00:21:16,810 Like you can come up with something that's really great, 414 00:21:16,810 --> 00:21:19,410 but if you're not a great executioner-- like for Fitbit, 415 00:21:19,410 --> 00:21:22,080 I met the guy who now works for Google X, 416 00:21:22,080 --> 00:21:24,350 and he created the Fitbit, but way better 417 00:21:24,350 --> 00:21:25,593 and had way more customers. 418 00:21:25,593 --> 00:21:27,510 But because he didn't raise a round of funding 419 00:21:27,510 --> 00:21:29,520 before the economic collapse, the product 420 00:21:29,520 --> 00:21:30,660 never got to market. 421 00:21:30,660 --> 00:21:33,110 So it might just be chance, right? 422 00:21:33,110 --> 00:21:35,825 So Darwinian sea is a good example. 423 00:21:35,825 --> 00:21:37,200 Your research can be really good. 424 00:21:37,200 --> 00:21:38,070 It can be really compelling. 425 00:21:38,070 --> 00:21:39,000 You can be a great team. 426 00:21:39,000 --> 00:21:40,320 But there's a lot of other factors 427 00:21:40,320 --> 00:21:42,778 that we don't take into account, a lot of hidden variables. 428 00:21:45,457 --> 00:21:47,790 WILLIAM BONVILLIAN: How about another question, Matthew? 429 00:21:47,790 --> 00:21:49,840 MATTHEW: Yeah, actually one thing 430 00:21:49,840 --> 00:21:53,970 that kind of a lot of people caught on to was-- 431 00:21:53,970 --> 00:22:00,070 so Branscomb and Auerswald, they detail three main challenges 432 00:22:00,070 --> 00:22:01,540 to crossing the Valley of Death. 433 00:22:01,540 --> 00:22:06,700 And the three challenges were motivation on the R&D side, 434 00:22:06,700 --> 00:22:11,560 to reducing that to practice, trust between the technologist 435 00:22:11,560 --> 00:22:13,210 and the business manager. 436 00:22:13,210 --> 00:22:15,400 And then the third is the sources 437 00:22:15,400 --> 00:22:19,030 of funding for entrepreneurs. 438 00:22:19,030 --> 00:22:22,660 And focusing in on that trust or understanding even 439 00:22:22,660 --> 00:22:24,910 between the technologist and the business manager, 440 00:22:24,910 --> 00:22:28,960 someone asked, is there value in maybe changing 441 00:22:28,960 --> 00:22:32,530 the way we educate people, or having 442 00:22:32,530 --> 00:22:37,070 more joint technology in business degrees 443 00:22:37,070 --> 00:22:39,800 or courses of study to help bridge that gap? 444 00:22:48,985 --> 00:22:51,110 WILLIAM BONVILLIAN: Matthew, I can give you a hint. 445 00:22:51,110 --> 00:22:55,820 You can ask the person who wrote the question to respond. 446 00:22:55,820 --> 00:23:00,168 MATTHEW: He's double major, or-- 447 00:23:00,168 --> 00:23:02,210 WILLIAM BONVILLIAN: No, which one of the students 448 00:23:02,210 --> 00:23:04,010 who wrote the question that you're drawing on, 449 00:23:04,010 --> 00:23:04,885 you can call on them. 450 00:23:04,885 --> 00:23:06,388 AUDIENCE: It was a lot at once. 451 00:23:06,388 --> 00:23:07,680 WILLIAM BONVILLIAN: It was you? 452 00:23:07,680 --> 00:23:09,020 AUDIENCE: So if you have an answer, just like, 453 00:23:09,020 --> 00:23:10,050 it was a lot at once. 454 00:23:10,050 --> 00:23:12,175 MATTHEW: Yeah, so what do you think the value would 455 00:23:12,175 --> 00:23:16,460 be in maybe restructuring the way we do education 456 00:23:16,460 --> 00:23:19,590 or offering more interdisciplinary 457 00:23:19,590 --> 00:23:23,000 degrees in maybe, say, science or engineering and business 458 00:23:23,000 --> 00:23:25,530 to help bridge that gap? 459 00:23:25,530 --> 00:23:28,150 AUDIENCE: I would look into the top most successful 460 00:23:28,150 --> 00:23:29,150 technologists right now. 461 00:23:29,150 --> 00:23:31,970 So like Zuckerberg was psychology and computer 462 00:23:31,970 --> 00:23:33,800 science. 463 00:23:33,800 --> 00:23:37,880 I think Larry Ellison, he was medicine, 464 00:23:37,880 --> 00:23:40,610 but then he switched and then went to Silicon Valley. 465 00:23:40,610 --> 00:23:43,250 Elon Musk was economics and physics. 466 00:23:43,250 --> 00:23:46,430 So I don't know if that's a good answer. 467 00:23:46,430 --> 00:23:48,950 AUDIENCE: So frankly, I'd say you're in support of it, 468 00:23:48,950 --> 00:23:51,080 because a lot of these people that were successful. 469 00:23:51,080 --> 00:23:53,600 Of course, correlation does not imply causation. 470 00:23:53,600 --> 00:23:57,955 So just because Mark Zuckerberg happened 471 00:23:57,955 --> 00:23:59,580 to use computer science and psychology, 472 00:23:59,580 --> 00:24:00,670 it doesn't mean that-- 473 00:24:00,670 --> 00:24:02,587 AUDIENCE: But I was trying to-- the education, 474 00:24:02,587 --> 00:24:05,010 in terms, like, has there a bit a really, really 475 00:24:05,010 --> 00:24:12,310 great technologist who was just pure science, or like just one? 476 00:24:12,310 --> 00:24:14,660 AUDIENCE: Maybe 100 years ago. 477 00:24:14,660 --> 00:24:16,617 AUDIENCE: I think during the transistor era, 478 00:24:16,617 --> 00:24:18,200 there was a lot of great technologists 479 00:24:18,200 --> 00:24:22,115 that could execute well, like Bardeen, Shockley. 480 00:24:22,115 --> 00:24:23,615 And then that's where Intel started. 481 00:24:23,615 --> 00:24:25,760 AUDIENCE: Well, I don't know about Shockley. 482 00:24:25,760 --> 00:24:27,510 AUDIENCE: Yeah, he didn't take the credit, 483 00:24:27,510 --> 00:24:28,835 but he was still there. 484 00:24:28,835 --> 00:24:30,960 WILLIAM BONVILLIAN: Well, that's next week's story, 485 00:24:30,960 --> 00:24:32,450 or two weeks from now story. 486 00:24:32,450 --> 00:24:34,310 No, next week-- right, sorry. 487 00:24:34,310 --> 00:24:36,110 Luyao, you asked that question? 488 00:24:36,110 --> 00:24:37,270 So do you want to oppose? 489 00:24:37,270 --> 00:24:39,430 Do you want to give us an answer or your thoughts? 490 00:24:39,430 --> 00:24:41,570 AUDIENCE: Like to me, I realize the American system 491 00:24:41,570 --> 00:24:43,670 is more flexible and allows you to take 492 00:24:43,670 --> 00:24:45,950 cross-disciplinary course. 493 00:24:45,950 --> 00:24:47,540 But from my home university, like 494 00:24:47,540 --> 00:24:51,000 England has really kind of narrowed 495 00:24:51,000 --> 00:24:52,730 choices for each student. 496 00:24:52,730 --> 00:24:57,410 So you see less students choose a double degree 497 00:24:57,410 --> 00:24:59,880 or double major courses. 498 00:24:59,880 --> 00:25:02,690 I do think that plays an important role 499 00:25:02,690 --> 00:25:08,850 in the development of innovations in the States. 500 00:25:08,850 --> 00:25:12,190 This is a cross-country comparison. 501 00:25:12,190 --> 00:25:13,690 WILLIAM BONVILLIAN: As you all know, 502 00:25:13,690 --> 00:25:15,420 there's lots of MIT students who are 503 00:25:15,420 --> 00:25:19,770 doing business minors and engineering or science degrees, 504 00:25:19,770 --> 00:25:23,310 and lots of entrepreneurship courses 505 00:25:23,310 --> 00:25:27,040 that people from both sides are taking. 506 00:25:27,040 --> 00:25:32,045 So I think it's a development that's starting to occur. 507 00:25:32,045 --> 00:25:34,170 Matthew, do you have a closing thought on Branscomb 508 00:25:34,170 --> 00:25:37,110 and Auerswald for us? 509 00:25:37,110 --> 00:25:38,750 MATTHEW: I can give a personal-- 510 00:25:38,750 --> 00:25:40,052 WILLIAM BONVILLIAN: Please. 511 00:25:40,052 --> 00:25:42,010 MATTHEW: I actually am a mechanical engineering 512 00:25:42,010 --> 00:25:44,510 and business minor. 513 00:25:44,510 --> 00:25:47,190 And I do think it's really valuable. 514 00:25:47,190 --> 00:25:49,920 At the same time, I think specialization 515 00:25:49,920 --> 00:25:52,890 is important to keep, because I know 516 00:25:52,890 --> 00:25:56,460 I'll never take as in-depth mechanical engineering classes 517 00:25:56,460 --> 00:25:57,990 as people who are just that studying 518 00:25:57,990 --> 00:25:59,860 that throughout their four years here. 519 00:25:59,860 --> 00:26:01,980 But I do think having more people 520 00:26:01,980 --> 00:26:07,440 with interdisciplinary degrees can help transition that gap. 521 00:26:07,440 --> 00:26:09,660 WILLIAM BONVILLIAN: Great, thank you. 522 00:26:09,660 --> 00:26:12,210 All right, so we're going to push along to our next reading 523 00:26:12,210 --> 00:26:14,340 here. 524 00:26:14,340 --> 00:26:20,550 And Vernon Ruttan is another one of our great growth economists. 525 00:26:20,550 --> 00:26:23,140 Ruttan taught at the University of Minnesota. 526 00:26:23,140 --> 00:26:30,930 And he really develops the whole concept of induced innovation. 527 00:26:30,930 --> 00:26:33,600 In other words, how does industry innovate, 528 00:26:33,600 --> 00:26:35,310 is really the problem he's looking at. 529 00:26:35,310 --> 00:26:37,770 Obviously, it's not just government agencies for sure. 530 00:26:37,770 --> 00:26:40,300 Industry does the great bulk of the innovation. 531 00:26:40,300 --> 00:26:44,710 So he studies induced innovation through his whole career, 532 00:26:44,710 --> 00:26:49,080 and develops a whole set of thinking about that doctrine. 533 00:26:49,080 --> 00:26:53,100 And then towards the end of his life, 534 00:26:53,100 --> 00:26:56,550 because he dies only a couple of years after writing this book, 535 00:26:56,550 --> 00:27:02,500 he goes back and looks at the Defense Innovation system. 536 00:27:02,500 --> 00:27:05,910 So he's looking at where these big strands 537 00:27:05,910 --> 00:27:11,700 of the American economy come from, things like aviation, 538 00:27:11,700 --> 00:27:19,720 space, electronics, nuclear power, computing, the internet. 539 00:27:19,720 --> 00:27:22,220 And I wouldn't say he stumbles, but he 540 00:27:22,220 --> 00:27:25,970 focuses on the Defense Innovation system, 541 00:27:25,970 --> 00:27:29,880 and starts to lay out for us what that's like. 542 00:27:29,880 --> 00:27:32,900 So we've just talked about the Vannevar Bush basic research 543 00:27:32,900 --> 00:27:36,470 only, peer-reviewed, basic science agency 544 00:27:36,470 --> 00:27:39,530 model that we tend to think of when we think 545 00:27:39,530 --> 00:27:42,170 about US R&D. That's the dominant model, 546 00:27:42,170 --> 00:27:44,330 certainly on the civilian side. 547 00:27:44,330 --> 00:27:47,060 But then there's this whole parallel universe 548 00:27:47,060 --> 00:27:50,330 that's organized in a very different way. 549 00:27:50,330 --> 00:27:53,630 And he goes back and traces the history, 550 00:27:53,630 --> 00:27:56,570 and has this very provocative title-- 551 00:27:56,570 --> 00:27:59,240 Is War Necessary for Economic Growth? 552 00:27:59,240 --> 00:28:03,650 Because the big innovation waves of the latter part 553 00:28:03,650 --> 00:28:07,580 of the 20th century, frankly, came out 554 00:28:07,580 --> 00:28:11,330 of that Defense Innovation system. 555 00:28:11,330 --> 00:28:13,790 Those are the big ways that I just listed. 556 00:28:13,790 --> 00:28:17,000 So what's going on here? 557 00:28:17,000 --> 00:28:23,290 And Ruttan tells a very interesting story that-- 558 00:28:23,290 --> 00:28:24,550 this didn't happen yesterday. 559 00:28:24,550 --> 00:28:26,092 He tells the story of the development 560 00:28:26,092 --> 00:28:29,380 of interchangeable machine-made parts, which, as you all know, 561 00:28:29,380 --> 00:28:33,235 is the core initial step towards mass production. 562 00:28:33,235 --> 00:28:35,110 And that gets developed in the United States. 563 00:28:35,110 --> 00:28:38,440 And how does it get developed? 564 00:28:38,440 --> 00:28:41,590 It gets developed by the War Department. 