1 00:00:01,800 --> 00:00:05,560 Speaker 1: For all the focus on deficits and tariffs, you might 2 00:00:05,680 --> 00:00:09,560 Speaker 1: think economic ties between the US and China are just 3 00:00:09,760 --> 00:00:12,840 Speaker 1: about how much stuff is put on a ship, how 4 00:00:12,920 --> 00:00:16,400 Speaker 1: much it costs, where it's made, and where it's going. 5 00:00:17,400 --> 00:00:22,760 Speaker 1: You would be mistaken. The future belongs to data, not merchandise, 6 00:00:23,239 --> 00:00:27,520 Speaker 1: and the world economy is a duopoly. America and China 7 00:00:27,920 --> 00:00:40,240 Speaker 1: own it. Welcome to Benjamin, a show about the global econome. 8 00:00:40,920 --> 00:00:46,199 Speaker 1: I'm Daniel Moss, columnist at Bloomberg Opinion in New York. 9 00:00:46,840 --> 00:00:50,080 Speaker 1: A few people are as familiar with both the viewers 10 00:00:50,240 --> 00:00:56,000 Speaker 1: and China as Kai Fu Lei. Born in Taiwan, Doctor 11 00:00:56,080 --> 00:01:00,560 Speaker 1: Lee has spent his career straddling Silicon Valley the tech 12 00:01:00,720 --> 00:01:06,120 Speaker 1: precincts of Beijing. He used to run Google China and 13 00:01:06,200 --> 00:01:10,720 Speaker 1: now leads sign Ovation Ventures, a firm that focuses on 14 00:01:10,840 --> 00:01:14,480 Speaker 1: developing the next big thing. Along the way, he had 15 00:01:14,520 --> 00:01:20,280 Speaker 1: a personal crisis that further sharpened his insights. Dr Lee 16 00:01:20,480 --> 00:01:26,240 Speaker 1: is the author of Ai Superpowers, China, Silicon Valley, and 17 00:01:26,319 --> 00:01:31,399 Speaker 1: the New World Order. It's probably the business book of 18 00:01:31,480 --> 00:01:35,440 Speaker 1: the moment. Dr leeh thanks for joining us, and thanks 19 00:01:35,480 --> 00:01:40,000 Speaker 1: for not putting the word disruption in the title. Thank you. 20 00:01:40,240 --> 00:01:43,440 Speaker 1: It's great to talk to you. I've heard you describe 21 00:01:43,640 --> 00:01:47,400 Speaker 1: China as the new Saudi Arabia and data as the 22 00:01:47,480 --> 00:01:50,640 Speaker 1: new oil. What did you mean by that and how 23 00:01:50,680 --> 00:01:55,600 Speaker 1: does that capture the essence of this moment? Sure? The 24 00:01:55,640 --> 00:01:59,160 Speaker 1: way are the official intelligence or AI works today is 25 00:01:59,200 --> 00:02:03,560 Speaker 1: that within this single application, when an AI algorithm is 26 00:02:03,600 --> 00:02:07,720 Speaker 1: trained down a huge amount of data with corresponding labels, 27 00:02:08,200 --> 00:02:11,720 Speaker 1: it can then make decisions in that domain at a 28 00:02:11,840 --> 00:02:16,240 Speaker 1: superhuman accuracy. So the more the data, the better. So 29 00:02:16,280 --> 00:02:20,200 Speaker 1: the system is not programmed by humans to do make decisions, 30 00:02:20,240 --> 00:02:23,840 Speaker 1: but it learns from data. And the amount of data 31 00:02:23,880 --> 00:02:28,480 Speaker 1: that's needed is is huge. So today China has the 32 00:02:28,520 --> 00:02:31,240 Speaker 1: most data in the world and that gives a certain 33 00:02:31,280 --> 00:02:37,040 Speaker 1: advantage to China. Now, technology, business, and economic literature has 34 00:02:37,080 --> 00:02:42,200 Speaker 1: been gushing about artificial intelligence for a while. What's changed. 