1 00:00:01,370 --> 00:00:07,460 Hi, my name is Mike Wooldridge, I am head of Department of Computer Science at the University of Oxford. 2 00:00:07,460 --> 00:00:13,850 I am, as you might guess, home. I like, I guess most people on this on this webinar are. 3 00:00:13,850 --> 00:00:17,820 It's my very great pleasure to welcome you to the straight. 4 00:00:17,820 --> 00:00:26,780 She lecture for Michaelmas term 2020. This is, I think, the first straight lecture that has been completely virtual. 5 00:00:26,780 --> 00:00:31,480 You could regard that as a feature or a bug, depending on your point of view. 6 00:00:31,480 --> 00:00:39,200 As with all of these kind of events, glitches happen. The technology is not perfect and we're having to coordinate things very remotely. 7 00:00:39,200 --> 00:00:43,850 So if things go wrong back with us, we will recover very, very quickly, I'm sure. 8 00:00:43,850 --> 00:00:50,330 So on to today's lecture. Today's lecture is by Matt Ridley. 9 00:00:50,330 --> 00:00:59,960 Matt Ridley is a Matt Ridley, sits in the House of Lords on the conservative benches. 10 00:00:59,960 --> 00:01:04,910 He has been there since 2013. His books have sold over a million copies. 11 00:01:04,910 --> 00:01:09,140 They've been translated into 32 languages and they've won several awards. 12 00:01:09,140 --> 00:01:14,210 His books include The Red Queen Genome, The Rational Optimist and the Evolution of Everything. 13 00:01:14,210 --> 00:01:18,860 And the reason he's here today is that his most recent book is entitled How Innovation Works. 14 00:01:18,860 --> 00:01:24,530 It was published in 2020. He joined the House of Lords in February 2013. 15 00:01:24,530 --> 00:01:31,780 He served on the Science and Technology Select Committee in the Artificial Intelligence Select Committee. 16 00:01:31,780 --> 00:01:35,410 He was founding chairman for the International Centre for Life in Newcastle. 17 00:01:35,410 --> 00:01:40,750 He created the Mind and Matter column for The Wall Street Journal in 2010, and he was a columnist for The Times. 18 00:01:40,750 --> 00:01:47,740 In 2013 through to 2018, he is a fellow of the Royal Society of Literature and the Academy of Medical Sciences. 19 00:01:47,740 --> 00:01:54,220 And he is a foreign honorary member of the American Academy of the Arts and Sciences, and he lives in Northumberland. 20 00:01:54,220 --> 00:01:58,690 You may wonder what is the special interest in maths? Well, two reasons. 21 00:01:58,690 --> 00:02:03,790 Firstly, I encountered maps through his service on the House of Lords Select Committee for Artificial Intelligence, 22 00:02:03,790 --> 00:02:09,490 which I gave evidence at, and and he has a special interest in that. 23 00:02:09,490 --> 00:02:17,080 But in addition, his most recent book is on innovation and Innovation is something which in the Department of Computer Science, 24 00:02:17,080 --> 00:02:26,680 we are extremely active in at the moment. This is an unprecedented time with respect to innovation in the Department of Computer Science. 25 00:02:26,680 --> 00:02:32,080 We have a range of spin off companies which have been enormously successful over the last few years. 26 00:02:32,080 --> 00:02:37,090 So we look forward to hearing what Matt has to tell us about how innovation actually works. 27 00:02:37,090 --> 00:02:42,700 Before I go any further, I have to give a very big shout out to our sponsors. 28 00:02:42,700 --> 00:02:50,050 We are this year, as always, extremely grateful to acknowledge the sponsorship of Oxford Asset Management. 29 00:02:50,050 --> 00:02:53,230 They had been sponsoring our lectures now for a number of years, 30 00:02:53,230 --> 00:02:59,230 and they have enabled us to do things with these lectures that simply weren't possible previously to take to bring PE, 31 00:02:59,230 --> 00:03:04,450 bring over speakers and to reach an audience that we wouldn't have been able to do previously. 32 00:03:04,450 --> 00:03:10,590 So we are extremely grateful to Oxford Asset Management. I think they would probably like me to say that they are hiring. 33 00:03:10,590 --> 00:03:17,050 So if you're interested in machine learning, for example, if you're interested in finance, Oxford Asset Management are currently hiring. 34 00:03:17,050 --> 00:03:23,230 And a number of our graduates and indeed one of my DFL students says has gone to work for them in the past. 35 00:03:23,230 --> 00:03:27,730 So that's Oxford Asset Management. As always, we are extremely grateful to them. 36 00:03:27,730 --> 00:03:32,830 So without further ado, what I'm going to hand over now would do now is hand over to Mat's lecture. 37 00:03:32,830 --> 00:03:47,610 So let's go live with Mat's lecture. Thank you. Good afternoon. 38 00:03:47,610 --> 00:03:55,380 It's great to be with you. It's a huge honour to deliver the stretchy lecture, and I'm most grateful to Michael Wooldridge for inviting me to do this. 39 00:03:55,380 --> 00:04:03,420 I've learnt a lot from him about artificial intelligence and other matters, and it's a real honour to be with you this afternoon. 40 00:04:03,420 --> 00:04:08,070 I only wish I could be in Oxford in person. 41 00:04:08,070 --> 00:04:18,210 The topic of my talk is innovation, and that's an enormous important subject and one on which an awful lot of people know an awful lot. 42 00:04:18,210 --> 00:04:28,660 What am I trying to bring to this topic? I think I'm trying to bring the perspective of an evolutionary biologist who has written about technology 43 00:04:28,660 --> 00:04:37,300 for 20 or 30 years and who has become more more interested in this mysterious phenomenon called innovation. 44 00:04:37,300 --> 00:04:41,500 What it is, why it happens to human beings at all. 45 00:04:41,500 --> 00:04:44,320 Why it happens when and where it does. 46 00:04:44,320 --> 00:04:56,140 And why it takes place quickly in some sectors and slowly and others and at different times and in different places at different rates. 47 00:04:56,140 --> 00:05:01,750 I believe it's a somewhat mysterious phenomenon. I don't think we fully understand innovation. 48 00:05:01,750 --> 00:05:12,130 Economic theory struggles to formally incorporate innovation and to explain why it's occurring, even though it relies upon it. 49 00:05:12,130 --> 00:05:16,450 Innovation is the main theme of the last few hundred years of human history. 50 00:05:16,450 --> 00:05:25,210 I would argue it explains the extraordinary enrichment of the human species, the incredible decline of poverty of recent decades. 51 00:05:25,210 --> 00:05:32,710 But also many of the trends that affect our politics are economics, our warfare and so on. 52 00:05:32,710 --> 00:05:39,520 So innovation matters. And this has been driven home to us enormously by the current pandemic. 