565 00:28:41,590 --> 00:28:44,530 And the War Department is, essentially-- 566 00:28:44,530 --> 00:28:49,390 you think of the early 19th century, 567 00:28:49,390 --> 00:28:52,790 muskets are made by hand. 568 00:28:52,790 --> 00:28:55,210 They're made by blacksmiths. 569 00:28:55,210 --> 00:28:57,070 Armorers they were called. 570 00:28:57,070 --> 00:29:01,960 And every army had to bring along a whole group of armorers 571 00:29:01,960 --> 00:29:04,810 to constantly keep its muskets repaired. 572 00:29:04,810 --> 00:29:07,268 And every time a part would break down, 573 00:29:07,268 --> 00:29:08,560 they'd have to make a new part. 574 00:29:08,560 --> 00:29:11,110 So they'd have to pull out their forge and their anvils 575 00:29:11,110 --> 00:29:14,620 and their hammers, and then model that part exactly 576 00:29:14,620 --> 00:29:16,300 so it would actually fit. 577 00:29:16,300 --> 00:29:18,760 Because no two parts were the same. 578 00:29:18,760 --> 00:29:21,110 They were not interchangeable. 579 00:29:21,110 --> 00:29:25,620 So Eli Whitney has a vision for interchangeable machine-made 580 00:29:25,620 --> 00:29:26,120 parts. 581 00:29:26,120 --> 00:29:27,900 Why Eli Whitney? 582 00:29:27,900 --> 00:29:29,650 You've heard of the cotton gin, of course, 583 00:29:29,650 --> 00:29:34,030 one of the key early 19th century simple machines 584 00:29:34,030 --> 00:29:37,570 that launched the industrial economy in the United States. 585 00:29:37,570 --> 00:29:42,300 But Whitney's got a big problem with the cotton gin. 586 00:29:42,300 --> 00:29:43,200 Anybody can make one. 587 00:29:43,200 --> 00:29:47,220 You can see this thing, and any decent mechanic 588 00:29:47,220 --> 00:29:50,190 all over the country could essentially replicate it. 589 00:29:50,190 --> 00:29:53,940 So he's faced with massive patent violations. 590 00:29:53,940 --> 00:29:56,110 And he's handling lawsuits all over the country. 591 00:29:56,110 --> 00:29:57,480 He can't manage this. 592 00:29:57,480 --> 00:30:01,440 So he has this remarkable invention, 593 00:30:01,440 --> 00:30:03,780 but he can't capture any revenue off it. 594 00:30:03,780 --> 00:30:09,940 So being a good US industrialist, what do you do? 595 00:30:09,940 --> 00:30:13,780 The War Department bailout, that's what you do, right? 596 00:30:13,780 --> 00:30:17,830 So he goes to his friends and colleagues in the War 597 00:30:17,830 --> 00:30:20,095 Department and paints this vision. 598 00:30:23,240 --> 00:30:25,900 Why make muskets by hand? 599 00:30:25,900 --> 00:30:29,370 I'll give you interchangeable machine-made parts. 600 00:30:29,370 --> 00:30:32,590 We'll drive the costs through the floor. 601 00:30:32,590 --> 00:30:36,190 And you won't have to have these armor trains dragging down 602 00:30:36,190 --> 00:30:38,500 the speed of your armies. 603 00:30:38,500 --> 00:30:41,350 We'll just have a bunch of parts in boxes. 604 00:30:41,350 --> 00:30:44,690 And you'll just snap them in, and they'll be interchangeable. 605 00:30:44,690 --> 00:30:49,545 It's a wonderful vision, and he sells it to the War Department. 606 00:30:49,545 --> 00:30:50,170 And guess what? 607 00:30:50,170 --> 00:30:51,820 He gets something that's the equivalent 608 00:30:51,820 --> 00:30:56,020 of a cost-plus contract, every industrialist's dream. 609 00:30:56,020 --> 00:30:59,770 Whatever you need to spend, spend it. 610 00:30:59,770 --> 00:31:02,340 It's consistent with our contract terms. 611 00:31:02,340 --> 00:31:06,580 So he turns his factory in North Haven, Connecticut, just north 612 00:31:06,580 --> 00:31:10,990 of New Haven, into an attempt to develop 613 00:31:10,990 --> 00:31:12,460 interchangeable machine-made parts. 614 00:31:12,460 --> 00:31:15,040 He doesn't quite get there. 615 00:31:15,040 --> 00:31:17,590 This requires really creating the whole first generation 616 00:31:17,590 --> 00:31:20,100 of machine tools. 617 00:31:20,100 --> 00:31:21,900 And he isn't quite able to pull it off. 618 00:31:21,900 --> 00:31:25,290 You have a whole new way of organizing the workforce 619 00:31:25,290 --> 00:31:28,560 around division of labor and around specific differentiated 620 00:31:28,560 --> 00:31:30,390 tasks for the workforce. 621 00:31:30,390 --> 00:31:33,450 So it carries all kinds of organizational implications 622 00:31:33,450 --> 00:31:37,940 with it, so that each part of the labor force 623 00:31:37,940 --> 00:31:41,150 is mastering one set of tasks related to a production system. 624 00:31:41,150 --> 00:31:43,310 All these things are starting to happen 625 00:31:43,310 --> 00:31:46,780 in that North Haven facility of his. 626 00:31:46,780 --> 00:31:49,348 And there's now a museum setting that's 627 00:31:49,348 --> 00:31:51,890 around this, so you can go tramp the sites where all this was 628 00:31:51,890 --> 00:31:54,050 happening in North Haven. 629 00:31:54,050 --> 00:31:55,460 But he doesn't quite pull it off. 630 00:31:55,460 --> 00:32:01,910 But meanwhile, there's two armories, 631 00:32:01,910 --> 00:32:05,270 one in Harpers Ferry, West Virginia, 632 00:32:05,270 --> 00:32:08,540 and the other in Springfield, Massachusetts. 633 00:32:08,540 --> 00:32:13,430 And these armories are pursuing the same project, 634 00:32:13,430 --> 00:32:16,790 because it's so key to the War Department. 635 00:32:16,790 --> 00:32:19,130 It's an absolutely critical technology capability 636 00:32:19,130 --> 00:32:21,530 the War Department needs. 637 00:32:21,530 --> 00:32:25,460 And the story that Ruttan picks up 638 00:32:25,460 --> 00:32:30,770 is the story of John Hall, who runs the Harpers Ferry arsenal. 639 00:32:30,770 --> 00:32:35,830 And over an extended period of time, over many, many years, 640 00:32:35,830 --> 00:32:40,780 he eventually perfects the machine tools 641 00:32:40,780 --> 00:32:43,810 that will enable the creation of these interchangeable 642 00:32:43,810 --> 00:32:46,210 machine-made parts. 643 00:32:46,210 --> 00:32:49,550 And it's a remarkable story. 644 00:32:49,550 --> 00:32:55,810 And only the long-term patience and capital 645 00:32:55,810 --> 00:32:59,050 of a government agency is going to tolerate 646 00:32:59,050 --> 00:33:00,685 this kind of 20-year project. 647 00:33:04,130 --> 00:33:07,540 Interesting, the minute he gets it done, 648 00:33:07,540 --> 00:33:11,740 other industrialists understand what the accomplishment is. 649 00:33:11,740 --> 00:33:17,880 So Congress forces Hall and the Army 650 00:33:17,880 --> 00:33:20,790 to throw the patent essentially into the commons 651 00:33:20,790 --> 00:33:22,830 and be accessible to others. 652 00:33:22,830 --> 00:33:27,960 So that stands up the whole early industrial economy 653 00:33:27,960 --> 00:33:31,380 of New England, building these simple machines. 654 00:33:31,380 --> 00:33:33,720 So you can go to Connecticut towns, 655 00:33:33,720 --> 00:33:36,420 Massachusetts towns, which are blessed 656 00:33:36,420 --> 00:33:39,550 with fairly small, slow-moving water power, 657 00:33:39,550 --> 00:33:43,350 because that's the power source, that moves fairly steadily. 658 00:33:43,350 --> 00:33:44,460 It doesn't flood a lot. 659 00:33:44,460 --> 00:33:50,820 This is an ideal region for water-powered energy 660 00:33:50,820 --> 00:33:53,864 do the building here to power the mills. 661 00:33:53,864 --> 00:33:57,690 AUDIENCE: So you said John Hall goes and makes 662 00:33:57,690 --> 00:34:00,803 the patents open to the public? 663 00:34:00,803 --> 00:34:02,720 WILLIAM BONVILLIAN: Well, the Congress force-- 664 00:34:02,720 --> 00:34:06,970 Congress passes legislation that precludes the Army and Hall 665 00:34:06,970 --> 00:34:07,970 from having the patents. 666 00:34:07,970 --> 00:34:10,489 In effect, they make them available to others. 667 00:34:10,489 --> 00:34:12,383 That turns out to be of great benefit, 668 00:34:12,383 --> 00:34:14,300 because then this interchangeable machine-made 669 00:34:14,300 --> 00:34:16,694 parts model can get picked up by everybody. 670 00:34:16,694 --> 00:34:19,194 AUDIENCE: I guess it would be a huge benefit of the country. 671 00:34:19,194 --> 00:34:21,739 But then people like John Hall, doesn't it 672 00:34:21,739 --> 00:34:24,170 give them a pretty strong incentive not to do something 673 00:34:24,170 --> 00:34:24,380 like that? 674 00:34:24,380 --> 00:34:25,520 WILLIAM BONVILLIAN: Yes, it would give someone 675 00:34:25,520 --> 00:34:27,440 a pretty strong incentive not to spend 676 00:34:27,440 --> 00:34:30,123 20 years of their lives working on this stuff, yes. 677 00:34:30,123 --> 00:34:32,040 But of course, he is working for the military. 678 00:34:32,040 --> 00:34:36,600 So it's not as if he would capitalize alone on this. 679 00:34:36,600 --> 00:34:38,949 But overall, it's a positive. 680 00:34:38,949 --> 00:34:42,280 And the power of those New England companies 681 00:34:42,280 --> 00:34:44,530 to get their congressional delegation 682 00:34:44,530 --> 00:34:47,520 to kind of take that patent away and put it out, 683 00:34:47,520 --> 00:34:49,389 it's an important political lesson. 684 00:34:49,389 --> 00:34:51,820 It was just too valuable for the Army to own it. 685 00:34:54,429 --> 00:34:58,870 So this creates the Connecticut River Valley 686 00:34:58,870 --> 00:35:01,570 of all these small, simple machine industries. 687 00:35:01,570 --> 00:35:04,330 Clocks are famous in New England. 688 00:35:04,330 --> 00:35:08,740 Muskets are famous up and down the Connecticut River Valley. 689 00:35:08,740 --> 00:35:12,430 All these kind of early fairly simple machines get built here, 690 00:35:12,430 --> 00:35:15,610 and that's the New England industrial economy. 691 00:35:15,610 --> 00:35:18,550 That is the first place the US to really-- 692 00:35:18,550 --> 00:35:20,680 obviously textiles are developing in parallel, 693 00:35:20,680 --> 00:35:22,330 including in Massachusetts. 694 00:35:22,330 --> 00:35:24,940 But this system of other hard technologies 695 00:35:24,940 --> 00:35:28,990 and simpler machines starts to take off pretty explosively. 696 00:35:28,990 --> 00:35:34,000 So the lesson here that Ruttan is pointing us towards 697 00:35:34,000 --> 00:35:37,180 is how the military can operate and the private sector 698 00:35:37,180 --> 00:35:38,020 can't operate. 699 00:35:38,020 --> 00:35:42,910 The military is willing to take a couple of decades-long effort 700 00:35:42,910 --> 00:35:46,750 and spend whatever is needed to get that technology perfected, 701 00:35:46,750 --> 00:35:48,640 because they really need it. 702 00:35:48,640 --> 00:35:51,370 Those risks are too high and the cost 703 00:35:51,370 --> 00:35:55,240 is too high for the private sector to manage. 704 00:35:55,240 --> 00:35:58,180 So that's his underlying point here, 705 00:35:58,180 --> 00:36:01,600 that the military is going to be able to do things 706 00:36:01,600 --> 00:36:03,790 that the civilian sector is not going 707 00:36:03,790 --> 00:36:09,640 to be able to do in the technology standup process. 708 00:36:09,640 --> 00:36:13,800 We skip time, right? 709 00:36:13,800 --> 00:36:17,040 I always try to provide some MIT material in the class. 710 00:36:17,040 --> 00:36:20,870 And this is Whirlwind, right? 711 00:36:27,980 --> 00:36:32,870 Mainframe computers had been created by the late '40s, 712 00:36:32,870 --> 00:36:34,560 early '50s. 713 00:36:34,560 --> 00:36:37,260 So there are a number-- you can number them on one hand, 714 00:36:37,260 --> 00:36:39,870 but there's a number being stood up around the country, 715 00:36:39,870 --> 00:36:42,290 particularly coming out of Mauchly and Eckert. 716 00:36:46,550 --> 00:36:48,840 And the UNIVAC generation machines 717 00:36:48,840 --> 00:36:51,090 came out of the University of Pennsylvania Engineering 718 00:36:51,090 --> 00:36:52,730 School. 