35 00:02:42,960 --> 00:02:46,359 Speaker 1: I think the biggest change was that ten years ago 36 00:02:46,919 --> 00:02:51,280 Speaker 1: a new technology called deep learning was invented and it 37 00:02:51,440 --> 00:02:56,119 Speaker 1: was applied in many many domains, and starting about six 38 00:02:56,200 --> 00:02:59,720 Speaker 1: years ago, we began to see its efficacy in face 39 00:02:59,720 --> 00:03:03,400 Speaker 1: wreck cognition, later speech recognition, later the game of Go, 40 00:03:04,240 --> 00:03:08,960 Speaker 1: and almost all subsequent technologies were built on this deep 41 00:03:09,040 --> 00:03:13,320 Speaker 1: learning or associated technologies. So that was the single big 42 00:03:13,360 --> 00:03:18,760 Speaker 1: breakthrough that became clear to the researchers about six years ago, 43 00:03:19,040 --> 00:03:21,160 Speaker 1: but to the rest of the world about two and 44 00:03:21,240 --> 00:03:25,040 Speaker 1: a half years ago when Alpha go emerged, and this 45 00:03:25,160 --> 00:03:30,400 Speaker 1: technology coincided with the rapidly increasing amount of data because 46 00:03:30,440 --> 00:03:34,400 Speaker 1: deep learning is a very deep network with potentially billions 47 00:03:34,400 --> 00:03:38,160 Speaker 1: of parameters to train, so it was hungry for data. 48 00:03:38,600 --> 00:03:43,120 Speaker 1: So the accessibility and growth of Internet data alongside with 49 00:03:43,240 --> 00:03:48,680 Speaker 1: that the development of deep learning together created never before 50 00:03:48,760 --> 00:03:52,840 Speaker 1: seeing accuracy in all kinds of tasks that deep learning 51 00:03:52,880 --> 00:03:56,800 Speaker 1: plus large data tackles. Can you put this in the 52 00:03:57,000 --> 00:04:02,240 Speaker 1: context of economic history for the past couple of centuries? 53 00:04:02,400 --> 00:04:06,560 Speaker 1: Where does this rank in the period that began with say, 54 00:04:06,640 --> 00:04:12,040 Speaker 1: the Industrial Revolution in the United Kingdom? Okay, I think 55 00:04:12,080 --> 00:04:17,760 Speaker 1: AI should definitely rank among the Industrial Revolution, in particular 56 00:04:17,920 --> 00:04:26,719 Speaker 1: with the steam engine, electricity, and perhaps the internet computer revolution. 57 00:04:27,400 --> 00:04:31,159 Speaker 1: These probably are the top three or four in my 58 00:04:31,279 --> 00:04:35,520 Speaker 1: personal opinion. It will end up proven to be number one, 59 00:04:35,880 --> 00:04:38,640 Speaker 1: but of course that remains to be seen. Does the 60 00:04:38,760 --> 00:04:43,800 Speaker 1: industrial and economic map of the world now resemble something 61 00:04:43,839 --> 00:04:48,680 Speaker 1: from the nine century but instead of European powers gobbling 62 00:04:48,760 --> 00:04:52,880 Speaker 1: up territory in Africa and Asia, China in the United 63 00:04:52,920 --> 00:04:57,799 Speaker 1: States carving up the technology world. What does that map 64 00:04:57,839 --> 00:05:01,680 Speaker 1: look like today? I think if we take a snapshot 65 00:05:01,800 --> 00:05:05,520 Speaker 1: right now, US is still has the upper hand with 66 00:05:05,720 --> 00:05:11,640 Speaker 1: American technologies penetrating developed countries and some developing countries, and 67 00:05:11,800 --> 00:05:15,320 Speaker 1: China is largely still within China, with a little bit 68 00:05:15,360 --> 00:05:19,440 Speaker 1: of penetration into other countries. But we're seeing a rapidly 69 00:05:19,600 --> 00:05:25,800 Speaker 1: increasing pace that Chinese technology companies, and that's primarily mobile 70 00:05:26,200 --> 