53 00:05:39,520 --> 00:05:46,330 The fact that we entered this pandemic without having done enough innovation to our method of developing vaccines, 54 00:05:46,330 --> 00:05:52,210 for example, is, I think, an important point lesson that we need to learn. 55 00:05:52,210 --> 00:06:01,180 We haven't been able to improve the rate at which we produce vaccines or the efficiency with which they work much in recent decades. 56 00:06:01,180 --> 00:06:10,270 That may be changing. These messenger RNA vaccines and the one from Oxford have been developed at great speed and look to be very promising. 57 00:06:10,270 --> 00:06:17,440 But it took the pandemic to shake us out of what was essentially a complacency about medical innovation. 58 00:06:17,440 --> 00:06:21,700 In recent years, I would argue. So we need more innovation, not less. 59 00:06:21,700 --> 00:06:27,370 If we are to survive the 21st century in good order. 60 00:06:27,370 --> 00:06:35,720 Well, what I want to do is start sharing a few slides and talk through what I think are the important themes of innovation, 61 00:06:35,720 --> 00:06:44,190 and these come from my new book, How Innovation Works, which essentially tells a bunch of stories. 62 00:06:44,190 --> 00:06:52,230 I tell stories about the search engine and the steam engine, about vaccines, about vaping and after telling stories. 63 00:06:52,230 --> 00:06:57,660 I then try and distil out some lessons about what the patterns of innovation are. 64 00:06:57,660 --> 00:07:09,690 And I think they're slightly different from what we generally assume. So let me start by sharing some slides on my desk at home sits this object. 65 00:07:09,690 --> 00:07:14,850 It's an Australian handshake's of the kind used by Homo erectus. 66 00:07:14,850 --> 00:07:19,940 Half a million years ago, my wife bought it for me on eBay. 67 00:07:19,940 --> 00:07:25,450 And right next to it sits an object of exactly the same size and shape. 68 00:07:25,450 --> 00:07:31,790 And it sent a real shiver down my spine when I noticed the similarity. These two objects both designed to fit the human hand. 69 00:07:31,790 --> 00:07:36,980 Half a million years apart. It's an extraordinary connexion with our ancestors. 70 00:07:36,980 --> 00:07:45,120 And obviously, in a sense, that is half a million years of innovation to go from one object to the other. 71 00:07:45,120 --> 00:07:47,370 The differences between them are quite instructive, I think, 72 00:07:47,370 --> 00:07:54,180 because whereas the axe is made from a single substance and used by a single person who also made it. 73 00:07:54,180 --> 00:08:03,480 The mouse is not made by me, but it is used by me and it's made of lots of different substances, plastic and silicon and metal and so on. 74 00:08:03,480 --> 00:08:09,270 And it embodies lots of different ideas, ideas that occurred to different people at different times, in different places. 75 00:08:09,270 --> 00:08:12,520 And that, to me, is what innovation is all about, 76 00:08:12,520 --> 00:08:20,130 is about the sharing of ideas to increase the usefulness and efficiency of the objects and indeed the habits. 77 00:08:20,130 --> 00:08:26,890 The nonmaterial things by which we organise our world. 78 00:08:26,890 --> 00:08:32,550 And just to drive home what innovation can do. 79 00:08:32,550 --> 00:08:43,690 This is a chart of the number of people dying of malaria in the world between 1990 and 2003, and it was increasing at that time. 80 00:08:43,690 --> 00:08:49,110 And because of climate change, there were widespread predictions that it would increase even faster in the 21st century. 81 00:08:49,110 --> 00:08:53,370 That malaria mortality was something that was going to get worse, not better. 82 00:08:53,370 --> 00:08:57,970 But then in 2003, the graph simply went into reverse. 83 00:08:57,970 --> 00:09:10,440 And a huge decline in mortality from malaria ensued, largely thanks to improvements in the dreadful malaria mortality in sub-Saharan Africa. 84 00:09:10,440 --> 00:09:17,430 What happened in 2003? In 2003, an innovation was promulgated. 85 00:09:17,430 --> 00:09:23,970 Was was was spread across the continent of Africa, largely with the help of the Gates Foundation. 86 00:09:23,970 --> 00:09:30,150 It wasn't antimalarial drugs. It wasn't anti mosquito campaigns. 87 00:09:30,150 --> 00:09:41,490 It was the mosquito sorry. The insecticide impregnated bed net, the mosquito net with insecticide painted on it, a very simple low tech solution, 88 00:09:41,490 --> 00:09:46,980 which turns out to have been responsible for the vast majority of that decline in malaria mortality. 89 00:09:46,980 --> 00:09:53,420 And I was curious as to where this innovation came from, who came up with the idea and why has it been so effective? 90 00:09:53,420 --> 00:10:04,200 And I eventually tracked it back to a paper that was published in 1983 by some scientists from France, 91 00:10:04,200 --> 00:10:12,780 Vietnam and Burkina Faso who did a rather beautiful experiment in which they simply set up 36 huts in Burkina Faso, 92 00:10:12,780 --> 00:10:18,810 each designed as mosquito traps, as well as to mimic ordinary hut design. 93 00:10:18,810 --> 00:10:24,900 And they caught all the mosquitoes that tried to get into the huts and they caught all the mosquitoes trying to get out of the Hudson. 94 00:10:24,900 --> 00:10:29,370 They measured whether they were alive or dead and whether they had eaten a blood meal or not. 95 00:10:29,370 --> 00:10:34,020 And so on. And volunteers slept in these huts for several weeks. 96 00:10:34,020 --> 00:10:38,970 And they found that a mosquito and it was very helpful. 97 00:10:38,970 --> 00:10:42,060 Mosquito net with holes in it was not very helpful. 98 00:10:42,060 --> 00:10:48,930 Mosquito net with insecticide impregnated into it was very helpful, even more so than an ordinary mosquito net. 99 00:10:48,930 --> 00:10:55,200 A huge deterrent effect and remain just as effective even if it had holes in it. 100 00:10:55,200 --> 00:11:03,360 So having holes in it, which is mosquito nets often do after a time of use, did not detract from the effectiveness of this technology. 101 00:11:03,360 --> 00:11:08,400 It's a beautiful experiment. My point is that nobody's heard of this experiment. 102 00:11:08,400 --> 00:11:12,330 Nobody knows who Frederick Dairy at is. Who is the lead author on this? 103 00:11:12,330 --> 00:11:19,500 I contacted him and my bad French. I had communicated with him about how this came to be. 104 00:11:19,500 --> 00:11:29,610 And it's this sort of low tech, unheralded, unprofitable innovation that really can change the world. 105 00:11:29,610 --> 00:11:38,730 My first point that I took from the world, from the stories of innovation that I told, is that innovation is different from invention. 106 00:11:38,730 --> 00:11:43,500 It's not the same thing. Invention means coming up with a new device. 