719 00:36:52,730 --> 00:36:54,950 But MIT, of course, wants to play in this game. 720 00:36:54,950 --> 00:36:59,780 So Jay Forrester, a great MIT technologist, 721 00:36:59,780 --> 00:37:08,010 persuades the Navy to develop a mainframe flight simulator. 722 00:37:08,010 --> 00:37:10,740 Now, the problem with having a flight simulator 723 00:37:10,740 --> 00:37:13,320 is that it has to operate in real-time. 724 00:37:13,320 --> 00:37:18,490 So the other mainframes tended to be gigantic calculators. 725 00:37:18,490 --> 00:37:20,980 This thing is different. 726 00:37:20,980 --> 00:37:24,310 And to operate in real-time, you have to have memory. 727 00:37:24,310 --> 00:37:27,730 And Forrester and one of his graduate students 728 00:37:27,730 --> 00:37:31,120 create the magnetic core memory that's 729 00:37:31,120 --> 00:37:35,200 part of this Whirlwind system. 730 00:37:35,200 --> 00:37:39,010 Now, this is a time also of Defense cutbacks. 731 00:37:39,010 --> 00:37:43,830 So the Navy actually pulls the contract 732 00:37:43,830 --> 00:37:46,410 on the Whirlwind system. 733 00:37:46,410 --> 00:37:51,510 But also at MIT is a professor named George Valley. 734 00:37:51,510 --> 00:37:56,260 And George Valley was a veteran of the Rad Lab in World War II, 735 00:37:56,260 --> 00:37:58,030 teaching at MIT. 736 00:37:58,030 --> 00:38:07,120 And he comes to the realization that the Soviet Union 737 00:38:07,120 --> 00:38:12,560 has developed a bomber fleet of sufficient long-range 738 00:38:12,560 --> 00:38:14,990 that they could undertake a first strike 739 00:38:14,990 --> 00:38:17,000 with atomic weapons, because they developed 740 00:38:17,000 --> 00:38:19,740 the atomic bomb in 1949. 741 00:38:19,740 --> 00:38:23,430 And there was nothing, nothing standing in their way. 742 00:38:23,430 --> 00:38:27,180 We would have no idea they were coming until it was too late. 743 00:38:27,180 --> 00:38:31,370 So Valley is an advisor to the Air Force. 744 00:38:31,370 --> 00:38:34,123 And he gets the Air Force in particular 745 00:38:34,123 --> 00:38:35,790 are really concerned about this problem. 746 00:38:35,790 --> 00:38:37,310 And boy, is it a real problem. 747 00:38:37,310 --> 00:38:39,680 It's a real problem. 748 00:38:39,680 --> 00:38:43,167 So Valley persuades the Air Force 749 00:38:43,167 --> 00:38:44,750 that they're going to have to stand up 750 00:38:44,750 --> 00:38:48,490 a whole new airborne warning defense system. 751 00:38:52,110 --> 00:38:53,520 What's he going to do? 752 00:38:53,520 --> 00:38:55,650 It's an incredibly complex network. 753 00:38:55,650 --> 00:38:59,100 It's going to have to get stood up all across, like, the Arctic 754 00:38:59,100 --> 00:39:02,047 and out into the North Atlantic on ships. 755 00:39:02,047 --> 00:39:03,630 And there's going to have to be planes 756 00:39:03,630 --> 00:39:05,130 with radar systems flying. 757 00:39:05,130 --> 00:39:08,010 And there's going to have to be radar installations 758 00:39:08,010 --> 00:39:11,760 all over northern Canada. 759 00:39:11,760 --> 00:39:14,670 In effect, they're going to have to build a radar interception 760 00:39:14,670 --> 00:39:15,570 network. 761 00:39:15,570 --> 00:39:18,120 And then these varying messages are all 762 00:39:18,120 --> 00:39:20,670 going to have to come to a single place. 763 00:39:20,670 --> 00:39:23,400 And you don't have a lot of time here. 764 00:39:23,400 --> 00:39:26,040 And the messages have got to be understood, and then 765 00:39:26,040 --> 00:39:28,410 transmitted to decision-makers to make 766 00:39:28,410 --> 00:39:30,573 a decision on what they do. 767 00:39:30,573 --> 00:39:31,990 It's a really complicated problem. 768 00:39:31,990 --> 00:39:35,710 So Valley realizes, I'm going to need a computer. 769 00:39:38,838 --> 00:39:43,350 He's walking around MIT, where else but the Infinite Corridor. 770 00:39:43,350 --> 00:39:47,360 And he bumps into Forrester, and discovers Forrester 771 00:39:47,360 --> 00:39:52,420 is actually building a big computer, Whirlwind. 772 00:39:52,420 --> 00:39:59,800 And Valley says, we need it for this new early warning defense 773 00:39:59,800 --> 00:40:01,390 system. 774 00:40:01,390 --> 00:40:07,650 And he enlists Forrester, who's over here. 775 00:40:10,950 --> 00:40:13,980 Because it's real-time computing, it's different. 776 00:40:13,980 --> 00:40:15,570 It's not just a big calculator. 777 00:40:19,203 --> 00:40:20,620 Look at this lady sitting in front 778 00:40:20,620 --> 00:40:23,200 of a keyboard with a cathode ray tube. 779 00:40:26,960 --> 00:40:27,720 That's this. 780 00:40:27,720 --> 00:40:29,900 That's this thing. 781 00:40:29,900 --> 00:40:34,370 That's not a standard mainframe from ENIAC or UNIVAC. 782 00:40:34,370 --> 00:40:37,550 That's this thing, right? 783 00:40:37,550 --> 00:40:41,680 That's what they stumble on to. 784 00:40:41,680 --> 00:40:43,680 And look at this. 785 00:40:43,680 --> 00:40:46,200 Here's an Air Force corporal sitting in front 786 00:40:46,200 --> 00:40:48,450 of the cathode ray tube. 787 00:40:48,450 --> 00:40:50,690 Signaling is coming in. 788 00:40:50,690 --> 00:40:54,760 You guessed it-- signals across telephone lines. 789 00:40:58,600 --> 00:41:01,180 So the radar signals are being sent to a central location 790 00:41:01,180 --> 00:41:04,830 across telephone lines. 791 00:41:04,830 --> 00:41:09,040 He's got this kind of gun in his hand. 792 00:41:11,590 --> 00:41:14,020 It's like an electronic gun. 793 00:41:14,020 --> 00:41:15,640 It's the mouse. 794 00:41:15,640 --> 00:41:17,370 That's what it is. 795 00:41:17,370 --> 00:41:20,170 You point on it, you get a readout 796 00:41:20,170 --> 00:41:21,970 of what the signal means. 797 00:41:21,970 --> 00:41:26,050 So here it is, like in the early '50s. 798 00:41:26,050 --> 00:41:26,910 That's Whirlwind. 799 00:41:26,910 --> 00:41:28,600 That's SAGE. 800 00:41:28,600 --> 00:41:32,710 Lincoln Lab has to get created to really drive the research, 801 00:41:32,710 --> 00:41:35,470 because it's not just going to happen in professors' labs 802 00:41:35,470 --> 00:41:37,990 in MIT. 803 00:41:37,990 --> 00:41:41,320 MIT starts to make these computers, and decides, 804 00:41:41,320 --> 00:41:44,190 we don't want to be in the computer business. 805 00:41:44,190 --> 00:41:51,670 So the contract is given to IBM to make the computers. 806 00:41:51,670 --> 00:41:55,480 And that becomes IBM 700 series, it's 807 00:41:55,480 --> 00:41:58,370 first really big important set of computers. 808 00:41:58,370 --> 00:42:01,660 So you begin to get an idea of the ramifications of pursuing 809 00:42:01,660 --> 00:42:07,003 this Defense project at the scale 810 00:42:07,003 --> 00:42:08,920 that the Air Force is willing to pursue it at. 811 00:42:08,920 --> 00:42:10,582 I'll just tell you one more story. 812 00:42:10,582 --> 00:42:12,040 At the end of World War II, there's 813 00:42:12,040 --> 00:42:16,800 two countries that are making a lot of progress on computing. 814 00:42:16,800 --> 00:42:20,650 The British have made a lot of progress 815 00:42:20,650 --> 00:42:23,770 at Bletchley Park on computing, because they have 816 00:42:23,770 --> 00:42:25,720 to cope with the U-boat threat. 817 00:42:25,720 --> 00:42:30,250 And they have to decipher these incredibly complex Enigma 818 00:42:30,250 --> 00:42:34,820 signals that the German communication system relies on. 819 00:42:34,820 --> 00:42:38,293 It's really quite capable cryptography. 820 00:42:38,293 --> 00:42:40,210 And they develop computers to be able to break 821 00:42:40,210 --> 00:42:41,002 those signals down. 822 00:42:41,002 --> 00:42:42,370 So the British are going well. 823 00:42:42,370 --> 00:42:44,578 And they share a lot of that information with the US, 824 00:42:44,578 --> 00:42:49,050 and we develop comparable encryption capability. 825 00:42:49,050 --> 00:42:54,470 End of Wordl War II, Britain dismantles its war machine, 826 00:42:54,470 --> 00:42:58,790 cancels its nascent computing operations. 827 00:42:58,790 --> 00:43:06,000 There is one company in Britain that picks up computing. 828 00:43:06,000 --> 00:43:07,140 It's a tea biscuit company. 829 00:43:09,990 --> 00:43:13,770 At 4 o'clock, everybody's got to get tea. 830 00:43:13,770 --> 00:43:17,283 And at 4 o'clock, everybody's got to have fresh tea biscuits 831 00:43:17,283 --> 00:43:18,450 right there in the tea shop. 832 00:43:21,130 --> 00:43:23,590 It's a very complicated problem. 833 00:43:23,590 --> 00:43:27,190 It involves incredibly complex railroad time schedules 834 00:43:27,190 --> 00:43:31,660 and analysis of delay and delay factors. 835 00:43:31,660 --> 00:43:33,550 And they need a computer, so they 836 00:43:33,550 --> 00:43:36,667 take the wartime computers the British have been developing. 837 00:43:36,667 --> 00:43:38,500 And they develop this whole computing system 838 00:43:38,500 --> 00:43:41,320 for getting tea biscuits throughout the British Isles 839 00:43:41,320 --> 00:43:44,770 at 4 o'clock in the afternoon at all the tea shops. 840 00:43:44,770 --> 00:43:47,920 That's one development project. 841 00:43:47,920 --> 00:43:51,520 The other development project on the other side of the Atlantic 842 00:43:51,520 --> 00:43:55,150 is the United States Air Force. 843 00:43:55,150 --> 00:43:57,970 They're beginning to develop missile technology 844 00:43:57,970 --> 00:44:00,040 and ballistic missile technology. 845 00:44:00,040 --> 00:44:01,900 And boy, does that require computing. 846 00:44:01,900 --> 00:44:06,020 Getting those trajectories right really requires computing. 847 00:44:06,020 --> 00:44:08,610 Who does the IT revolution, the tea company or the US Air 848 00:44:08,610 --> 00:44:09,110 Force? 849 00:44:09,110 --> 00:44:10,130 Who wins? 850 00:44:10,130 --> 00:44:12,680 You can only guess. 851 00:44:12,680 --> 00:44:15,050 So that's how these things happen. 852 00:44:15,050 --> 00:44:16,950 There's often foundational stories. 853 00:44:16,950 --> 00:44:18,530 They're pretty key here. 854 00:44:18,530 --> 00:44:19,905 But you get that rough comparison 855 00:44:19,905 --> 00:44:22,072 of what you're up against, if you're the British tea 856 00:44:22,072 --> 00:44:24,350 company trying to develop computing versus the US Air 857 00:44:24,350 --> 00:44:24,850 Force. 858 00:44:24,850 --> 00:44:27,950 The US Air Force is doing this stuff-- 859 00:44:27,950 --> 00:44:32,210 magnetic core memory, the mouse, the cathode ray. 860 00:44:32,210 --> 00:44:34,930 They're putting all these pieces together 861 00:44:34,930 --> 00:44:38,590 that become foundational. 862 00:44:38,590 --> 00:44:42,920 The Whirlwind project becomes the SAGE project. 863 00:44:42,920 --> 00:44:46,130 And that becomes really critical for a lot 864 00:44:46,130 --> 00:44:50,500 of early computing, particularly real-time computing. 865 00:44:50,500 --> 00:44:52,840 The Defense Department goes on to semiconductors. 866 00:44:52,840 --> 00:44:57,670 It goes on with key work in all kinds of semiconductor 867 00:44:57,670 --> 00:44:58,382 technologies. 868 00:44:58,382 --> 00:45:00,490 It goes on to supercomputing, leading 869 00:45:00,490 --> 00:45:02,515 that, all kinds of advances in software. 870 00:45:04,930 --> 00:45:06,430 When we talk about DARPA, we'll talk 871 00:45:06,430 --> 00:45:09,520 about the development of personal computing 872 00:45:09,520 --> 00:45:13,200 in the network and the internet. 873 00:45:13,200 --> 00:45:21,670 But it's a powerful story of this Defense Innovation system 874 00:45:21,670 --> 00:45:26,780 and the role that it plays in the US economy 875 00:45:26,780 --> 00:45:29,990 in the second half of the 20th century. 