00:05:32,760 Speaker 1: apps and AI companies going from China to Southeast Asia, 71 00:05:33,120 --> 00:05:37,760 Speaker 1: Middle East, and Africa. They're just at the beginning, so 72 00:05:37,800 --> 00:05:41,720 Speaker 1: it's too early to tell the final results. But given 73 00:05:41,800 --> 00:05:46,800 Speaker 1: that the American giants have largely ignored those regions. Um 74 00:05:46,880 --> 00:05:50,360 Speaker 1: as you add India also, since that's generally separate from 75 00:05:50,440 --> 00:05:54,520 Speaker 1: the Southeast Asia, US is generally not paid too much 76 00:05:54,560 --> 00:05:58,280 Speaker 1: attention to those four regions. I think it gives China 77 00:05:58,440 --> 00:06:03,520 Speaker 1: an opportunity to go into these four regions. And in addition, 78 00:06:03,760 --> 00:06:08,440 Speaker 1: the Chinese demographics may match those regions better than the US, 79 00:06:08,480 --> 00:06:13,479 Speaker 1: so the products may be more attractive. And coincidentally, it 80 00:06:13,560 --> 00:06:19,080 Speaker 1: also matches the Belt Road initiative from China. So I 81 00:06:19,120 --> 00:06:22,479 Speaker 1: think the developed countries will end up continuing to be 82 00:06:23,279 --> 00:06:29,279 Speaker 1: a stronghold of American dominance in technology. But I think 83 00:06:29,720 --> 00:06:34,039 Speaker 1: most of the rest of our world would potentially have 84 00:06:34,240 --> 00:06:38,320 Speaker 1: a high degree of Chinese penetration, probably not as strong 85 00:06:38,400 --> 00:06:41,719 Speaker 1: as US in the developed countries, but let's say a 86 00:06:42,279 --> 00:06:47,560 Speaker 1: more than fifty percent penetration or dependency on Chinese technologies. 87 00:06:47,720 --> 00:06:51,160 Speaker 1: Over let's say the next five to ten years. So 88 00:06:51,600 --> 00:06:57,479 Speaker 1: broadly speaking, the US would have Western Europe, Canada, and Japan, 89 00:06:58,680 --> 00:07:05,720 Speaker 1: and China would have the rest, probably not quite I 90 00:07:05,760 --> 00:07:09,920 Speaker 1: think um. I think the US would have nearly total 91 00:07:10,000 --> 00:07:16,480 Speaker 1: penetration of most of, if not all, of Europe, Canada, Australia, 92 00:07:17,160 --> 00:07:23,400 Speaker 1: and Japan, and possibly some of South America and a 93 00:07:23,440 --> 00:07:26,000 Speaker 1: little bit at the rest of the world. And China 94 00:07:26,120 --> 00:07:31,640 Speaker 1: would have all of China and more than fifty of India, 95 00:07:31,760 --> 00:07:37,200 Speaker 1: Southeast Asia, Middle East, and Africa. The trade disputes between 96 00:07:37,320 --> 00:07:40,880 Speaker 1: the United States and China, which dominate much of the 97 00:07:40,960 --> 00:07:47,880 Speaker 1: public discourse in America these days, that principally about merchandise trade, 98 00:07:48,320 --> 00:07:53,200 Speaker 1: about deficits, about the cost of production. That seems to 99 00:07:53,240 --> 00:07:58,400 Speaker 1: be a completely different conversation from that of the world 100 00:07:58,480 --> 00:08:02,640 Speaker 1: that you're inhabiting. Well to be fair. There's also intellectual property, 101 00:08:02,920 --> 00:08:07,280 Speaker 1: which I think is crosses both. I do agree that 102 00:08:07,320 --> 00:08:11,880 Speaker 1: the trade disputes are include the intellectual property don't affect 103 00:08:12,480 --> 00:08:17,800 Speaker 1: um our area, which is AI mobile software. But some 104 00:08:17,920 --> 