107 00:11:43,500 --> 00:11:49,920 Innovation means making that new device practical, affordable, available. 108 00:11:49,920 --> 00:11:55,740 And that isn't easy. In fact, it's often a lot more work than coming up with a new device in the first place. 109 00:11:55,740 --> 00:12:05,160 And there are innovations such as container shipping, which drastically reduce the cost of shipping goods around the world starting in the 1960s, 110 00:12:05,160 --> 00:12:09,600 which are not inventions at all, are not based on new technologies. 111 00:12:09,600 --> 00:12:18,330 They are simply taking existing technologies and redesigning them in in useful ways. 112 00:12:18,330 --> 00:12:26,250 So it's very important, I think, not to get hung up just on the famous inventor who has the first idea, 113 00:12:26,250 --> 00:12:35,750 but to think about the people who then take these ideas and turn them into practical, reliable and affordable technologies. 114 00:12:35,750 --> 00:12:41,720 To drive home the point, there's a rather funny story that was told by Charles Townes, the inventor of the laser. 115 00:12:41,720 --> 00:12:48,110 He said, there's a beaver and a rabbit. Looking at the Hoover Dam at the beaver says to the rabbit. 116 00:12:48,110 --> 00:12:52,390 No, I didn't build it. But it is based on an idea of mine. 117 00:12:52,390 --> 00:12:56,210 An all too often we focus on the person, on the beaver, 118 00:12:56,210 --> 00:13:02,630 on the person who first has the idea rather than on the people who turn those ideas into practical realities. 119 00:13:02,630 --> 00:13:08,290 I think that's an important lesson of innovation. Innovation is also serendipitous. 120 00:13:08,290 --> 00:13:10,510 That is to say, there's a lot of accidents, 121 00:13:10,510 --> 00:13:17,360 a lot of times people set out to invent one thing and they end up inventing something completely different. 122 00:13:17,360 --> 00:13:22,560 And just as useful or more so. Kevlar, Teflon. 123 00:13:22,560 --> 00:13:28,270 The Post-it note were all invented by people looking for something completely different. 124 00:13:28,270 --> 00:13:34,370 In the case of the Post-it note, Art Fry was one of the people working at 3M. 125 00:13:34,370 --> 00:13:37,930 They were looking for a glue that would work with paper. They couldn't find one. 126 00:13:37,930 --> 00:13:43,930 They came up with this substance that worked as a temporary glue and they thought, that's useless. 127 00:13:43,930 --> 00:13:50,080 And then after I thought, I have to go to choir practise this evening, if I put this glue on the back of some bits of yellow paper, 128 00:13:50,080 --> 00:13:57,520 I can keep my place in my hymnbook and not damage the handbook when I take those bits of paper away and the Post-it note was bought. 129 00:13:57,520 --> 00:14:07,390 Something like DNA fingerprinting is a fine example of an incredibly important technology used in forensics and other methods, 130 00:14:07,390 --> 00:14:13,120 which was invented completely unexpectedly. 131 00:14:13,120 --> 00:14:22,240 It was thought that DNA work was going to be useful in medicine. Nobody saw it transforming criminology, and yet it did in the hands of Alec Lester. 132 00:14:22,240 --> 00:14:27,130 That's our Alec Jeffries of Lester. Now, innovation is disruptive. 133 00:14:27,130 --> 00:14:34,060 We know this. This is the famous point that innovation comes along and changes the world rather dramatically. 134 00:14:34,060 --> 00:14:40,600 Here's a good example of this. A picture of Easter morning in nineteen hundred on Fifth Avenue, 135 00:14:40,600 --> 00:14:51,280 one car amongst hundreds of Horse-Drawn vehicles, the same place on the same day, 13 years later. 136 00:14:51,280 --> 00:14:58,240 Not a single horse in sight. Hundreds of cars. That is the speed at which innovation can change the world. 137 00:14:58,240 --> 00:15:02,110 Just 13 years between those two pictures. 138 00:15:02,110 --> 00:15:13,060 But I make the case that the more you look into disruptive innovations, the more you find that they are actually underpinned by gradual processes, 139 00:15:13,060 --> 00:15:22,660 by processes that build very slowly towards the moment when disruption happen and continue to evolve after the disruption has happened. 140 00:15:22,660 --> 00:15:27,970 So the most disruptive thing that has happened in our lifetime has been the rise of the silicon chip, 141 00:15:27,970 --> 00:15:34,110 the integrated circuit and the whole digital world that has come with it. 142 00:15:34,110 --> 00:15:36,570 And that seems very sudden in many ways. 143 00:15:36,570 --> 00:15:48,030 But when you look at what's happened, the incremental improvement in computing as a result of miniaturisation of silicon technologies, 144 00:15:48,030 --> 00:15:52,980 which we call Moore's Law after Gordon Moore, who noticed it in the 1960s, 145 00:15:52,980 --> 00:16:02,550 has inched forward incrementally for not just 50 years, but more than 100 years, because the last of the old technologies, 146 00:16:02,550 --> 00:16:08,340 things like vacuum tubes, were almost as good as the first of the new ones, the transistor. 147 00:16:08,340 --> 00:16:15,150 There are no step changes on this chart. This is the performance of computers over time. 148 00:16:15,150 --> 00:16:22,170 Basically, in terms of calculations per second, per thousand dollars. And it just marked she's incrementally upwards. 149 00:16:22,170 --> 00:16:25,290 You had to invent each new technology to move on to the next one. 150 00:16:25,290 --> 00:16:33,870 And even when Gordon Moore identified Moore's Law in 1964 and said this process is going to double every 18 months. 151 00:16:33,870 --> 00:16:39,600 We weren't able to say, well, to [INAUDIBLE] with that, let's double it in six months. 152 00:16:39,600 --> 00:16:43,170 Let's jump ahead. If we're gonna we're gonna double it every 18 months. 153 00:16:43,170 --> 00:16:47,500 Why do we quadruple it in 18 months? It turned out not to be possible. 154 00:16:47,500 --> 00:16:54,850 And I think this is a general observation that there is actually much more gradual background to disruptive 155 00:16:54,850 --> 00:17:01,990 innovations than we've tended to get a bit hung up on the idea of disruptive innovation recently. 156 00:17:01,990 --> 00:17:07,030 Innovation is also an evolutionary phenomenon. I wrote a whole book called The Evolution of Everything, 157 00:17:07,030 --> 00:17:14,560 arguing that evolution is a good explanation of how our technology and all our other parts of culture change. 158 00:17:14,560 --> 00:17:24,130 You can see descent with modification in our devices. You can see how one thing is derived from a parent and gives rise to offspring. 