876 00:45:29,990 --> 00:45:32,970 So which of you has got-- 877 00:45:32,970 --> 00:45:34,700 Matthew again, all right. 878 00:45:34,700 --> 00:45:35,580 You're up. 879 00:45:35,580 --> 00:45:39,230 MATTHEW: Yeahl so there are definitely a lot of examples 880 00:45:39,230 --> 00:45:41,340 that Ruttan gives. 881 00:45:41,340 --> 00:45:45,090 And his thesis was that maybe these technological 882 00:45:45,090 --> 00:45:48,420 developments would have happened anyway, but that urgency of war 883 00:45:48,420 --> 00:45:50,320 made these happen a lot faster. 884 00:45:50,320 --> 00:45:53,160 And you see the DOD becoming, in his eyes, 885 00:45:53,160 --> 00:45:55,710 the major organization that's kind of funding 886 00:45:55,710 --> 00:45:58,005 this technological development. 887 00:45:58,005 --> 00:46:00,080 So I think the one question we really 888 00:46:00,080 --> 00:46:03,892 to need to ask is, is war necessary for economic growth? 889 00:46:03,892 --> 00:46:06,350 WILLIAM BONVILLIAN: That would be the foundational question 890 00:46:06,350 --> 00:46:08,330 at the least. 891 00:46:08,330 --> 00:46:09,330 That's a great question. 892 00:46:09,330 --> 00:46:12,770 I mean, it's a great question. 893 00:46:12,770 --> 00:46:16,550 AUDIENCE: Well, I have a counter question to that. 894 00:46:16,550 --> 00:46:19,400 Maybe rather than war, maybe what's really required 895 00:46:19,400 --> 00:46:20,750 is DOD funding. 896 00:46:23,503 --> 00:46:24,920 Throughout a lot of this, granted, 897 00:46:24,920 --> 00:46:27,710 there was a lot of Cold War paranoia that was fueling this. 898 00:46:27,710 --> 00:46:30,410 And that was fueled on all these advances. 899 00:46:30,410 --> 00:46:35,900 But you could still paint a lot of the problems that 900 00:46:35,900 --> 00:46:39,067 face us today as national security risks. 901 00:46:39,067 --> 00:46:41,150 And then you could get a similar level of urgency. 902 00:46:41,150 --> 00:46:42,525 Even though we're not technically 903 00:46:42,525 --> 00:46:46,997 at a war with, say, the climate, you can't really shoot that. 904 00:46:46,997 --> 00:46:48,330 And you kind of need it to live. 905 00:46:48,330 --> 00:46:55,926 So maybe it's less about war and more just 906 00:46:55,926 --> 00:46:58,185 a sense of priorities. 907 00:46:58,185 --> 00:47:00,060 AUDIENCE: I think that's a really good point. 908 00:47:00,060 --> 00:47:04,470 Pretty much every presidential campaign debate 909 00:47:04,470 --> 00:47:06,040 I've ever watched, there's always 910 00:47:06,040 --> 00:47:08,373 the essential question they ask, where they're like, oh, 911 00:47:08,373 --> 00:47:10,065 what's the biggest risk that you think 912 00:47:10,065 --> 00:47:11,190 is facing our nation today. 913 00:47:11,190 --> 00:47:13,680 And often one of the answers is climate change. 914 00:47:13,680 --> 00:47:18,180 So I think that might be a really key part of rephrasing 915 00:47:18,180 --> 00:47:21,900 or reorienting our perspective to maybe start 916 00:47:21,900 --> 00:47:24,150 re-allocating funding towards what 917 00:47:24,150 --> 00:47:26,640 is necessary for the welfare of the nation that might not 918 00:47:26,640 --> 00:47:31,490 always be another nation's intentions. 919 00:47:31,490 --> 00:47:34,370 AUDIENCE: Yeah, I think he used it as a provocative title. 920 00:47:34,370 --> 00:47:36,860 But it should have actually been called, 921 00:47:36,860 --> 00:47:40,190 Is the Threat of War Necessary for Economic Growth, 922 00:47:40,190 --> 00:47:42,980 because I think there's a stronger argument for that. 923 00:47:42,980 --> 00:47:49,700 Yeah, threat makes us put funding into national security 924 00:47:49,700 --> 00:47:50,900 technologies. 925 00:47:50,900 --> 00:47:55,160 Also we've talked a bit about Japan's manufacturing 926 00:47:55,160 --> 00:47:55,790 innovation. 927 00:47:55,790 --> 00:47:58,435 And I don't think that was spurred by war 928 00:47:58,435 --> 00:47:59,310 or the threat of war. 929 00:47:59,310 --> 00:48:01,785 So it's caveats. 930 00:48:01,785 --> 00:48:04,160 WILLIAM BONVILLIAN: Yeah, and you make an important point 931 00:48:04,160 --> 00:48:04,660 here, too. 932 00:48:04,660 --> 00:48:09,290 Which is, the US is pretty unique in putting 933 00:48:09,290 --> 00:48:12,720 national security at the center of its innovation system. 934 00:48:12,720 --> 00:48:13,970 Other countries don't do that. 935 00:48:13,970 --> 00:48:15,410 For sure, Japan doesn't. 936 00:48:15,410 --> 00:48:18,350 For sure, Germany does not at this stage. 937 00:48:18,350 --> 00:48:22,470 So other countries have other organizational motivations 938 00:48:22,470 --> 00:48:25,700 than, as you put it, the threat of war. 939 00:48:25,700 --> 00:48:27,350 But it's a powerful one in our country. 940 00:48:27,350 --> 00:48:29,683 AUDIENCE: Yeah, that's the other point I wanted to make, 941 00:48:29,683 --> 00:48:32,300 is that I think Ruttan was very United States-centric just 942 00:48:32,300 --> 00:48:36,590 throughout our entire reading. 943 00:48:36,590 --> 00:48:39,470 MATTHEW: So with that in mind, is there 944 00:48:39,470 --> 00:48:44,620 anything to worry about the $54 billion 945 00:48:44,620 --> 00:48:50,390 cut to science and basic science research, 946 00:48:50,390 --> 00:48:53,870 and reallocating that towards national security 947 00:48:53,870 --> 00:48:57,590 defense, if that's going to go to the DOD anyway? 948 00:48:57,590 --> 00:49:01,578 AUDIENCE: Well, I guess I could get a job flipping burgers. 949 00:49:01,578 --> 00:49:03,620 WILLIAM BONVILLIAN: I don't think the $54 billion 950 00:49:03,620 --> 00:49:08,040 will necessarily go into Defense R&D. 951 00:49:08,040 --> 00:49:09,590 And obviously, the entire $54 billion 952 00:49:09,590 --> 00:49:12,270 didn't come out of the domestic side either, 953 00:49:12,270 --> 00:49:15,210 but there are very significant cuts to US science 954 00:49:15,210 --> 00:49:16,385 on the civilian side. 955 00:49:16,385 --> 00:49:17,760 I don't think they're going to be 956 00:49:17,760 --> 00:49:21,970 offset by corresponding increases on the defense side. 957 00:49:21,970 --> 00:49:24,328 We should be so lucky. 958 00:49:24,328 --> 00:49:26,745 But I think, Matthew, you're driving an interesting point. 959 00:49:29,350 --> 00:49:31,460 Suppose there's no war, right? 960 00:49:31,460 --> 00:49:34,870 What's the motivator we're going to use 961 00:49:34,870 --> 00:49:37,381 to drive a technology advance? 962 00:49:44,600 --> 00:49:47,030 MATTHEW: I think one person mentioned in their question 963 00:49:47,030 --> 00:49:51,220 if maybe international competition could replace 964 00:49:51,220 --> 00:49:53,210 kind of that sense of urgency. 965 00:49:56,970 --> 00:49:59,522 AUDIENCE: Yeah, I think it's just a question of, 966 00:49:59,522 --> 00:50:01,480 what are your priorities at the current moment, 967 00:50:01,480 --> 00:50:03,760 and what can you make urgent enough just 968 00:50:03,760 --> 00:50:10,510 to justify kind of large-scale, huge, not just funding, 969 00:50:10,510 --> 00:50:15,260 but reorganization around maybe computers or key principles. 970 00:50:15,260 --> 00:50:17,530 And so in this case, I guess it was a threat of war. 971 00:50:17,530 --> 00:50:23,420 But you could probably argue, around the time of-- 972 00:50:23,420 --> 00:50:24,290 man, I'm forgetting. 973 00:50:24,290 --> 00:50:27,400 But there's probably some public health epidemic 974 00:50:27,400 --> 00:50:28,900 that you could argue that would have 975 00:50:28,900 --> 00:50:34,650 spurred massive bioresearch in that area. 976 00:50:34,650 --> 00:50:37,120 And I think that can also happen internationally. 977 00:50:37,120 --> 00:50:38,590 So you think maybe the development 978 00:50:38,590 --> 00:50:40,180 of an epidemic in a different country 979 00:50:40,180 --> 00:50:43,150 could also spur bioresearch in other countries 980 00:50:43,150 --> 00:50:45,320 to supplement or help. 981 00:50:45,320 --> 00:50:48,430 And so I think we could even generalize even further 982 00:50:48,430 --> 00:50:53,210 and just say, is threat necessary for economic growth? 983 00:50:53,210 --> 00:50:55,660 AUDIENCE: I think the big point about war 984 00:50:55,660 --> 00:50:58,270 is that you're a kind of centralizing everyone 985 00:50:58,270 --> 00:50:59,500 towards a common cause. 986 00:50:59,500 --> 00:51:01,450 So I think a lot of the initiatives 987 00:51:01,450 --> 00:51:06,040 nowadays, like the Cancer Moonshoot or even the push 988 00:51:06,040 --> 00:51:08,860 around getting a drug out there for CF, 989 00:51:08,860 --> 00:51:12,640 like those targeted initiatives towards a certain cause, 990 00:51:12,640 --> 00:51:16,690 I think those could be one way to target 991 00:51:16,690 --> 00:51:20,380 the need for development in a certain area, 992 00:51:20,380 --> 00:51:26,800 in times of peace, where you don't have a war impending. 993 00:51:26,800 --> 00:51:28,880 AUDIENCE: One thing I thought was interesting, 994 00:51:28,880 --> 00:51:31,640 especially when people were discussing the increase in DOD 995 00:51:31,640 --> 00:51:33,670 funding, despite the fact that we're not really 996 00:51:33,670 --> 00:51:39,910 in a World War II era of war, I've noticed that-- 997 00:51:39,910 --> 00:51:41,625 how much of MIT's funding is DOD? 998 00:51:41,625 --> 00:51:42,892 It's like half, right? 999 00:51:42,892 --> 00:51:43,850 WILLIAM BONVILLIAN: No. 1000 00:51:43,850 --> 00:51:44,190 AUDIENCE: It's not. 1001 00:51:44,190 --> 00:51:45,440 WILLIAM BONVILLIAN: Not close. 1002 00:51:45,440 --> 00:51:48,103 AUDIENCE: Oh, it might be just the Nuclear department then, 1003 00:51:48,103 --> 00:51:49,030 which makes sense. 1004 00:51:49,030 --> 00:51:53,340 WILLIAM BONVILLIAN: Yes, that makes sense. 1005 00:51:53,340 --> 00:51:54,330 I don't know. 1006 00:51:54,330 --> 00:51:58,500 It's like in the 18% range of federal research funding. 1007 00:51:58,500 --> 00:52:03,120 So NIH and DOD are just about equal at MIT, 1008 00:52:03,120 --> 00:52:08,070 in terms of originating research funding for the university. 1009 00:52:08,070 --> 00:52:11,400 MIT tends to be somewhat higher in defense research 1010 00:52:11,400 --> 00:52:12,690 than most universities. 1011 00:52:15,550 --> 00:52:16,565 It's not close to half. 1012 00:52:16,565 --> 00:52:18,440 AUDIENCE: So the point that I wanted to make, 1013 00:52:18,440 --> 00:52:23,200 though, regardless of the exact number, 1014 00:52:23,200 --> 00:52:26,080 I'm sure that a lot of DOD money is spent on things that 1015 00:52:26,080 --> 00:52:27,880 don't necessarily have applications 1016 00:52:27,880 --> 00:52:30,610 of, say, building a better tank or a better missile 1017 00:52:30,610 --> 00:52:33,070 or anything like that. 1018 00:52:33,070 --> 00:52:35,590 So just because some things have the label 1019 00:52:35,590 --> 00:52:37,548 and are under the Department of Defense, 1020 00:52:37,548 --> 00:52:39,340 that does not necessarily mean that they're 1021 00:52:39,340 --> 00:52:42,651 going strictly toward learning how to fight a new enemy. 1022 00:52:42,651 --> 00:52:45,950 I'm just curious what your thoughts are. 1023 00:52:45,950 --> 00:52:47,430 AUDIENCE: Can you rephrase that? 1024 00:52:47,430 --> 00:52:47,972 AUDIENCE: OK. 1025 00:52:51,450 --> 00:52:54,780 So MIT, we don't really research building 1026 00:52:54,780 --> 00:52:56,520 better guns and bombs, right? 1027 00:52:56,520 --> 00:52:57,860 WILLIAM BONVILLIAN: Correct. 1028 00:52:57,860 --> 00:52:59,895 And we don't do classified research either. 