00:08:23,920 Speaker 1: of those issues certainly do affect semiconductor PC UM mobile 105 00:08:23,960 --> 00:08:26,840 Speaker 1: phones and so on, which are very much related to 106 00:08:26,960 --> 00:08:30,480 Speaker 1: the area as we invest in now. You were born 107 00:08:30,480 --> 00:08:33,400 Speaker 1: in Taiwan, you came to the United States as a 108 00:08:33,440 --> 00:08:37,800 Speaker 1: small boy to Tennessee. You've worked in the Valley, You've 109 00:08:37,800 --> 00:08:40,680 Speaker 1: worked for an American company in China, you have your 110 00:08:40,679 --> 00:08:45,480 Speaker 1: own venture capital firm. As a student of the United 111 00:08:45,520 --> 00:08:51,160 Speaker 1: States and the economic and technological currents, what from your perspective, 112 00:08:51,200 --> 00:08:53,280 Speaker 1: is going on in this country right now? How would 113 00:08:53,320 --> 00:08:58,199 Speaker 1: you define this moment? Do you mean the technology development 114 00:08:58,400 --> 00:09:02,680 Speaker 1: or the trade disputes? If you've wrapped up the overall 115 00:09:02,840 --> 00:09:07,800 Speaker 1: vibe in America right now compared with previous visits, from 116 00:09:07,800 --> 00:09:09,480 Speaker 1: the time you were growing up, from the time you 117 00:09:09,520 --> 00:09:14,120 Speaker 1: were a student at university, here, what's changed in this 118 00:09:14,280 --> 00:09:20,720 Speaker 1: country and why? I think in Silicon Valley not much 119 00:09:20,760 --> 00:09:25,440 Speaker 1: has changed. There has been and still is a very 120 00:09:25,480 --> 00:09:28,960 Speaker 1: strong self confidence that it is the center of the world. 121 00:09:29,679 --> 00:09:33,800 Speaker 1: The rest of America is beginning to realize that there 122 00:09:34,000 --> 00:09:40,680 Speaker 1: is an alternate technological force emerging that's called China. And 123 00:09:41,880 --> 00:09:47,640 Speaker 1: I think the Silicon Valley centric view is potentially dangerous 124 00:09:48,320 --> 00:09:50,680 Speaker 1: because it is a great view. It is a great 125 00:09:50,920 --> 00:09:54,680 Speaker 1: way to develop products, but China has proven that it 126 00:09:54,800 --> 00:09:57,720 Speaker 1: is not the only way. So it would be wise 127 00:09:57,800 --> 00:10:02,600 Speaker 1: to consider at least the two alternate ways that great 128 00:10:02,640 --> 00:10:09,160 Speaker 1: innovative products can be developed. And in terms of overall sentiment, 129 00:10:09,960 --> 00:10:16,959 Speaker 1: I think I sense more divisiveness in America. I think 130 00:10:17,360 --> 00:10:22,600 Speaker 1: before there was a much greater unity, and I think 131 00:10:22,640 --> 00:10:28,600 Speaker 1: there is um more disagreements today, and I think there 132 00:10:28,640 --> 00:10:33,080 Speaker 1: are it feels like they're more uncertainty, but the economy 133 00:10:33,200 --> 00:10:39,959 Speaker 1: is good and the people feel confident about the American technologies. Yeah, 134 00:10:40,080 --> 00:11:14,840 Speaker 1: that's basically what I see. How profoundly did your brush 135 00:11:15,200 --> 00:11:21,440 Speaker 1: with cancer effect your perspective? Very very profoundly. In my 136 00:11:21,559 --> 00:11:25,640 Speaker 1: first fifty plus years of my life, I've I've really 137 00:11:25,880 --> 00:11:29,840 Speaker 1: was a workaholic, and I felt work was the center 138 00:11:29,880 --> 00:11:34,800 Speaker 1: of my life. And family was UM a set of 139 