159 00:17:24,130 --> 00:17:32,590 The first motorcars looked like a cross between a horse carriage and a steam engine with a little bit of bicycle thrown in and so on. 160 00:17:32,590 --> 00:17:37,300 It was only after that that they took on characteristic features of being a car. 161 00:17:37,300 --> 00:17:42,850 The mobile phone has evolved to get smaller and smaller and then to get bigger and bigger again. 162 00:17:42,850 --> 00:17:48,340 Or recently. And evolution is innovative in another way. 163 00:17:48,340 --> 00:17:49,720 When you get on an aeroplane, 164 00:17:49,720 --> 00:17:58,870 you probably hope that it is designed by an intelligent designer that a clever person put together design for this aeroplane. 165 00:17:58,870 --> 00:18:05,260 But actually, when you think about it, he didn't. All he did was take a previous design and adapt it and so on. 166 00:18:05,260 --> 00:18:10,210 Back to the Wright brothers. People don't start from scratch. 167 00:18:10,210 --> 00:18:14,320 And along the way, there are failed designs that don't work and get discarded. 168 00:18:14,320 --> 00:18:22,090 This is exactly like natural selection. Here is the French philosopher Allar making the same point in nineteen hundred and eight. 169 00:18:22,090 --> 00:18:25,240 Every boat is copied from another boat. That's reason as follows. 170 00:18:25,240 --> 00:18:32,110 In the manner of Darwin, it's clear that a very badly made boat will end up at the bottom up to one or two voyages and thus never be copied. 171 00:18:32,110 --> 00:18:39,340 One could then say with complete rigour that it is the sea herself who chooses the boats to designs the boats, 172 00:18:39,340 --> 00:18:44,470 choosing those which function are destroying the others. 173 00:18:44,470 --> 00:18:52,360 One of the consequences of this way of seeing the world is that you suddenly realise that we are too creationist about the world. 174 00:18:52,360 --> 00:18:55,510 We have learnt not to be creationist about the natural world. 175 00:18:55,510 --> 00:19:01,450 When we see a rainforest, we don't immediately assume that its complexity is the result of an intelligent designer. 176 00:19:01,450 --> 00:19:04,420 But we are creationists about the human world. 177 00:19:04,420 --> 00:19:11,320 When we see order in the human world, we assume that someone, whether it's a government, government or or a designer, is in charge. 178 00:19:11,320 --> 00:19:18,370 But actually, there are lots of things that, in the words of Adam Ferguson, the 18th century Scottish philosopher, 179 00:19:18,370 --> 00:19:23,760 are the result of human action, but not the execution of any human design. 180 00:19:23,760 --> 00:19:28,020 So the English language, for example, is a human invention. 181 00:19:28,020 --> 00:19:34,380 It's not a natural phenomenon, but there is no sense in which it is the execution of design. 182 00:19:34,380 --> 00:19:38,690 There is nobody in charge of designing it. There was nobody who started designing it. 183 00:19:38,690 --> 00:19:48,390 If it evolved through the use of certain habits in language by some people and the discarding of other habits until it became the English language. 184 00:19:48,390 --> 00:19:52,860 And the same is true of modern the modern economy in many ways. 185 00:19:52,860 --> 00:19:58,170 Ten million people eat lunch on a normal day, or at least they did before the pandemic. 186 00:19:58,170 --> 00:20:06,600 The amount of food that they need and the right types of food are available for them every day, day in, day out. 187 00:20:06,600 --> 00:20:12,480 Despite the fact that they might make up their mind at the last minute what they're going to eat. 188 00:20:12,480 --> 00:20:17,430 How is that possible? Who's in charge? Who is London's lunch commissioner? 189 00:20:17,430 --> 00:20:24,000 And why is he so incredibly clever? And of course, the answer is there is no such person. 190 00:20:24,000 --> 00:20:28,880 It's a market. It's a bottom up process, not a top down one. 191 00:20:28,880 --> 00:20:36,920 Now, evolution works by recombination. That is to say, different genetic sequences get mixed together in the process called sex. 192 00:20:36,920 --> 00:20:43,070 So that you get new combinations of genes and that enables evolution to be innovative. 193 00:20:43,070 --> 00:20:52,520 The same is true of technology, that we will recombine existing technologies in new forms to make new technologies. 194 00:20:52,520 --> 00:20:58,160 In fact, almost every technology you can think of is actually a combination of other technologies. 195 00:20:58,160 --> 00:21:01,940 And often it's just the same technologies combined in different ways. 196 00:21:01,940 --> 00:21:08,510 My favourite example is this thing. It's called the pill camera. It takes a photograph of your insides if you swallow it. 197 00:21:08,510 --> 00:21:15,680 It came about after a conversation over a garden fence between a gastroenterologist and a guided missile designer. 198 00:21:15,680 --> 00:21:27,130 That's the process that I call ideas having sex, because it is a very precise analogy with the way sex works in evolution. 199 00:21:27,130 --> 00:21:32,140 Now, the other lesson that I learnt was that innovation is collaborative. 200 00:21:32,140 --> 00:21:39,220 It is not something that people hardly ever achieve on their own or in secret. 201 00:21:39,220 --> 00:21:45,730 The idea of the brilliant inventor sitting in his ivory tower scratching his head is generally a myth. 202 00:21:45,730 --> 00:21:53,680 The more you look into them, the more it turns out that these stories are just not true, that people were having to build on the work of other people, 203 00:21:53,680 --> 00:21:59,680 but also talk to other people and share ideas with other people in order to be innovative. 204 00:21:59,680 --> 00:22:07,630 Here's a very nice example of that process. This is a photograph of an epic moment in the history of flight. 205 00:22:07,630 --> 00:22:18,160 This is Samuel Langley's attempt in nineteen hundred and three to take off from the roof of a houseboat on the Potomac River near Washington. 206 00:22:18,160 --> 00:22:22,570 In a aeroplane designed from scratch. 207 00:22:22,570 --> 00:22:28,030 Samuel Langley was a brilliant man. He was an astronomer. He was the head of the Smithsonian Institution. 208 00:22:28,030 --> 00:22:32,350 He got an enormous grant from the US government to build an aeroplane. He said, I know how to do it. 209 00:22:32,350 --> 00:22:38,260 He went off in secret and did it. And as you can see, it flopped straight into the water. 210 00:22:38,260 --> 00:22:44,610 It barely went 20 yards. The pilot was wearing a Coke. 211 00:22:44,610 --> 00:22:56,550 Bob to the surface and swim to safety 10 days later on a beach off North Carolina to humble bicycle mechanics from Dayton, 212 00:22:56,550 --> 00:23:01,260 Ohio, managed to achieve what Langley had failed to achieve. 