1029 00:52:59,895 --> 00:53:00,520 AUDIENCE: Yeah. 1030 00:53:00,520 --> 00:53:05,185 So just because we have a lot of DOD funding coming our way, 1031 00:53:05,185 --> 00:53:06,810 it does not necessarily mean that we're 1032 00:53:06,810 --> 00:53:09,180 researching better ways to kill people 1033 00:53:09,180 --> 00:53:11,190 or to keep ourselves from being killed. 1034 00:53:11,190 --> 00:53:13,440 AUDIENCE: Does that funding come to MIT the institute, 1035 00:53:13,440 --> 00:53:15,113 or Lincoln Lab as part of MIT? 1036 00:53:15,113 --> 00:53:16,530 WILLIAM BONVILLIAN: So Lincoln Lab 1037 00:53:16,530 --> 00:53:20,280 is a separate entity from MIT and, in fact, 1038 00:53:20,280 --> 00:53:22,140 undertakes a lot of Defense work. 1039 00:53:22,140 --> 00:53:26,940 But it is defense, not offense, is kind of a general rule 1040 00:53:26,940 --> 00:53:29,690 that they apply. 1041 00:53:29,690 --> 00:53:31,680 AUDIENCE: So that 18% doesn't go to just MIT. 1042 00:53:31,680 --> 00:53:34,055 WILLIAM BONVILLIAN: I'm not counting Lincoln Lab in that. 1043 00:53:36,358 --> 00:53:38,400 AUDIENCE: So my thought on that is basically just 1044 00:53:38,400 --> 00:53:41,880 that, you're taking this money, but it's not necessarily 1045 00:53:41,880 --> 00:53:44,840 trying to make us a better war machine. 1046 00:53:47,790 --> 00:53:49,630 WILLIAM BONVILLIAN: So Max, in our reading 1047 00:53:49,630 --> 00:53:52,510 of Glenn Fong, which I think comes next, 1048 00:53:52,510 --> 00:53:55,640 we're actually going to derive after this exact point. 1049 00:53:55,640 --> 00:53:59,590 So we can really lay out some of those nuances 1050 00:53:59,590 --> 00:54:02,665 when we look at his piece. 1051 00:54:02,665 --> 00:54:04,040 So Matthew, do you have a closing 1052 00:54:04,040 --> 00:54:07,835 thought for us on Vernon Ruttan? 1053 00:54:10,540 --> 00:54:13,430 MATTHEW: I think I thought very similarly to other people 1054 00:54:13,430 --> 00:54:17,500 here, that it seems more than war itself. 1055 00:54:17,500 --> 00:54:19,840 A sense of urgency and threat, whether it's 1056 00:54:19,840 --> 00:54:26,077 military or health-related, that's really what drives us. 1057 00:54:26,077 --> 00:54:27,160 WILLIAM BONVILLIAN: Right. 1058 00:54:27,160 --> 00:54:31,300 And that'll drive a societal, scaled-up effort, 1059 00:54:31,300 --> 00:54:33,650 those kinds of concerns. 1060 00:54:33,650 --> 00:54:35,602 I think you're absolutely right. 1061 00:54:35,602 --> 00:54:37,310 AUDIENCE: My main concern with this piece 1062 00:54:37,310 --> 00:54:40,108 was like, you're overspending to move very quickly, which 1063 00:54:40,108 --> 00:54:40,900 isn't really great. 1064 00:54:40,900 --> 00:54:43,347 But also right after-- like once your initiative 1065 00:54:43,347 --> 00:54:44,930 is done, that's like saying, yeah, I'm 1066 00:54:44,930 --> 00:54:46,940 going to diet up until Friday, like right 1067 00:54:46,940 --> 00:54:48,470 after you kind of go all out. 1068 00:54:48,470 --> 00:54:51,050 So I wonder if these things, if you move the science forward 1069 00:54:51,050 --> 00:54:54,310 very quickly, and then people just kind of drop it after. 1070 00:54:54,310 --> 00:54:56,327 So there's this kind of lost cause, 1071 00:54:56,327 --> 00:54:57,410 and they don't advance it. 1072 00:54:57,410 --> 00:54:58,850 Because also, like for most technologies, 1073 00:54:58,850 --> 00:55:00,620 like we can't do certain technologies 1074 00:55:00,620 --> 00:55:02,660 that we would have been able to do 50 years ago, 1075 00:55:02,660 --> 00:55:04,820 because the experts in that kind of thinking 1076 00:55:04,820 --> 00:55:06,320 are not here anymore. 1077 00:55:11,180 --> 00:55:15,340 AUDIENCE: I had a quick operations question for Bill. 1078 00:55:15,340 --> 00:55:23,440 When it comes to increasing R&D funding for agencies like DOD, 1079 00:55:23,440 --> 00:55:26,590 is it the Congresspeople and Senators acting sort of 1080 00:55:26,590 --> 00:55:28,840 in an executive capacity for their districts, 1081 00:55:28,840 --> 00:55:30,700 or is there pressure from the district 1082 00:55:30,700 --> 00:55:35,470 to sort of increase the policymaking for that, 1083 00:55:35,470 --> 00:55:37,160 in terms of national defense? 1084 00:55:37,160 --> 00:55:42,070 So I guess I'm asking, are legislators acting autonomously 1085 00:55:42,070 --> 00:55:43,690 in defense of the country, or is there 1086 00:55:43,690 --> 00:55:46,210 pressure coming from their districts, as well? 1087 00:55:48,510 --> 00:55:50,260 WILLIAM BONVILLIAN: So members of Congress 1088 00:55:50,260 --> 00:55:55,140 tend to be much more concerned about defense spending that's 1089 00:55:55,140 --> 00:55:58,620 part of big acquisition programs. 1090 00:55:58,620 --> 00:56:03,210 Who's going to get the next award for the next Air Force 1091 00:56:03,210 --> 00:56:04,950 aircraft? 1092 00:56:04,950 --> 00:56:07,410 That's significant scale. 1093 00:56:07,410 --> 00:56:11,380 R&D spending tends to be at a much more modest scale. 1094 00:56:11,380 --> 00:56:14,560 And Congress itself has eliminated the appropriations 1095 00:56:14,560 --> 00:56:15,700 earmarking system. 1096 00:56:15,700 --> 00:56:17,680 So members can no longer go into bills 1097 00:56:17,680 --> 00:56:21,385 and stick money in for projects in their district. 1098 00:56:24,190 --> 00:56:26,690 That system has really been significantly-- 1099 00:56:26,690 --> 00:56:28,190 I wouldn't say it's been eliminated, 1100 00:56:28,190 --> 00:56:29,960 but it's been significantly reduced. 1101 00:56:29,960 --> 00:56:33,670 So the Congress itself, to some extent, has reformed itself. 1102 00:56:33,670 --> 00:56:36,130 Now, the problem for that is that it gives members 1103 00:56:36,130 --> 00:56:39,852 much less at the stake in federal expenditures. 1104 00:56:39,852 --> 00:56:42,310 If they can't affect what's going on in their own district, 1105 00:56:42,310 --> 00:56:45,820 why should they care what federal appropriations levels 1106 00:56:45,820 --> 00:56:46,630 are? 1107 00:56:46,630 --> 00:56:49,910 So it's a two-edged sword here. 1108 00:56:49,910 --> 00:56:52,060 But by and large, members of Congress 1109 00:56:52,060 --> 00:56:58,100 have stayed out of R&D. They don't really touch DARPA. 1110 00:56:58,100 --> 00:57:00,050 They certainly don't touch NSF. 1111 00:57:00,050 --> 00:57:03,140 They don't touch NIH. 1112 00:57:03,140 --> 00:57:04,850 And part of this is that the amount 1113 00:57:04,850 --> 00:57:08,530 of funding awards for a research project are relatively modest 1114 00:57:08,530 --> 00:57:10,940 and really don't affect anything at scale. 1115 00:57:10,940 --> 00:57:13,730 What they worry about are these larger acquisition projects. 1116 00:57:13,730 --> 00:57:16,195 AUDIENCE: Was that also the case for the [INAUDIBLE] 1117 00:57:16,195 --> 00:57:20,123 observation that Ruttan undertook? 1118 00:57:20,123 --> 00:57:22,040 WILLIAM BONVILLIAN: I'm not sure I follow you. 1119 00:57:22,040 --> 00:57:27,890 AUDIENCE: Was it the pre-earmark era? 1120 00:57:27,890 --> 00:57:29,907 Was it present [INAUDIBLE] observation? 1121 00:57:29,907 --> 00:57:30,990 WILLIAM BONVILLIAN: Right. 1122 00:57:30,990 --> 00:57:35,000 The earmark era is only in it in the last four or five years. 1123 00:57:35,000 --> 00:57:37,920 AUDIENCE: So then Ruttan was operating under that system. 1124 00:57:37,920 --> 00:57:39,670 WILLIAM BONVILLIAN: Yeah, but again, there 1125 00:57:39,670 --> 00:57:43,760 wasn't very much earmarking of R&D funding, which 1126 00:57:43,760 --> 00:57:44,887 is really what-- 1127 00:57:44,887 --> 00:57:46,470 he's focused on the innovation system. 1128 00:57:50,810 --> 00:57:56,450 OK, so Glenn Fong-- 1129 00:57:56,450 --> 00:58:01,380 and he starts his piece with a quote 1130 00:58:01,380 --> 00:58:03,240 from a former White House chief of staff, 1131 00:58:03,240 --> 00:58:10,250 John Sununu of New Hampshire, who states, "We don't do 1132 00:58:10,250 --> 00:58:13,620 industrial policy," in the US. 1133 00:58:13,620 --> 00:58:20,020 And Glenn takes that line on and essentially proves otherwise, 1134 00:58:20,020 --> 00:58:23,550 that we actually are operating, at least through the defense 1135 00:58:23,550 --> 00:58:26,490 sector, with what can only be viewed as a pretty 1136 00:58:26,490 --> 00:58:29,200 significant industrial policy. 1137 00:58:29,200 --> 00:58:34,770 So how does case studies of various agencies. 1138 00:58:34,770 --> 00:58:36,180 It's not all defense. 1139 00:58:36,180 --> 00:58:40,050 He also looks at Commerce and NIST. 1140 00:58:40,050 --> 00:58:42,882 But he concludes that the significance 1141 00:58:42,882 --> 00:58:45,090 of the governmental role, particularly on the defense 1142 00:58:45,090 --> 00:58:49,140 side, is really quite strong. 1143 00:58:49,140 --> 00:58:53,600 And that because of the volume of the spending, in particular, 1144 00:58:53,600 --> 00:58:58,930 that's particularly powerful on the defense side. 1145 00:58:58,930 --> 00:59:04,520 And he argues that there are about four models to drive it. 1146 00:59:04,520 --> 00:59:06,780 The question, Max, you were asking about, 1147 00:59:06,780 --> 00:59:09,570 there's about four models by which 1148 00:59:09,570 --> 00:59:12,600 DOD undertakes its spending that happen 1149 00:59:12,600 --> 00:59:17,230 to have spillover effects into the civilian sector. 1150 00:59:17,230 --> 00:59:21,300 So one model is what he calls the byproduct model. 1151 00:59:21,300 --> 00:59:24,900 Military R&D will have unintended spillovers 1152 00:59:24,900 --> 00:59:26,830 into the commercial sector. 1153 00:59:26,830 --> 00:59:34,140 And he cites ARPA-NET as an example of this. 1154 00:59:34,140 --> 00:59:37,100 In other words, when DOD is setting up 1155 00:59:37,100 --> 00:59:42,370 the internet, the ARPA-NET, for its own internal purposes, 1156 00:59:42,370 --> 00:59:45,230 it's a defense communication system, and a communication 1157 00:59:45,230 --> 00:59:49,370 system between the early computer science departments 1158 00:59:49,370 --> 00:59:51,853 that DARPA has been supporting. 1159 00:59:51,853 --> 00:59:54,020 It's a way for them to communicate and transfer data 1160 00:59:54,020 --> 00:59:55,310 amongst themselves. 1161 00:59:55,310 --> 00:59:57,768 They're not envisioning that this 1162 00:59:57,768 --> 00:59:59,810 is going to be the standard form of communication 1163 00:59:59,810 --> 01:00:01,900 of the 21st century. 1164 01:00:01,900 --> 01:00:05,230 They were thinking about a much more immediate problem. 1165 01:00:05,230 --> 01:00:07,780 But the byproduct is that we create 1166 01:00:07,780 --> 01:00:11,290 this massive economic sector. 1167 01:00:11,290 --> 01:00:13,630 Then there's an intentional spinoff model. 1168 01:00:13,630 --> 01:00:18,600 So commercial spinoffs get expressly 1169 01:00:18,600 --> 01:00:23,210 contemplated during the program planning around an R&D 1170 01:00:23,210 --> 01:00:25,470 initiative. 1171 01:00:25,470 --> 01:00:32,670 And [? E-side ?] strategic computing and VHSIC as examples 1172 01:00:32,670 --> 01:00:38,150 where DARPA know that what it was going to create 1173 01:00:38,150 --> 01:00:40,610 in the computing sector was going to benefit all parts 1174 01:00:40,610 --> 01:00:43,190 of the computing sector, not simply DOD. 1175 01:00:43,190 --> 01:00:47,110 But the gains were significant enough for DOD 1176 01:00:47,110 --> 01:00:50,380 that it was really important to pursue this. 1177 01:00:50,380 --> 01:00:53,260 And in fact, DARPA and the IT revolution 1178 01:00:53,260 --> 01:00:57,980 in general consciously worked on standing up 1179 01:00:57,980 --> 01:01:02,120 a lot of these technologies in the civilian sector. 