00:11:34,840 --> 00:11:38,880 Speaker 1: people I depended on, but I gave them time as 140 00:11:38,920 --> 00:11:42,520 Speaker 1: I could afford from my work. UM gave enough times 141 00:11:42,520 --> 00:11:48,600 Speaker 1: so that they tolerate my lack of attention. But as 142 00:11:48,640 --> 00:11:52,880 Speaker 1: I found out that I had cancer, I realized that 143 00:11:52,920 --> 00:11:57,880 Speaker 1: all the accomplishment really meant nothing, and that, like most 144 00:11:57,920 --> 00:12:01,920 Speaker 1: people facing the possibility of death, I realized that what 145 00:12:02,160 --> 00:12:08,120 Speaker 1: was important in life was first and foremost to love 146 00:12:08,200 --> 00:12:10,400 Speaker 1: and give love back to the people who love me, 147 00:12:11,120 --> 00:12:14,960 Speaker 1: and secondly, to follow the things and do things that 148 00:12:15,080 --> 00:12:19,720 Speaker 1: I am passionate about. And that's very consistent across thousands 149 00:12:19,760 --> 00:12:22,439 Speaker 1: of people facing death, and I think there's a lot 150 00:12:22,480 --> 00:12:27,200 Speaker 1: of wisdom in people facing death. So fortunately, I'm now 151 00:12:27,360 --> 00:12:32,280 Speaker 1: in remission and when I now come back to work, 152 00:12:32,880 --> 00:12:36,800 Speaker 1: I no longer put work as my only priority, and 153 00:12:36,960 --> 00:12:40,560 Speaker 1: when my kids come home, I actually just don't work, 154 00:12:41,040 --> 00:12:43,240 Speaker 1: and it's a reversal of what I used to do. 155 00:12:43,679 --> 00:12:46,760 Speaker 1: I still spend a lot of hours working less than before, 156 00:12:47,240 --> 00:12:50,160 Speaker 1: but it's a matter of priorities. It's a matter of 157 00:12:50,200 --> 00:12:53,600 Speaker 1: finally realizing what was important. And it also made me 158 00:12:53,640 --> 00:12:59,679 Speaker 1: realize that workaholism is something that haunts both the Americans 159 00:12:59,760 --> 00:13:03,959 Speaker 1: and the Chinese, and that there really is more to 160 00:13:04,200 --> 00:13:09,080 Speaker 1: life than work. So in some sense, uh, as we 161 00:13:09,240 --> 00:13:12,880 Speaker 1: enter the era of AI, I think AI is here 162 00:13:12,920 --> 00:13:17,359 Speaker 1: to relieve us from a lot of redundant or repetitive 163 00:13:17,480 --> 00:13:20,800 Speaker 1: or routine work that we're doing, giving us a lot 164 00:13:20,800 --> 00:13:25,040 Speaker 1: more time back to us so that we can give 165 00:13:25,280 --> 00:13:29,199 Speaker 1: time to the people who love us, We can do 166 00:13:29,240 --> 00:13:33,440 Speaker 1: the things that we are passionate about, and and we 167 00:13:33,480 --> 00:13:36,520 Speaker 1: can have time to think about the real meaning of life, 168 00:13:36,559 --> 00:13:40,600 Speaker 1: which is definitely not work. In keeping with that, what 169 00:13:40,640 --> 00:13:46,199 Speaker 1: does this new technological world order main for the future 170 00:13:46,240 --> 00:13:52,920 Speaker 1: of work? Because AI is capable of doing single, distinct 171 00:13:53,000 --> 00:13:57,079 Speaker 1: tasks much better than people, that means we don't have 172 00:13:57,160 --> 00:14:02,000 Speaker 1: to be threatened that AI will become robot overlords ruling 173 00:14:02,040 --> 00:14:05,720 Speaker 1: over us because there are tools that we control. On 174 00:14:05,760 --> 00:14:09,000 Speaker 1: the other hand, if they can do single tasks better 175 00:14:09,080 --> 