213 00:23:01,260 --> 00:23:08,790 The Orville and Wilbur Wright got an aeroplane into the air and they had done everything right. 214 00:23:08,790 --> 00:23:14,460 That Langley had done wrong. They had collaborated with other people. 215 00:23:14,460 --> 00:23:21,500 They had, particularly a man named Octave Chanute in Chicago, had been an incredibly important source for them. 216 00:23:21,500 --> 00:23:27,810 He was a sort of node in a network who communicated with everyone in the world who was interested in flight. 217 00:23:27,810 --> 00:23:36,690 And he downloaded their brains to find out what they knew about gliders, about kites, about aerofoils files, about wind tunnels, about everything, 218 00:23:36,690 --> 00:23:43,140 and particularly the ideas of a brilliant Australian named Lawrence Hargrave, who had made real progress, 219 00:23:43,140 --> 00:23:50,580 particularly in the development of the box kite, as a way of understanding how to how to do a controlled flight. 220 00:23:50,580 --> 00:23:56,940 And all of this was what the Wright brothers were drawing on. And then they were doing a ton of experiments themselves. 221 00:23:56,940 --> 00:24:00,870 They were not pretending to know the answer from scratch. 222 00:24:00,870 --> 00:24:10,200 They did years and years of experiments with gliders in North Carolina before they ever added an engine to their aeroplane. 223 00:24:10,200 --> 00:24:13,770 So our technology is an incredibly collaborative thing. 224 00:24:13,770 --> 00:24:20,520 When you think about it, there's a famous essay by a man named Leonard Reid written in 1958 called A Pencil, 225 00:24:20,520 --> 00:24:25,050 which is a by a pencil trying to work out how it came into existence. 226 00:24:25,050 --> 00:24:32,400 And the pencil concludes that it was the result of collaboration between millions of people, hundreds of thousands, 227 00:24:32,400 --> 00:24:37,150 at least, because there were people who were cutting down trees to make the wood for the pencil. 228 00:24:37,150 --> 00:24:41,100 But they were drinking coffee and the coffee was drunk by somebody else. 229 00:24:41,100 --> 00:24:43,080 Sorry, it was grown by somebody else. 230 00:24:43,080 --> 00:24:51,390 And and that their wood was taken by somebody to a mill where it was milled and then it was shipped to a factory. 231 00:24:51,390 --> 00:24:56,730 And all these people were involved in this process, hundreds of them, thousands, 232 00:24:56,730 --> 00:25:01,770 maybe hundreds of thousands or even millions, as I say, involved in making one pencil. 233 00:25:01,770 --> 00:25:10,540 And yet the amazing thing was. In all those millions of people, there is not one person who knows how to make a pencil. 234 00:25:10,540 --> 00:25:15,190 The knowledge is not held inside a single head. It's shared between heads. 235 00:25:15,190 --> 00:25:21,250 The person working on the factory floor in the pencil factory doesn't know how to cut down a tree. 236 00:25:21,250 --> 00:25:34,470 And so on. So the reason innovation happens to our species, I reckon, and not to others, except with very few very minor exceptions. 237 00:25:34,470 --> 00:25:39,480 Is because our species is uniquely fascinated by the process of exchange. 238 00:25:39,480 --> 00:25:48,540 It's very, very hard to find other examples in the animal kingdom of animals that want to swap one thing for another and do so regularly. 239 00:25:48,540 --> 00:25:55,290 And yet we're obsessed with it. It comes very naturally to us in all societies at all times. 240 00:25:55,290 --> 00:25:59,730 It has been a feature and it's been part of human life forever, a hundred thousand years. 241 00:25:59,730 --> 00:26:09,960 Adam Smith spotted this. He said no man ever saw a dog make Ferencz deliberate exchange of a bone with another dog. 242 00:26:09,960 --> 00:26:16,680 One of the consequences of the importance of experimentation to reach innovations 243 00:26:16,680 --> 00:26:21,900 is the trial and error features in all the stories about great innovators. 244 00:26:21,900 --> 00:26:27,360 If you ask innovators like Art, pray with the Post-it note or Thomas Edison with the light bulb, how did you do it? 245 00:26:27,360 --> 00:26:32,160 They always say, I just tried and failed. Tried and failed. Tried and failed until I succeeded. 246 00:26:32,160 --> 00:26:38,550 Or other as Adam as Edison said, I've not failed. I've just found 10000 ways that won't work. 247 00:26:38,550 --> 00:26:49,050 Edison tried six thousand different types of plant material before he settled upon Japanese bamboo to make the filament of his first light bulb. 248 00:26:49,050 --> 00:26:56,880 He was searching and searching for something that would have durability that would last a long time when you switch the light bulb. 249 00:26:56,880 --> 00:27:00,600 And he wasn't satisfied until he'd found the perfect thing. 250 00:27:00,600 --> 00:27:05,640 That's an incredibly important feature of innovation and it's one that is often not appreciated. 251 00:27:05,640 --> 00:27:11,130 You don't get the answer right first time you keep trying until you do. 252 00:27:11,130 --> 00:27:18,810 Now, there's another weird thing about the light bulb. 21 different people invented the light bulb independently. 253 00:27:18,810 --> 00:27:26,080 There was Edison in England. There was sworn inward. Russia, there was digging and so on. 254 00:27:26,080 --> 00:27:29,240 And as far as we can make out, none of these people communicate with each other. 255 00:27:29,240 --> 00:27:33,490 We all came up with the idea independently and this is a very common phenomenon. 256 00:27:33,490 --> 00:27:42,610 It's called simultaneous. Kevin Kelly writes about it very entertainingly in his book, What Technology Wants and. 257 00:27:42,610 --> 00:27:46,060 At first sight, it seems rather weird, 258 00:27:46,060 --> 00:27:54,580 almost as if there is a deity reaching down from the sky and implanting the idea of the light bulb in 21 different minds at the same time. 259 00:27:54,580 --> 00:28:01,030 But when you think about it, it's much more likely that what's going on is that the contributing technologies of electricity, 260 00:28:01,030 --> 00:28:08,540 of glass, of vacuums, et cetera, have just reached the point where it's inevitable someone will see this, 261 00:28:08,540 --> 00:28:15,100 that there's something wholly inexorable about innovation in certain fields once it gets to a certain point. 262 00:28:15,100 --> 00:28:20,350 You can't stop it even if you want to. This is probably more easy to understand. 263 00:28:20,350 --> 00:28:28,960 If you think about a more recent example, the search engine is probably the most useful invention of my lifetime. 