1180 01:01:02,120 --> 01:01:03,080 Why is that? 1181 01:01:03,080 --> 01:01:07,210 Because the Defense Department is often 1182 01:01:07,210 --> 01:01:11,500 quite good at standing up the early prototypes of a pretty 1183 01:01:11,500 --> 01:01:14,170 radical set of technologies. 1184 01:01:14,170 --> 01:01:16,960 But they don't have the follow-on capital 1185 01:01:16,960 --> 01:01:20,470 that the civilian sector can muster, a big financing 1186 01:01:20,470 --> 01:01:22,910 follow-on capability. 1187 01:01:22,910 --> 01:01:25,648 So DARPA consciously understood this, 1188 01:01:25,648 --> 01:01:27,440 realized there was going to have to be huge 1189 01:01:27,440 --> 01:01:29,740 incremental advances in the technologies 1190 01:01:29,740 --> 01:01:31,280 it was standing up. 1191 01:01:31,280 --> 01:01:35,420 It would help create the model, make 1192 01:01:35,420 --> 01:01:38,000 it available in the civilian sector, on the assumption 1193 01:01:38,000 --> 01:01:42,290 that a rising IT sector and financial support system 1194 01:01:42,290 --> 01:01:45,230 would come in and scale this up. 1195 01:01:45,230 --> 01:01:47,060 It would radically drive the price down, 1196 01:01:47,060 --> 01:01:51,020 enabling DOD to buy the technologies back 1197 01:01:51,020 --> 01:01:54,380 at a fraction of the cost and with much greater capability 1198 01:01:54,380 --> 01:01:57,110 than their own system would be able to do this. 1199 01:01:57,110 --> 01:02:00,890 So DARPA's decision to stand up a lot of the IT revolution 1200 01:02:00,890 --> 01:02:03,740 around computing on the civilian side 1201 01:02:03,740 --> 01:02:09,070 comes from a pretty conscious effort 1202 01:02:09,070 --> 01:02:11,800 to understand the dynamics of what was going to be. 1203 01:02:11,800 --> 01:02:13,870 And they all understood it to be a very large 1204 01:02:13,870 --> 01:02:15,610 potential economic sector. 1205 01:02:15,610 --> 01:02:18,430 And how DOD could be the initiator and then 1206 01:02:18,430 --> 01:02:22,420 leverage off what were going to be much higher investments 1207 01:02:22,420 --> 01:02:23,350 on the civilian side. 1208 01:02:23,350 --> 01:02:26,260 So for example, for a long period of time, 1209 01:02:26,260 --> 01:02:29,180 DOD would be the initial market. 1210 01:02:29,180 --> 01:02:32,170 So when we talked about how Kilby and Noyce developed 1211 01:02:32,170 --> 01:02:34,870 the integrated circuit, the core breakthrough 1212 01:02:34,870 --> 01:02:41,410 technology in semiconductors, and really in computing, 1213 01:02:41,410 --> 01:02:43,390 the only customer for the first four years 1214 01:02:43,390 --> 01:02:47,730 were the Defense Department and NASA. 1215 01:02:47,730 --> 01:02:50,820 So the Defense Department carried all those advances 1216 01:02:50,820 --> 01:02:53,760 through the first four years of new generations of advances 1217 01:02:53,760 --> 01:02:54,780 for integrated circuits. 1218 01:02:54,780 --> 01:02:58,830 It wasn't until four years later that a civilian sector 1219 01:02:58,830 --> 01:02:59,970 started to evolve. 1220 01:02:59,970 --> 01:03:03,420 So DOD can play this initiator model. 1221 01:03:03,420 --> 01:03:06,360 And what Glenn Fong is driving at here is, 1222 01:03:06,360 --> 01:03:10,090 that's an intentional spinoff model that works well for DOD. 1223 01:03:12,690 --> 01:03:17,340 Also, DOD has an explicit dual use model. 1224 01:03:17,340 --> 01:03:20,820 So a defense project could have the explicit goal 1225 01:03:20,820 --> 01:03:22,650 of developing a military technology 1226 01:03:22,650 --> 01:03:25,500 and a civilian technology in parallel. 1227 01:03:25,500 --> 01:03:33,080 And advances in lithography in semiconductor etching 1228 01:03:33,080 --> 01:03:34,560 are a pretty good example of that. 1229 01:03:34,560 --> 01:03:37,050 High performance computing, which Al Gore 1230 01:03:37,050 --> 01:03:40,560 helped to originate and pass the original legislation before, 1231 01:03:40,560 --> 01:03:42,810 these were going to have benefits on the military side 1232 01:03:42,810 --> 01:03:46,740 big-time, but obviously corresponding big benefits 1233 01:03:46,740 --> 01:03:47,790 on the civilian side. 1234 01:03:47,790 --> 01:03:49,980 And then kind of the fourth model, Glenn 1235 01:03:49,980 --> 01:03:56,190 points out, for how DOD thinks about its role in the economy 1236 01:03:56,190 --> 01:03:58,200 and intervenes in the economy and has, 1237 01:03:58,200 --> 01:04:01,770 in effect, an industrial policy, is what he calls 1238 01:04:01,770 --> 01:04:03,570 the industrial base model. 1239 01:04:03,570 --> 01:04:05,790 So sometimes, DOD is going to decide 1240 01:04:05,790 --> 01:04:10,090 that it must have an industrial base in a particular sector, 1241 01:04:10,090 --> 01:04:13,260 and will consciously support the development 1242 01:04:13,260 --> 01:04:16,320 of an industrial base in the civilian sector. 1243 01:04:16,320 --> 01:04:20,340 The best example of this I know of 1244 01:04:20,340 --> 01:04:23,220 is that both the Navy and the Army, 1245 01:04:23,220 --> 01:04:28,010 in the early days of aviation in the 1920s and '30s, 1246 01:04:28,010 --> 01:04:30,440 are consciously attempting to create 1247 01:04:30,440 --> 01:04:34,097 a very strong civilian industrial base in aviation. 1248 01:04:34,097 --> 01:04:35,930 Because they know how powerful and important 1249 01:04:35,930 --> 01:04:37,280 that's going to be. 1250 01:04:37,280 --> 01:04:39,740 So Admiral Moffett, who was leading the Navy's 1251 01:04:39,740 --> 01:04:44,000 early aviation program, carefully makes 1252 01:04:44,000 --> 01:04:46,640 sure, in the appropriations process, 1253 01:04:46,640 --> 01:04:49,310 the congressional appropriations process, 1254 01:04:49,310 --> 01:04:55,370 that there are a multitude of projects for engine makers, 1255 01:04:55,370 --> 01:04:58,100 for airframe makers, for different types of aircraft. 1256 01:04:58,100 --> 01:05:00,620 So that he's going to start to stand up 1257 01:05:00,620 --> 01:05:02,340 a whole industrial base and aviation. 1258 01:05:02,340 --> 01:05:05,360 It's done very consciously. 1259 01:05:05,360 --> 01:05:07,695 I think that's the best example. 1260 01:05:07,695 --> 01:05:09,320 But there are other examples like that, 1261 01:05:09,320 --> 01:05:14,920 too including in the IT side, such as Semitech. 1262 01:05:14,920 --> 01:05:18,940 When Japan came very close to capturing leadership 1263 01:05:18,940 --> 01:05:22,060 in the semiconductor sector-- and we talked about this 1264 01:05:22,060 --> 01:05:24,830 in the manufacturing class-- 1265 01:05:24,830 --> 01:05:26,660 DOD intervenes. 1266 01:05:26,660 --> 01:05:30,590 So under President Reagan, DARPA jumps in here 1267 01:05:30,590 --> 01:05:35,510 and cost-shares the development of new advanced manufacturing 1268 01:05:35,510 --> 01:05:39,910 approaches in semiconductors, so that the US 1269 01:05:39,910 --> 01:05:41,980 could get back into that game. 1270 01:05:41,980 --> 01:05:45,070 Japan had figured out better processes, better production 1271 01:05:45,070 --> 01:05:50,810 systems, more efficiency, higher quality in semiconductor 1272 01:05:50,810 --> 01:05:51,830 fabrication. 1273 01:05:51,830 --> 01:05:53,600 The US had missed these. 1274 01:05:53,600 --> 01:05:55,850 This was a conscious attempt to keep up, 1275 01:05:55,850 --> 01:05:57,530 because the Defense Department felt 1276 01:05:57,530 --> 01:06:01,590 it had to have an industrial base in semiconductors. 1277 01:06:01,590 --> 01:06:06,920 So these are four ways by which DOD is willing to intervene. 1278 01:06:06,920 --> 01:06:09,140 It will not intervene just for straight economic 1279 01:06:09,140 --> 01:06:10,250 competitiveness reasons. 1280 01:06:13,160 --> 01:06:15,563 So getting back to our conversation earlier, Max, 1281 01:06:15,563 --> 01:06:17,480 it's not going to do something just because it 1282 01:06:17,480 --> 01:06:19,590 will help US competitiveness. 1283 01:06:19,590 --> 01:06:21,980 It will only do it if it can find 1284 01:06:21,980 --> 01:06:26,100 one of these very close military needs associated with it. 1285 01:06:26,100 --> 01:06:28,850 And these are the four models they use. 1286 01:06:28,850 --> 01:06:31,103 Who's got the Q&A on this, Chris? 1287 01:06:31,103 --> 01:06:32,020 I think we're Through. 1288 01:06:32,020 --> 01:06:34,457 Yeah, we're through this. 1289 01:06:34,457 --> 01:06:36,040 Why don't you lead us off in some Q&A. 1290 01:06:36,040 --> 01:06:38,215 And Max has got a question, too. 1291 01:06:38,215 --> 01:06:38,840 AUDIENCE: Sure. 1292 01:06:38,840 --> 01:06:43,300 So as we just went through pretty briefly, 1293 01:06:43,300 --> 01:06:45,280 he mentions a lot of different models 1294 01:06:45,280 --> 01:06:47,830 and different agency projects that 1295 01:06:47,830 --> 01:06:53,170 have been kind of case studies of opportunities 1296 01:06:53,170 --> 01:06:57,640 that the DOD largely has used to advance 1297 01:06:57,640 --> 01:07:01,960 technological innovation, somewhat indirectly. 1298 01:07:01,960 --> 01:07:04,960 So maybe we could start off by discussing, 1299 01:07:04,960 --> 01:07:07,870 which model do you guys think is most effective? 1300 01:07:07,870 --> 01:07:10,300 Do you think it changes when you consider 1301 01:07:10,300 --> 01:07:13,690 different industries or different focuses? 1302 01:07:13,690 --> 01:07:18,509 And how applicable is this kind of structure to present day? 1303 01:07:26,325 --> 01:07:28,950 AUDIENCE: I think what's really cool about all these is they're 1304 01:07:28,950 --> 01:07:32,940 separated by intent, really. 1305 01:07:32,940 --> 01:07:38,707 So if you're intending to have a sort of dual use-- 1306 01:07:38,707 --> 01:07:41,290 it's probably easier to see the bottom two than the first one. 1307 01:07:41,290 --> 01:07:44,580 But the dual use and the intentional spinoff 1308 01:07:44,580 --> 01:07:48,450 are pretty strong arguments for how DARPA projects could 1309 01:07:48,450 --> 01:07:51,060 be effective and useful and why you should advocate for them. 1310 01:07:51,060 --> 01:07:56,460 It'd be pretty hard to do the byproduct model 1311 01:07:56,460 --> 01:07:59,542 with that sort of intent for spinoff, 1312 01:07:59,542 --> 01:08:01,500 just because you have absolutely no idea of how 1313 01:08:01,500 --> 01:08:02,700 that's going to turn out. 1314 01:08:02,700 --> 01:08:05,490 But because they're separated by intent, 1315 01:08:05,490 --> 01:08:08,850 I think it's pretty fair to say that, depending 1316 01:08:08,850 --> 01:08:10,950 on what sort of project you're looking at, 1317 01:08:10,950 --> 01:08:13,840 you're going to see which model is going to be better. 1318 01:08:13,840 --> 01:08:17,277 And it's nice that you can do that from the get-go. 1319 01:08:17,277 --> 01:08:19,069 When you start the project, you can kind of 1320 01:08:19,069 --> 01:08:20,506 see where that's going. 1321 01:08:24,819 --> 01:08:28,450 AUDIENCE: So just personally, it seems like some of these 1322 01:08:28,450 --> 01:08:31,779 might be hard to kind of create a project around, oh, I'm 1323 01:08:31,779 --> 01:08:33,939 going to have unintended spillovers 1324 01:08:33,939 --> 01:08:36,010 into the commercial sector. 1325 01:08:36,010 --> 01:08:38,950 In some sense to me, it seems like a bit 1326 01:08:38,950 --> 01:08:43,149 like post-classification of what has been done. 1327 01:08:43,149 --> 01:08:47,290 So thinking about the DOD as they're 1328 01:08:47,290 --> 01:08:49,930 trying to fund projects, what do you think 1329 01:08:49,930 --> 01:08:52,090 are their main priorities, in terms 1330 01:08:52,090 --> 01:08:56,979 of potential commercialization and potential kind of benefits 1331 01:08:56,979 --> 01:09:00,550 that way, and also benefiting their military efforts? 