00:14:12,760 Speaker 1: than us, there are many people who do jobs that 176 00:14:12,880 --> 00:14:17,880 Speaker 1: are composed of a number of single tasks. That means 177 00:14:17,960 --> 00:14:22,120 Speaker 1: those jobs will be displaced by AI, either one on 178 00:14:22,240 --> 00:14:26,800 Speaker 1: one or through industry disruption. So in terms of the 179 00:14:26,840 --> 00:14:31,000 Speaker 1: future of work, I'm quite concerned that a certain percentage 180 00:14:31,000 --> 00:14:36,400 Speaker 1: of jobs that are not requiring the most creativity and 181 00:14:36,480 --> 00:14:40,960 Speaker 1: not requiring the greatest human touch and interaction, those kinds 182 00:14:40,960 --> 00:14:44,560 Speaker 1: of routine jobs will be replaced by AI, and that 183 00:14:45,160 --> 00:14:49,000 Speaker 1: the time has come for us to plan to real 184 00:14:49,520 --> 00:14:53,760 Speaker 1: to reskill the people in those jobs, and while we 185 00:14:53,800 --> 00:14:57,960 Speaker 1: still have time to create jobs that can be both 186 00:14:58,000 --> 00:15:03,160 Speaker 1: satisfying and reasonably play paying, so that people can move 187 00:15:03,200 --> 00:15:06,200 Speaker 1: on to the next steps in their lives rather than 188 00:15:06,360 --> 00:15:09,840 Speaker 1: just to see AI take over one type of job 189 00:15:09,920 --> 00:15:14,040 Speaker 1: after another, Doctor Lee. You're probably familiar with some of 190 00:15:14,080 --> 00:15:18,240 Speaker 1: the criticism that's made of Northern California and in some 191 00:15:18,280 --> 00:15:22,760 Speaker 1: ways the state in general, that the scene is to uniform, 192 00:15:22,840 --> 00:15:26,200 Speaker 1: there's too much group think, it's a one party state, 193 00:15:27,040 --> 00:15:30,280 Speaker 1: and it's lost its age. What's your perspective on that 194 00:15:31,000 --> 00:15:36,720 Speaker 1: about California, about Silicon Valley California in general, versus what 195 00:15:36,760 --> 00:15:39,520 Speaker 1: you're seeing when you hang out in the tech precincts 196 00:15:39,520 --> 00:15:44,560 Speaker 1: of Beijing. Well, I am very conflicted because at the 197 00:15:44,600 --> 00:15:49,120 Speaker 1: same time, I have tremendous respect of the vision that's 198 00:15:49,160 --> 00:15:51,720 Speaker 1: come out of Silicon Valley, that has led the world 199 00:15:51,800 --> 00:15:55,600 Speaker 1: for the last thirty years, and that still has many 200 00:15:55,640 --> 00:15:59,880 Speaker 1: of the world's most amazing companies and startups. But I 201 00:16:00,000 --> 00:16:04,280 Speaker 1: I'm also at the same time concerned that the success 202 00:16:04,400 --> 00:16:10,000 Speaker 1: has created some degree of self entitlement and maybe even 203 00:16:10,040 --> 00:16:13,080 Speaker 1: a little bit of hubris, the feeling that the world 204 00:16:13,200 --> 00:16:17,920 Speaker 1: revolves around Silicon Valley. They belief that um only the 205 00:16:17,960 --> 00:16:22,960 Speaker 1: companies there matter, the belief that only Silicon Valley innovates, 206 00:16:23,160 --> 00:16:27,320 Speaker 1: and only the method of Silicon Valley that matters when 207 00:16:27,320 --> 00:16:31,600 Speaker 1: it comes to innovation. And I think that is myopic. 