264 00:28:28,960 --> 00:28:33,430 I use it pretty well every day. It was invented in the early 1990s. 265 00:28:33,430 --> 00:28:41,140 Soon after the Internet, and in retrospect, it's kind of inevitable that it would get invented then, 266 00:28:41,140 --> 00:28:47,530 because if Sergei Brin had never met Larry Page and founded Google, we would still have search engines. 267 00:28:47,530 --> 00:28:52,240 There were lots around before Google and there were lots of rivals. 268 00:28:52,240 --> 00:28:59,290 And they all came up with search engines because it was sort of obvious that 269 00:28:59,290 --> 00:29:04,700 people were going to want to search the Internet to find what they wanted. 270 00:29:04,700 --> 00:29:15,420 So it didn't matter if by chance, Larry Page had not met Sergei Brin, we would still have search engines today. 271 00:29:15,420 --> 00:29:22,780 But if you go back to the late, late 1980s and you read the literature about the Internet. 272 00:29:22,780 --> 00:29:30,560 The nascent Internet, nobody sees search engines coming, at least very few people, and they only very sketchily, 273 00:29:30,560 --> 00:29:34,910 and indeed, the people who invented search engines didn't really understand what they were doing. 274 00:29:34,910 --> 00:29:38,330 Page and Brin didn't think they were inventing a search engine. 275 00:29:38,330 --> 00:29:46,670 They thought they were cataloguing the Internet. At first. So there's something strangely asymmetric about innovation. 276 00:29:46,670 --> 00:29:56,420 It's fantastically obvious that it would happen when and where it does. When you look backwards, but it's not at all obvious when you look forwards. 277 00:29:56,420 --> 00:30:02,630 So innovation is inexorable, but it's also unpredictable. 278 00:30:02,630 --> 00:30:10,120 To illustrate this, let me just tell you the story of the 20th century in terms of two particular technologies. 279 00:30:10,120 --> 00:30:19,700 In the first half of the 20th century, there was a ferment of innovation in transport and almost no innovation in communication and computing. 280 00:30:19,700 --> 00:30:23,930 There were cars that were planes, there were helicopters that were rockets. 281 00:30:23,930 --> 00:30:33,780 Space travel, those you know, all this kind of stuff began in roughly the first half of the 20th, 20th century. 282 00:30:33,780 --> 00:30:42,570 Whereas the telephone predates the 20th century and it was still around in 1950 in very similar form. 283 00:30:42,570 --> 00:30:48,120 So no wonder in the 1950s, future ologists are obsessed with transport. 284 00:30:48,120 --> 00:30:53,670 They go on and on about how in the future we're going to have flying cars and personal 285 00:30:53,670 --> 00:30:58,200 jet packs and routine space travel and supersonic airliners and all that kind of thing. 286 00:30:58,200 --> 00:31:05,280 None of which happened because in the second half of the 20th century, almost nothing came along in the way of transport. 287 00:31:05,280 --> 00:31:12,110 I mean, we flew seven full sevens for 50 years without changing TEAC design. 288 00:31:12,110 --> 00:31:18,280 Whereas there was a ferment of innovation in computing and communication. 289 00:31:18,280 --> 00:31:26,190 Now, I don't believe you could have predicted that switch. And indeed, I don't think we fully understand why it happened in some sense. 290 00:31:26,190 --> 00:31:31,190 Transport hit a brick wall. It hit diminishing returns. 291 00:31:31,190 --> 00:31:36,600 And by the way, it implies that computing and communication might do the same at some point in the near future, 292 00:31:36,600 --> 00:31:45,280 the next 50 years might not be about computing and communication to the degree we expect it will be today. 293 00:31:45,280 --> 00:31:52,130 Here's an image from the year I was born, 1958, of what they think the future is going to be like in the year 2000, 294 00:31:52,130 --> 00:31:54,520 mailmen are going to be delivering ordinary mail. 295 00:31:54,520 --> 00:32:00,820 There's no such thing as e-mail, but they're going to have rockets strapped to their backs so they can jump from house to house. 296 00:32:00,820 --> 00:32:05,530 Didn't quite turn out like that. Not everybody gets prediction wrong. 297 00:32:05,530 --> 00:32:15,990 Here's a picture from Germany in the 1930s showing us doing pretty well exactly what we're doing right now. 298 00:32:15,990 --> 00:32:20,660 But one of the things about the unpredictability of innovation is that it leads some very, 299 00:32:20,660 --> 00:32:27,040 very clever people to say some very, very stupid things about the future. And I'm sorry, but I'm going to embarrass four of them. 300 00:32:27,040 --> 00:32:29,180 And his brother, the man who split the atom, 301 00:32:29,180 --> 00:32:36,290 said in 1933 that anyone who expects a source of power from the transformation of the atom is talking moonshine. 302 00:32:36,290 --> 00:32:41,570 Ken Olsen, chairman of the company that made the mini computer and was one of the most successful companies, 303 00:32:41,570 --> 00:32:50,350 computer companies of the 1970s making the smallest computers, said there's no reason I want a computer in there at home. 304 00:32:50,350 --> 00:32:56,610 Paul Krugman, Nobel prise winning economist, said in 1998, by 2005 or so, 305 00:32:56,610 --> 00:33:02,020 it will become clear that the Internet's impact on the economy will be no greater than the fax machines. 306 00:33:02,020 --> 00:33:09,730 And Steve Ballmer, chief executive, Microsoft 2007, said there's no chance the iPhone is going to get market share in this market. 307 00:33:09,730 --> 00:33:16,620 No chance. They are being wrong footed by the unpredictability of innovation. 308 00:33:16,620 --> 00:33:27,730 These people. And I think the main reason and it comes back to disruption, to gradual trends suddenly turning sudden. 309 00:33:27,730 --> 00:33:36,370 Is because innovation is non-linear. It doesn't progress in a straight line from one technology to the. 310 00:33:36,370 --> 00:33:40,540 Roy Emara is the person who said the cleverest thing about this. 311 00:33:40,540 --> 00:33:49,570 I think he was a computer scientist in Silicon Valley in the 1960s and he said we underestimate the impact of a new technology in the long run. 312 00:33:49,570 --> 00:33:55,570 But we overestimate it in the short run. It's more like that. 313 00:33:55,570 --> 00:34:01,680 Nothing much happens for some years, and then suddenly the world has changed. 314 00:34:01,680 --> 00:34:07,110 And it's worth thinking about where today's technology sit on that curve. 315 00:34:07,110 --> 00:34:10,620 I mean, the Internet isn't. I think we can all agree not disappointing. 316 00:34:10,620 --> 00:34:19,470 Whatever Paul Krugman might have said it is, it is outperforming our expectations at this stage. 317 00:34:19,470 --> 00:34:28,020 Genomics has been disappointing. Bill Clinton in 2000, when the first human genome was sequenced, talked about the imminent curing of cancer. 