1332 01:09:00,550 --> 01:09:02,020 What do you think is that balance, 1333 01:09:02,020 --> 01:09:04,930 and what kind of characteristics would they 1334 01:09:04,930 --> 01:09:08,890 be looking for in, maybe, a funding proposal? 1335 01:09:08,890 --> 01:09:11,598 AUDIENCE: Well, I'd say one characteristic 1336 01:09:11,598 --> 01:09:13,390 that they look for and definitely emphasize 1337 01:09:13,390 --> 01:09:15,910 would be superiority over other countries 1338 01:09:15,910 --> 01:09:17,590 who are working in similar fields. 1339 01:09:17,590 --> 01:09:20,260 So with the semiconductor thing, the moment they saw, 1340 01:09:20,260 --> 01:09:22,479 hey, Japan's doing this, they're like, oh no. 1341 01:09:22,479 --> 01:09:25,520 OK, now we need to get on this. 1342 01:09:25,520 --> 01:09:27,090 What was the direct implication? 1343 01:09:27,090 --> 01:09:28,582 That was my question, by the way. 1344 01:09:28,582 --> 01:09:30,040 WILLIAM BONVILLIAN: Semiconductors? 1345 01:09:30,040 --> 01:09:30,250 AUDIENCE: Yeah. 1346 01:09:30,250 --> 01:09:32,625 WILLIAM BONVILLIAN: [INAUDIBLE] for the computing system. 1347 01:09:32,625 --> 01:09:33,189 AUDIENCE: OK. 1348 01:09:33,189 --> 01:09:36,250 Because you said the DOD does not 1349 01:09:36,250 --> 01:09:38,830 support different industries unless it 1350 01:09:38,830 --> 01:09:43,920 has a direct national security application. 1351 01:09:43,920 --> 01:09:46,140 So I guess I'm just trying to figure out 1352 01:09:46,140 --> 01:09:50,010 how we could implement these ideas today, 1353 01:09:50,010 --> 01:09:55,062 so that we could, I guess, boost our current innovation system. 1354 01:09:55,062 --> 01:09:57,270 AUDIENCE: I don't know if it would be military-based, 1355 01:09:57,270 --> 01:09:58,840 but you just go with a focus point, 1356 01:09:58,840 --> 01:10:01,080 have that kind of military ideology of like, 1357 01:10:01,080 --> 01:10:03,030 we need to get here by X amount of time. 1358 01:10:03,030 --> 01:10:04,710 And let's put these efforts and try 1359 01:10:04,710 --> 01:10:07,545 to think more as a system, rather 1360 01:10:07,545 --> 01:10:09,240 than different departments. 1361 01:10:09,240 --> 01:10:11,400 But you would put initiatives. 1362 01:10:11,400 --> 01:10:14,120 Like in private capital that's been happening recently, 1363 01:10:14,120 --> 01:10:15,870 like [INAUDIBLE] made a private initiative 1364 01:10:15,870 --> 01:10:19,050 to cancer and certain diseases. 1365 01:10:19,050 --> 01:10:20,670 But if you have a national effort-- 1366 01:10:20,670 --> 01:10:21,237 I don't know. 1367 01:10:21,237 --> 01:10:23,570 I wasn't alive during this, but I think during the '70s, 1368 01:10:23,570 --> 01:10:25,020 during the Cold War, there was a huge initiative 1369 01:10:25,020 --> 01:10:26,400 for science and rockets. 1370 01:10:26,400 --> 01:10:27,570 I don't know. 1371 01:10:27,570 --> 01:10:28,800 You probably know. 1372 01:10:28,800 --> 01:10:30,420 I haven't seen a [INAUDIBLE] this. 1373 01:10:30,420 --> 01:10:32,040 WILLIAM BONVILLIAN: We'll get into that in a later reading 1374 01:10:32,040 --> 01:10:32,540 today. 1375 01:10:32,540 --> 01:10:34,165 AUDIENCE: But I think definitely having 1376 01:10:34,165 --> 01:10:36,748 a strong national interest, but not just financial incentives. 1377 01:10:36,748 --> 01:10:38,332 Because from a management perspective, 1378 01:10:38,332 --> 01:10:40,260 people have different ideas of what's good 1379 01:10:40,260 --> 01:10:41,610 and what they want out of life. 1380 01:10:41,610 --> 01:10:44,310 So I would do financial incentives, social incentives, 1381 01:10:44,310 --> 01:10:47,250 in terms of, you solve this problem, you're a superstar. 1382 01:10:47,250 --> 01:10:51,030 Kind of like an Einstein, it'll get you on TV. 1383 01:10:51,030 --> 01:10:52,990 And then also educational, in terms of like, 1384 01:10:52,990 --> 01:10:55,220 oh, these are our star students, from five years old, 1385 01:10:55,220 --> 01:10:59,443 10 years old, 15 years old, so they're part of the community. 1386 01:10:59,443 --> 01:11:00,860 And that's probably how I'd do it. 1387 01:11:00,860 --> 01:11:03,000 And getting rid of egos, like finding a way 1388 01:11:03,000 --> 01:11:06,660 to do that in a system, that's how I would think about it. 1389 01:11:06,660 --> 01:11:11,310 But I'm interested in what policy people think, 1390 01:11:11,310 --> 01:11:13,230 people who focus on policy. 1391 01:11:13,230 --> 01:11:14,670 I don't know policy. 1392 01:11:18,750 --> 01:11:22,360 Have there been policies in the past that do something similar? 1393 01:11:22,360 --> 01:11:23,860 AUDIENCE: Well, apparently, right? 1394 01:11:23,860 --> 01:11:25,860 AUDIENCE: I mean outside of this. 1395 01:11:31,360 --> 01:11:32,920 WILLIAM BONVILLIAN: Martin, you're 1396 01:11:32,920 --> 01:11:36,190 laying out a whole new set of initiative drivers here. 1397 01:11:36,190 --> 01:11:38,290 And it's an interesting list. 1398 01:11:38,290 --> 01:11:42,220 And in fact, in the Sputnik era, which 1399 01:11:42,220 --> 01:11:44,350 we'll talk about a little bit, we 1400 01:11:44,350 --> 01:11:46,700 do see a tremendous focus on education, 1401 01:11:46,700 --> 01:11:50,530 for example, and training, and the importance 1402 01:11:50,530 --> 01:11:52,330 of being a scientist. 1403 01:11:52,330 --> 01:11:55,180 Those all come to the forefront in American society 1404 01:11:55,180 --> 01:11:57,344 for a reasonable period of time. 1405 01:12:02,162 --> 01:12:04,162 AUDIENCE: And coming back to what I was actually 1406 01:12:04,162 --> 01:12:08,350 saying, because it's less obvious, or at least 1407 01:12:08,350 --> 01:12:11,430 it's not as advertised to the American people, 1408 01:12:11,430 --> 01:12:13,480 that, in a lot of aspects, we're not really 1409 01:12:13,480 --> 01:12:20,110 doing all that well, like education or in manufacturing. 1410 01:12:20,110 --> 01:12:21,940 Because it's not advertised as much, 1411 01:12:21,940 --> 01:12:24,820 perhaps that's why maybe we spend 1412 01:12:24,820 --> 01:12:27,590 some time resting on our laurels from the '70s or whatever. 1413 01:12:27,590 --> 01:12:33,018 And maybe that's why we're progressing less quickly 1414 01:12:33,018 --> 01:12:33,685 in other places. 1415 01:12:37,600 --> 01:12:40,450 AUDIENCE: To bring in the question you asked earlier, 1416 01:12:40,450 --> 01:12:45,200 Chris, I really like the diagram, I guess, 1417 01:12:45,200 --> 01:12:48,580 he poses on page 161. 1418 01:12:48,580 --> 01:12:58,400 I guess I can zoom into it on my computer, where he essentially 1419 01:12:58,400 --> 01:13:02,290 shows where each of these fit on the models. 1420 01:13:02,290 --> 01:13:06,530 And I like this trend line was in between intentional spinoff 1421 01:13:06,530 --> 01:13:08,600 and explicit dual use. 1422 01:13:08,600 --> 01:13:10,610 And I appreciate that in particular, 1423 01:13:10,610 --> 01:13:12,440 because I think it really highlights-- 1424 01:13:12,440 --> 01:13:14,990 and even within the context of him choosing those as case 1425 01:13:14,990 --> 01:13:15,740 studies-- 1426 01:13:15,740 --> 01:13:17,660 a point that he had made towards the beginning 1427 01:13:17,660 --> 01:13:20,158 on structural attributes of the United States. 1428 01:13:20,158 --> 01:13:21,950 And he argues something along the lines of, 1429 01:13:21,950 --> 01:13:24,470 structural attributes determine industrial policymaking 1430 01:13:24,470 --> 01:13:25,520 capabilities. 1431 01:13:25,520 --> 01:13:28,430 And the US has deficiencies in industrial policymaking, 1432 01:13:28,430 --> 01:13:30,620 because we don't care, or rather because we 1433 01:13:30,620 --> 01:13:33,750 don't put an emphasis on creating 1434 01:13:33,750 --> 01:13:35,150 that policy explicitly. 1435 01:13:35,150 --> 01:13:37,040 And I guess I question how much of that 1436 01:13:37,040 --> 01:13:41,680 is, I guess, a cultural barrier almost, that we have, 1437 01:13:41,680 --> 01:13:45,020 or a perception barrier, more so than a policymaking barrier. 1438 01:13:45,020 --> 01:13:49,820 Because if policymakers don't conceive of themselves 1439 01:13:49,820 --> 01:13:52,860 as change agents, maybe-- 1440 01:13:52,860 --> 01:13:56,350 was there a reading in this concept for this week that-- 1441 01:13:56,350 --> 01:13:59,725 was it yours, Bill, the fifth reading? 1442 01:13:59,725 --> 01:14:01,100 Yeah, that talked about changing, 1443 01:14:01,100 --> 01:14:02,933 because if policymakers don't see themselves 1444 01:14:02,933 --> 01:14:05,540 as change agents within the economic context, 1445 01:14:05,540 --> 01:14:08,090 and they feel like that should be left up to private markets, 1446 01:14:08,090 --> 01:14:10,970 then they might not feel like it is their position or even 1447 01:14:10,970 --> 01:14:12,890 something in their area of expertise 1448 01:14:12,890 --> 01:14:14,740 to promote industrial policymaking 1449 01:14:14,740 --> 01:14:16,610 as a key to economic growth. 1450 01:14:16,610 --> 01:14:20,420 But if, I guess, someone were to articulate-- 1451 01:14:20,420 --> 01:14:21,890 or maybe, Bill, that was you. 1452 01:14:21,890 --> 01:14:23,610 Maybe that was your position in the Senate, right? 1453 01:14:23,610 --> 01:14:25,652 If there was someone who was clearly articulating 1454 01:14:25,652 --> 01:14:27,740 the link between industrial policymaking 1455 01:14:27,740 --> 01:14:33,840 and economic growth as of the utmost importance, then maybe 1456 01:14:33,840 --> 01:14:35,070 they would do it more often. 1457 01:14:35,070 --> 01:14:39,180 So I think that's where that diagram that he draws 1458 01:14:39,180 --> 01:14:41,640 is really important in establishing that trend 1459 01:14:41,640 --> 01:14:43,410 line between intentional M off modeling 1460 01:14:43,410 --> 01:14:45,000 and the explicit dual use model. 1461 01:14:45,000 --> 01:14:47,370 Because it is perhaps precisely trending 1462 01:14:47,370 --> 01:14:50,130 towards explicit dual use that you can convince 1463 01:14:50,130 --> 01:14:54,780 policymakers to invest in R&D, and not in basic research 1464 01:14:54,780 --> 01:14:58,780 and not explicitly at the hands of the market. 1465 01:14:58,780 --> 01:15:02,270 WILLIAM BONVILLIAN: Chris, do you want to react? 1466 01:15:02,270 --> 01:15:03,536 AUDIENCE: Yes. 1467 01:15:03,536 --> 01:15:05,530 AUDIENCE: That was a lot. 1468 01:15:07,708 --> 01:15:09,500 WILLIAM BONVILLIAN: No, go ahead, go ahead. 1469 01:15:09,500 --> 01:15:10,625 AUDIENCE: Oh, no, go ahead. 1470 01:15:10,625 --> 01:15:12,730 I'm still trying to gather my thoughts. 1471 01:15:12,730 --> 01:15:14,032 WILLIAM BONVILLIAN: Yeah, no. 1472 01:15:14,032 --> 01:15:16,490 I'll say just a couple words, then Rasheed and then, Chris. 1473 01:15:19,480 --> 01:15:22,540 Industrial policy is a negative term in the United States. 1474 01:15:22,540 --> 01:15:26,650 And what it's come to suggest is that the government is playing 1475 01:15:26,650 --> 01:15:29,320 a role, intervening in the marketplace 1476 01:15:29,320 --> 01:15:32,650 to pick, as the phrase goes, winners and losers-- 1477 01:15:32,650 --> 01:15:34,900 in other words, who's going to be the successful firms 1478 01:15:34,900 --> 01:15:37,030 and who's not. 1479 01:15:37,030 --> 01:15:40,570 And what Glenn is arguing is, like it or not, 1480 01:15:40,570 --> 01:15:45,160 as the military moves into these very applied areas in the IT 1481 01:15:45,160 --> 01:15:49,420 revolution, it is playing an industrial policy, 1482 01:15:49,420 --> 01:15:53,470 industrial organizational kind of role, like it or not. 1483 01:15:53,470 --> 01:15:56,650 And even though we deny we have industrial policy in the United 1484 01:15:56,650 --> 01:16:00,660 States, Glenn is arguing, look, as a practical matter, 1485 01:16:00,660 --> 01:16:02,150 the Defense Department definitely 1486 01:16:02,150 --> 01:16:04,470 has tendencies in this direction. 