208 00:16:32,160 --> 00:16:36,360 Speaker 1: And if if we, if Americans all really believe that, 209 00:16:37,000 --> 00:16:40,120 Speaker 1: then it would be missing all the exciting things happening 210 00:16:40,120 --> 00:16:45,280 Speaker 1: in China. Chinese model of innovation is different. It's heavier, 211 00:16:45,720 --> 00:16:50,120 Speaker 1: it's building impregnable business models that actually are more built 212 00:16:50,160 --> 00:16:55,800 Speaker 1: to last, but maybe less visionary and technically exciting. I 213 00:16:55,840 --> 00:16:59,480 Speaker 1: think as citizens of this world, we should all be 214 00:16:59,720 --> 00:17:04,119 Speaker 1: hum ball and study different types of innovation and be 215 00:17:04,240 --> 00:17:09,320 Speaker 1: open to different models. And if Silicon Valley continues to 216 00:17:09,560 --> 00:17:15,080 Speaker 1: only look within and not accept external innovation, then it 217 00:17:15,160 --> 00:17:18,399 Speaker 1: will be missing half of the teaching materials for the 218 00:17:18,480 --> 00:17:21,840 Speaker 1: young people in Silicon Valley. That I can assure you 219 00:17:21,920 --> 00:17:26,840 Speaker 1: that the young people in China are studying humbly both 220 00:17:27,240 --> 00:17:30,560 Speaker 1: the successes in the US, the Googles and facebooks and 221 00:17:30,640 --> 00:17:33,919 Speaker 1: the successes from China the Ali Baba's and made Twins 222 00:17:33,960 --> 00:17:38,320 Speaker 1: and ten cents, and that gives a more robust set 223 00:17:38,680 --> 00:17:42,800 Speaker 1: of instructions, if you will, for the Chinese entrepreneurs that 224 00:17:42,920 --> 00:17:47,639 Speaker 1: there's no reason American entrepreneurs should um keep the blinders 225 00:17:47,680 --> 00:17:51,639 Speaker 1: on and throw away half of the instructions that could 226 00:17:51,640 --> 00:17:56,320 Speaker 1: be so helpful to their growth as entrepreneurs. What role 227 00:17:56,480 --> 00:18:00,400 Speaker 1: should the state play in this? I was fortunate enough 228 00:18:00,440 --> 00:18:04,120 Speaker 1: to be at an event last month with Audrey Tongue, 229 00:18:05,040 --> 00:18:09,119 Speaker 1: Taiwan's Digital minister, whom you probably know. Uh. That was 230 00:18:09,160 --> 00:18:14,600 Speaker 1: a very special experience. It should China and the United 231 00:18:14,640 --> 00:18:18,639 Speaker 1: States each have a digital affairs minister like Audrey Tongue. 232 00:18:20,040 --> 00:18:23,879 Speaker 1: I'm not sure. I think UM, whatever role is called 233 00:18:24,359 --> 00:18:29,720 Speaker 1: chief technical officer, chief Digital officer, chief AI officer, that 234 00:18:29,960 --> 00:18:34,280 Speaker 1: role has to be empowered in order to be impactful 235 00:18:34,680 --> 00:18:39,600 Speaker 1: for any country. I think what's perhaps more important is 236 00:18:39,760 --> 00:18:44,520 Speaker 1: to let private enterprises do what they do best. That is, 237 00:18:44,720 --> 00:18:49,840 Speaker 1: let private capital invest in private companies to build companies, 238 00:18:50,280 --> 00:18:53,360 Speaker 1: and to the extent that they're successful in getting users, 239 00:18:53,359 --> 00:18:56,600 Speaker 1: in generating revenues and profits, they will get more money 240 00:18:56,640 --> 00:19:01,399 Speaker 1: and then potentially be listed publicly under to success. But 241 00:19:01,520 --> 00:19:05,919 Speaker 1: the role of governments is really to provide the types 242 00:19:05,960 --> 00:19:11,639 Speaker 1: of infrastructure that private companies cannot do, and to have 243 00:19:12,600 --> 00:19:17,480 Speaker 1: really as open as possible technical policies that let new 244 00:19:17,520 --> 