318 00:34:28,020 --> 00:34:35,760 We haven't achieved nearly as much as we would like with genomics, and yet we are suddenly seeing some pretty dramatic breakthroughs at the moment. 319 00:34:35,760 --> 00:34:40,950 Think again of the messenger RNA vaccines, for example. I. 320 00:34:40,950 --> 00:34:42,720 Well, Michael might put me right here, 321 00:34:42,720 --> 00:34:49,080 but I suspect we aren't quite through the disappointing phase with some of the technologies we're excited about yet. 322 00:34:49,080 --> 00:34:53,760 The driverless cars may prove a little more difficult than we think before. 323 00:34:53,760 --> 00:35:00,450 Indeed, they do change the world at some point. And as for block chain, I believe that it's hardly begun to disappoint us. 324 00:35:00,450 --> 00:35:05,280 But that doesn't mean we should write it off in the long run. 325 00:35:05,280 --> 00:35:10,600 Now, there was a very important point that the merged from the stories that I told in my book, 326 00:35:10,600 --> 00:35:16,120 and that is that whereas we think in terms of the linear model of science and technology, 327 00:35:16,120 --> 00:35:23,330 that science leads to technology, which leads to applications, which leads to business. 328 00:35:23,330 --> 00:35:32,600 In fact, it's very rarely as simple as that, because technology is often the seed of science as well as the fruit and can sometimes be both. 329 00:35:32,600 --> 00:35:39,440 It can sometimes come out of science, but then lead to new scientific breakthroughs is quite a nice example. 330 00:35:39,440 --> 00:35:41,180 This man is called Philip Horvath. 331 00:35:41,180 --> 00:35:54,950 He worked for a yoghurt making company in France and the Nobel Prise that was won this year by two brilliant scientists, 332 00:35:54,950 --> 00:36:03,400 Jennifer Doudna and Emmanuelle Charpentier, for the invention of Crispell gene editing. 333 00:36:03,400 --> 00:36:10,070 Looks at first sight like a purely academic discovery made in universities. 334 00:36:10,070 --> 00:36:14,500 But actually, where did they find out about crisper? 335 00:36:14,500 --> 00:36:23,740 Where did they find out about these strange palindromic sequences in genomes of bacteria that could be repurposed to editing genes? 336 00:36:23,740 --> 00:36:28,300 They found out about them from Felipe Horvath in the yoghurt industry. 337 00:36:28,300 --> 00:36:33,100 And why was the yoghurt industry studying bacteria and their genes? 338 00:36:33,100 --> 00:36:38,800 Because the yoghurt industry depends on bacteria and sometimes they get viral infections. 339 00:36:38,800 --> 00:36:43,510 So they need to understand the immune system of the bacterium and the immune system of the bacterium 340 00:36:43,510 --> 00:36:51,130 turns out to be to carry libraries of virus genomes so they can be recognised by the defensive system, 341 00:36:51,130 --> 00:36:58,080 which chops up the DNA of the viruses. And this is what we have repurposed for gene editing. 342 00:36:58,080 --> 00:37:04,250 So in a sense, it comes out of industry and goes into academia rather than the other way round. 343 00:37:04,250 --> 00:37:10,160 Now, you take the story further back to Francisco. He Mahiga in Al Jazeera said it's back in university again. 344 00:37:10,160 --> 00:37:22,870 So these tech technologies, these innovations can start in industry or they can start in academia and they can go in both directions. 345 00:37:22,870 --> 00:37:31,070 An even more dramatic example when you think about it, is vaccination itself or rather inoculation as it was when it first started. 346 00:37:31,070 --> 00:37:37,940 Which was brought to Britain and thereby to Western Europe by a rather remarkable woman, 347 00:37:37,940 --> 00:37:49,100 literary woman called Lady Mary Wortley Montagu, who was in that she was the wife of the ambassador in Constantinople. 348 00:37:49,100 --> 00:37:58,340 And she then picked up while there this habit of inoculating people against smallpox, children against smallpox. 349 00:37:58,340 --> 00:38:03,620 She brought it back to England, persuaded the Prince Wales and others to try it and did to our own children. 350 00:38:03,620 --> 00:38:11,570 And despite being extremely unpopular with the medical profession, it caught on and it saved a lot of lives about the same time. 351 00:38:11,570 --> 00:38:21,200 The same thing happened in North America because of a preacher named Cotton Mather who had a 352 00:38:21,200 --> 00:38:29,510 slave called Uneasiness and the slave brought with him from Africa the concept of inoculation. 353 00:38:29,510 --> 00:38:39,830 Cotton mother gave it as Abdelal Boylston, a medick who inoculated half the students at Harvard when a smallpox epidemic was 354 00:38:39,830 --> 00:38:46,250 threatened and had to lock himself in a cupboard for more than a week to escape the mob, 355 00:38:46,250 --> 00:38:53,380 which wanted to kill him for this dangerous experiment. But it succeeded and it proved it right. 356 00:38:53,380 --> 00:38:57,790 The point is that these people have a humble slave. 357 00:38:57,790 --> 00:39:01,590 A woman with no scientific education. 358 00:39:01,590 --> 00:39:11,220 Invented this, and it was used for hundreds of years without us having the slightest scientific idea of white work. 359 00:39:11,220 --> 00:39:20,220 It wasn't till well after Pasteur that we really understood why inoculation or vaccination works. 360 00:39:20,220 --> 00:39:26,570 So technology can precede science by quite a long time. 361 00:39:26,570 --> 00:39:37,130 Another theme that emerged is the common fear that innovation will destroy jobs from the Luddites in the 18th century to today. 362 00:39:37,130 --> 00:39:42,950 It's been there's been repeated waves of worry that automation is going to steal jobs. 363 00:39:42,950 --> 00:39:45,470 It doesn't happen. It won't happen. 364 00:39:45,470 --> 00:39:59,210 And the reason is because it creates new kinds of work and because it although it does save us time, it doesn't replace work. 365 00:39:59,210 --> 00:40:08,130 If you. And trying to explain what a software engineer is. 366 00:40:08,130 --> 00:40:13,290 Innovation also enables us to do more with less thanks to innovations in agriculture. 367 00:40:13,290 --> 00:40:19,500 We grow 68 percent. We use 68 percent less land to produce a given amount of food. 368 00:40:19,500 --> 00:40:24,300 We use 13 percent as much aluminium and a drinks cannas. We did when they were first invented. 369 00:40:24,300 --> 00:40:31,660 LCD lights use less than a quarter as much electricity to produce the same amount of light as they did. 370 00:40:31,660 --> 00:40:38,940 Now, one of the consequences of this is that innovation enables us to use fewer resources. 371 00:40:38,940 --> 00:40:51,300 And that means that innovation is potentially infinite because we won't run out of resources if we are able to use this through innovation. 