1487 01:16:04,470 --> 01:16:07,640 So this is a debate about pros and cons of industrial policy. 1488 01:16:07,640 --> 01:16:09,530 I think Glenn is arguing, you want 1489 01:16:09,530 --> 01:16:11,090 to see these technologies stood up, 1490 01:16:11,090 --> 01:16:13,382 you're going to have to think about how you're actually 1491 01:16:13,382 --> 01:16:16,190 organizing to implement them. 1492 01:16:16,190 --> 01:16:18,130 AUDIENCE: As a quick followup, do 1493 01:16:18,130 --> 01:16:20,710 you think that he would argue that calling it by its name 1494 01:16:20,710 --> 01:16:22,060 is important? 1495 01:16:22,060 --> 01:16:25,150 Rather than having these sort of disambiguations about research 1496 01:16:25,150 --> 01:16:26,890 and development funding, we really 1497 01:16:26,890 --> 01:16:28,690 talk about it in an economic sense 1498 01:16:28,690 --> 01:16:29,910 as industrial policymaking. 1499 01:16:29,910 --> 01:16:32,110 And if we call it like it is, then 1500 01:16:32,110 --> 01:16:35,020 perhaps we would sort of destigmatize market 1501 01:16:35,020 --> 01:16:37,335 interventions, at least in this context. 1502 01:16:37,335 --> 01:16:38,710 WILLIAM BONVILLIAN: You're right. 1503 01:16:38,710 --> 01:16:43,630 We invent a lot of phrases to not use that term. 1504 01:16:43,630 --> 01:16:46,780 For example, in the civilian research side, 1505 01:16:46,780 --> 01:16:49,510 when the Advanced Technology Program is being put together 1506 01:16:49,510 --> 01:16:53,110 that funds industry-applied research projects, 1507 01:16:53,110 --> 01:16:56,680 the argument is, this is not industrial policy. 1508 01:16:56,680 --> 01:16:59,440 We are funding pre-competitive research, 1509 01:16:59,440 --> 01:17:02,320 which is going to land and be accessible to a number 1510 01:17:02,320 --> 01:17:03,760 of firms. 1511 01:17:03,760 --> 01:17:06,490 So we're not particularly picking one firm as opposed 1512 01:17:06,490 --> 01:17:07,480 to another. 1513 01:17:07,480 --> 01:17:10,560 We're funding pre-competitive research that will benefit all. 1514 01:17:10,560 --> 01:17:13,060 And that's not a bad theory. 1515 01:17:13,060 --> 01:17:16,090 There are issues, as Charles Shultze taught us, 1516 01:17:16,090 --> 01:17:18,690 about governmental intervention and industrial policy. 1517 01:17:18,690 --> 01:17:21,970 This is not a simple landscape. 1518 01:17:21,970 --> 01:17:23,620 It's rife with problems. 1519 01:17:23,620 --> 01:17:26,050 We'll get to In-Q-Tel as soon as we take a break. 1520 01:17:26,050 --> 01:17:29,980 But that's the ultimate interventionist governmental 1521 01:17:29,980 --> 01:17:30,940 mechanism. 1522 01:17:30,940 --> 01:17:32,650 But Rashid, go ahead. 1523 01:17:32,650 --> 01:17:33,548 You had a point. 1524 01:17:33,548 --> 01:17:35,590 AUDIENCE: There are two things that are separate. 1525 01:17:35,590 --> 01:17:38,267 I think one, very quickly, is DARPA. 1526 01:17:38,267 --> 01:17:39,850 I think it was in one of the readings. 1527 01:17:39,850 --> 01:17:45,310 They do actually, at each stage of their project development, 1528 01:17:45,310 --> 01:17:48,040 they sort of kind of have you hash out just a white paper, 1529 01:17:48,040 --> 01:17:51,010 identifying what would be the potential commercial impacts 1530 01:17:51,010 --> 01:17:54,260 of this research if it were to go to market. 1531 01:17:54,260 --> 01:17:56,625 So they have sort of staged places 1532 01:17:56,625 --> 01:17:58,000 where they're thinking about, how 1533 01:17:58,000 --> 01:18:00,730 are we going to transition in toward 1534 01:18:00,730 --> 01:18:03,780 to this byproduct intentional spinoff 1535 01:18:03,780 --> 01:18:05,020 in an explicit dual use. 1536 01:18:05,020 --> 01:18:06,580 Because they realized like, yeah, 1537 01:18:06,580 --> 01:18:08,447 we're doing research, that's great for us. 1538 01:18:08,447 --> 01:18:10,780 But obviously, this is going to have benefits elsewhere. 1539 01:18:10,780 --> 01:18:12,880 But I think what's important is DARPA actually 1540 01:18:12,880 --> 01:18:14,600 has stages where they identify, and they 1541 01:18:14,600 --> 01:18:15,850 make you sort of write it out. 1542 01:18:15,850 --> 01:18:17,620 And it's not punitive or binding. 1543 01:18:17,620 --> 01:18:19,503 But they say that they're thinking about, 1544 01:18:19,503 --> 01:18:21,670 how are we going to actually transition this defense 1545 01:18:21,670 --> 01:18:24,330 research into commercial applications? 1546 01:18:24,330 --> 01:18:25,510 And that's really important. 1547 01:18:25,510 --> 01:18:28,630 Because they're kind of speeding through a lot of steps 1548 01:18:28,630 --> 01:18:33,490 here in the R&D space, by putting so much money in it, 1549 01:18:33,490 --> 01:18:37,300 doing these high risk, high reward opportunities. 1550 01:18:37,300 --> 01:18:39,100 But they're thinking actively about how 1551 01:18:39,100 --> 01:18:41,200 they're going to benefit the consumer 1552 01:18:41,200 --> 01:18:42,670 and commercial efforts. 1553 01:18:42,670 --> 01:18:45,520 And then two, I think policymakers 1554 01:18:45,520 --> 01:18:47,380 as change agents is pretty key. 1555 01:18:47,380 --> 01:18:50,230 And Martin and Steph kind of hit on it a little bit. 1556 01:18:50,230 --> 01:18:52,470 But I think it's just a different way of thinking. 1557 01:18:52,470 --> 01:18:54,220 And maybe it's just calling it like it is. 1558 01:18:54,220 --> 01:18:57,640 Maybe it's just saying, industrial policy or kind 1559 01:18:57,640 --> 01:19:01,120 of adopting these methods, without-- 1560 01:19:01,120 --> 01:19:03,760 so adopting the best of what we like about industrial policy, 1561 01:19:03,760 --> 01:19:05,885 which is this byproduct model and all these things, 1562 01:19:05,885 --> 01:19:08,020 without really getting into picking 1563 01:19:08,020 --> 01:19:12,230 winners and losers, sort of this In-Q-Tell kind of mechanism 1564 01:19:12,230 --> 01:19:12,730 here. 1565 01:19:12,730 --> 01:19:15,730 And I think it might be a little bit easier to decide what 1566 01:19:15,730 --> 01:19:17,770 we like about industrial policy if we just 1567 01:19:17,770 --> 01:19:19,420 call it industrial policy instead 1568 01:19:19,420 --> 01:19:21,400 of just avoiding market intervention as a term 1569 01:19:21,400 --> 01:19:22,210 entirely. 1570 01:19:22,210 --> 01:19:25,415 Like if you just decided, yes, it's a market intervention, 1571 01:19:25,415 --> 01:19:27,040 and yes, we're doing industrial policy, 1572 01:19:27,040 --> 01:19:29,272 but we want to do this kind of market intervention 1573 01:19:29,272 --> 01:19:30,730 and this kind of industrial policy, 1574 01:19:30,730 --> 01:19:33,560 instead of kind of masking it with ambiguous terms, 1575 01:19:33,560 --> 01:19:35,000 things might get a little easier. 1576 01:19:35,000 --> 01:19:38,290 And then third, I think the call for things 1577 01:19:38,290 --> 01:19:40,270 is a nice way to get around this. 1578 01:19:40,270 --> 01:19:42,680 So I think there's a lot of examples 1579 01:19:42,680 --> 01:19:45,495 about the government putting out calls and initiations. 1580 01:19:45,495 --> 01:19:46,870 And even DARPA kind of does this, 1581 01:19:46,870 --> 01:19:47,953 where they initiate calls. 1582 01:19:47,953 --> 01:19:50,218 They say, we'd like to do research 1583 01:19:50,218 --> 01:19:51,760 in this particular area, or we'd like 1584 01:19:51,760 --> 01:19:53,135 to solve this particular problem. 1585 01:19:56,385 --> 01:19:58,510 And it's not a way to pick these winners and losers 1586 01:19:58,510 --> 01:19:59,468 and decide who does it. 1587 01:19:59,468 --> 01:20:04,480 But like, the person who comes up with the best proposal 1588 01:20:04,480 --> 01:20:06,430 and can prove that they can meet these 1589 01:20:06,430 --> 01:20:08,290 staged deadlines will win in the end. 1590 01:20:08,290 --> 01:20:11,070 And it's a pretty tried and true method 1591 01:20:11,070 --> 01:20:12,880 you see in things like that. 1592 01:20:12,880 --> 01:20:16,450 But it's just like, are we giving room for policymakers 1593 01:20:16,450 --> 01:20:19,390 to make these same judgments and put out 1594 01:20:19,390 --> 01:20:23,080 these calls for advancements in R&D funding and all 1595 01:20:23,080 --> 01:20:26,140 these other things, with these staged metrics. 1596 01:20:26,140 --> 01:20:27,640 WILLIAM BONVILLIAN: So Chris, do you 1597 01:20:27,640 --> 01:20:30,520 want to give us some closing thoughts on Glenn Fong's work? 1598 01:20:30,520 --> 01:20:31,390 AUDIENCE: Sure. 1599 01:20:31,390 --> 01:20:33,850 So I guess the general theme that we've 1600 01:20:33,850 --> 01:20:36,640 been talking about is that industrial policy in the US 1601 01:20:36,640 --> 01:20:41,230 is kind of obscured or hidden behind these programs, 1602 01:20:41,230 --> 01:20:42,370 by the DOD. 1603 01:20:42,370 --> 01:20:46,810 And they're only manifested when innovations are really 1604 01:20:46,810 --> 01:20:53,290 pushed towards that explicit competitiveness. 1605 01:20:53,290 --> 01:20:56,950 And he claims that increasing US capacity 1606 01:20:56,950 --> 01:20:58,990 to undertake these programs is directly 1607 01:20:58,990 --> 01:21:02,463 relevant to economic competitiveness. 1608 01:21:02,463 --> 01:21:03,880 Which is interesting, because this 1609 01:21:03,880 --> 01:21:05,800 is kind of in direct contrast to what 1610 01:21:05,800 --> 01:21:09,100 we've been talking about in some of the past lectures, 1611 01:21:09,100 --> 01:21:11,650 that there's this post-war paradigm, that they're 1612 01:21:11,650 --> 01:21:15,140 focusing government R&D to basic research. 1613 01:21:15,140 --> 01:21:19,870 Or I believe he calls it like mission agency. 1614 01:21:19,870 --> 01:21:22,410 So I think this is a pretty interesting reading. 1615 01:21:22,410 --> 01:21:25,080 And also, I guess, a side point was 1616 01:21:25,080 --> 01:21:28,200 that, one thing that came up for me was this kind of conflict 1617 01:21:28,200 --> 01:21:31,140 between a focus on economic competitiveness 1618 01:21:31,140 --> 01:21:35,430 and more I guess social impacts or ramifications that 1619 01:21:35,430 --> 01:21:40,510 could result. Like he mentions a couple of times that, 1620 01:21:40,510 --> 01:21:44,550 like welfare policies and stuff aren't considered 1621 01:21:44,550 --> 01:21:46,080 economic competitiveness. 1622 01:21:46,080 --> 01:21:52,410 And using those as metrics isn't exactly a good way 1623 01:21:52,410 --> 01:21:55,090 to look at competitiveness. 1624 01:21:55,090 --> 01:21:57,840 And I thought that was a really interesting way to kind 1625 01:21:57,840 --> 01:22:01,530 of segregate, I guess, the impact 1626 01:22:01,530 --> 01:22:03,298 of these kind of programs. 1627 01:22:03,298 --> 01:22:05,340 And obviously, they're two very different things. 1628 01:22:05,340 --> 01:22:09,600 And DOD probably has to stay out of it. 1629 01:22:09,600 --> 01:22:11,400 And just like we've been mentioning, 1630 01:22:11,400 --> 01:22:13,290 can't really pick winners or losers. 1631 01:22:13,290 --> 01:22:15,540 But yeah, I thought that was another interesting kind 1632 01:22:15,540 --> 01:22:17,780 of subtext theme.