00:19:23,480 Speaker 1: technologies have a chance to perhaps grow faster and potentially 245 00:19:23,520 --> 00:19:29,600 Speaker 1: even disrupt traditional UM technologies. I think it is that's 246 00:19:29,760 --> 00:19:34,200 Speaker 1: openness and infrastructure building UH that will ensure the country 247 00:19:34,400 --> 00:19:39,239 Speaker 1: moves forward. China does a reasonably good job on both UH. 248 00:19:39,359 --> 00:19:43,720 Speaker 1: Infrastructure building would be examples like building a new highway 249 00:19:43,840 --> 00:19:47,119 Speaker 1: for autonomous driving or even a new city the size 250 00:19:47,119 --> 00:19:52,320 Speaker 1: of Chicago for autonomous driving. And as far as open 251 00:19:52,359 --> 00:19:56,480 Speaker 1: policies would be the example of letting the Chinese software 252 00:19:56,480 --> 00:20:02,240 Speaker 1: companies develop payment so much so that these up mobile 253 00:20:02,280 --> 00:20:07,439 Speaker 1: payments have squeezed out cash as well as credit cards 254 00:20:07,800 --> 00:20:12,960 Speaker 1: from almost into obsolescence. So these are the kinds of 255 00:20:13,000 --> 00:20:17,120 Speaker 1: examples that has pushed China ahead to the extent possible. 256 00:20:17,359 --> 00:20:21,720 Speaker 1: I think other countries can try to build similar infrastructures 257 00:20:21,760 --> 00:20:27,000 Speaker 1: and have such open mindedness about technology, otherwise there would 258 00:20:27,040 --> 00:20:32,639 Speaker 1: be risks of falling behind. I attended your Asia Society 259 00:20:32,680 --> 00:20:36,199 Speaker 1: event in New York October one, and I have to 260 00:20:36,240 --> 00:20:40,040 Speaker 1: admit to being surprised to see you in an extremely smart, 261 00:20:40,560 --> 00:20:45,000 Speaker 1: well tailed three piece suit with an immaculate tie. I 262 00:20:45,080 --> 00:20:47,800 Speaker 1: don't think it was many people's vision of what a 263 00:20:47,880 --> 00:20:50,920 Speaker 1: tech guru would look like. Where had you just been 264 00:20:52,680 --> 00:20:55,320 Speaker 1: I knew I was going to the Asia Society. I 265 00:20:55,359 --> 00:21:00,199 Speaker 1: was going to greet many people who wear suits and tie. Um, 266 00:21:00,440 --> 00:21:03,720 Speaker 1: but to be fair, I do wear a certain tie 267 00:21:04,200 --> 00:21:08,400 Speaker 1: quite often and that's my prefer attire. Dr Lee, thank 268 00:21:08,440 --> 00:21:12,520 Speaker 1: you so much for joining us, and congratulations on the book. Okay, 269 00:21:12,520 --> 00:21:25,280 Speaker 1: thanks so much. Benchmark will be back next week. Until then, 270 00:21:25,320 --> 00:21:29,360 Speaker 1: you can find us on the Bloomberg terminal, Bloomberg dot com, 271 00:21:29,359 --> 00:21:33,480 Speaker 1: our Bloomberg app, as well as podcast destinations such as 272 00:21:33,520 --> 00:21:38,439 Speaker 1: Apple Podcasts, Spotify, or wherever you listen. We'd love it 273 00:21:38,720 --> 00:21:40,720 Speaker 1: if he took the time to rate and review the 274 00:21:40,760 --> 00:21:44,520 Speaker 1: show so more people can find us. You can follow 275 00:21:44,600 --> 00:21:50,160 Speaker 1: me on Twitter at moss underscore E. Benchmark is produced 276 00:21:50,160 --> 00:21:55,000 Speaker 1: by tofa Foreheirs. The head of Bloomberg Podcasts is Francesco Leaving. 277 00:21:55,560 --> 00:22:00,760 Speaker 1: Thanks for listening. See you next time. It was not 278 00:22:01,200 --> 00:22:03,720 Speaker 1: the Boy