372 00:40:51,300 --> 00:40:57,780 That is to say, innovation and economic growth can simply ask us to do more with less. 373 00:40:57,780 --> 00:41:06,400 And that will enable us to keep innovating pretty well indefinitely into the future. 374 00:41:06,400 --> 00:41:10,530 I also came up with the conclusion that a bad and innovation, 375 00:41:10,530 --> 00:41:19,150 great big employers that are huge free trade zones like the Ottoman Empire, for example, was very resistant to innovation. 376 00:41:19,150 --> 00:41:26,770 Something similar in the Ming Empire in China. Even the Roman Empire wasn't actually very innovative compared with the dark 377 00:41:26,770 --> 00:41:32,040 edges that came after or compared with the Greek city states that came before. 378 00:41:32,040 --> 00:41:41,250 And why? Because attention, essentially their very top down bureaucratic places where people at the centre tell people what they should do. 379 00:41:41,250 --> 00:41:45,360 They don't allow for the freedom and experimentation to trial and error. 380 00:41:45,360 --> 00:41:50,160 That is so crucial to innovation. Something similar happens in big companies. 381 00:41:50,160 --> 00:41:55,500 Kodak was blown away by digital photography. 382 00:41:55,500 --> 00:42:02,640 Nokia became the most spectacular success story of the mobile phone industry and hugely innovative company. 383 00:42:02,640 --> 00:42:09,010 I was then blown away by the switch in mobiles from voice to data. 384 00:42:09,010 --> 00:42:14,040 Big companies just become too invested in existing technologies to bureaucratic 385 00:42:14,040 --> 00:42:18,360 and slow in their decision making and too intolerant of experimentation. 386 00:42:18,360 --> 00:42:29,520 And maverick ideas. We think we're all in favour of innovation, but actually there is huge resistance to innovation. 387 00:42:29,520 --> 00:42:34,920 It comes from big companies that try to put barriers in the way of competitors. 388 00:42:34,920 --> 00:42:43,660 It comes from pressure groups that play on our conservatism and our caution about the future. 389 00:42:43,660 --> 00:42:52,770 And it comes from our interest in regulating, which often leads to barriers to innovation. 390 00:42:52,770 --> 00:42:58,830 He's a very nice example of how. Hope stick in the mud. 391 00:42:58,830 --> 00:43:10,920 We are sometimes about new stuff. Coffee. Coffee was an innovation in the 16th century in all of Europe where wherever it appeared, it was banned. 392 00:43:10,920 --> 00:43:16,470 It was made illegal. It was forbidden. It was driven out. 393 00:43:16,470 --> 00:43:23,230 There was coffeehouses, but closed down coffee pots were were destroyed. 394 00:43:23,230 --> 00:43:29,040 It's an it's an extraordinary story. And the attitude was very similar to the attitude. 395 00:43:29,040 --> 00:43:35,430 Genetically modified crops. Today in Europe, frankly. This stuff is dangerous. 396 00:43:35,430 --> 00:43:40,980 We don't know enough about it. The precautionary principle says we should not have it. 397 00:43:40,980 --> 00:43:49,290 Now, where was this opposition coming from? A lot of it was coming from the beer and wine industry, which in one case in Marseilles, 398 00:43:49,290 --> 00:43:55,260 actually paid for a university to produce a pamphlet saying that coffee was bad for you. 399 00:43:55,260 --> 00:44:01,050 So science could be bought and paid for in those days, as it can be. 400 00:44:01,050 --> 00:44:16,740 Occasionally today. But the other source of opposition to coffee was from rulers because rulers didn't like the fact that people met in coffee houses. 401 00:44:16,740 --> 00:44:27,050 And gossiped. And when they go sit in a coffee house gossiping, they might talk about whether the king is doing a good job or not. 402 00:44:27,050 --> 00:44:32,040 And they might even decide that he's not. And this is not to be encouraged. 403 00:44:32,040 --> 00:44:39,420 Basically, coffeehouses are the source of fake news. Here is King Charles, the second banning coffeehouses, the source. 404 00:44:39,420 --> 00:44:48,580 By the way, of the Royal Society. It was a coffeehouse here in Oxford. But here he is banning coffee in the 60s, 70s. 405 00:44:48,580 --> 00:44:51,030 As for coffee, tea and chocolate, I know you could they do. 406 00:44:51,030 --> 00:44:57,790 Only the places where they are sold are convenient for purses, peasants to meet in, sit half day and discourse with all companies that come in. 407 00:44:57,790 --> 00:45:03,520 Of state matters. Talking of news and broaching of lies are reigning the judgements and discretion of their governors. 408 00:45:03,520 --> 00:45:08,290 Censoring all their actions and insinuating into the is that the people are prejudice against them, 409 00:45:08,290 --> 00:45:12,880 extolling and magnifying their own past knowledge and wisdom and blah, blah, blah. 410 00:45:12,880 --> 00:45:19,240 You get the point. He didn't like fake news. Fortunately, it proved impossible to ban coffee. 411 00:45:19,240 --> 00:45:26,010 It just kept coming back. Now, if, as I argue. 412 00:45:26,010 --> 00:45:31,380 The great theme of innovation is freedom. The freedom to experiment, the freedom to make mistakes. 413 00:45:31,380 --> 00:45:36,360 The freedom to change direction. The freedom to to fail and start again. 414 00:45:36,360 --> 00:45:43,980 The freedom as the consumer to express a preference amongst different competing innovations, particularly. 415 00:45:43,980 --> 00:45:50,010 How do I explain China being one of the innovative parts of the world today? 416 00:45:50,010 --> 00:45:57,900 Is that not because actually China is innovative, because it has a policy, a top down policy of innovation? 417 00:45:57,900 --> 00:46:06,030 I don't believe that's the right way to read China at all. I think what happened after the fall of Mao Tse tung in 1970. 418 00:46:06,030 --> 00:46:16,040 A pin was that China became a very free place economically, even while it was a very unfair. 419 00:46:16,040 --> 00:46:22,580 I'm not sure that a new political party, but if you invented a new widget and you just joined us, 420 00:46:22,580 --> 00:46:30,680 you faced many that you are actually bureaucratic rules and delays than you did in the West. 421 00:46:30,680 --> 00:46:37,840 You actually could get up and running with your new factory and you selling a new device much quicker than in the West. 422 00:46:37,840 --> 00:46:43,870 And that has been true for most of the last four decades. Branding. 423 00:46:43,870 --> 00:46:53,730 I believe the Xi Jingping regime is now economically illiberal as well as politically, and that we will see innovation stifled in China in the future. 424 00:46:53,730 --> 00:46:57,620 Something similar happened in China a very long time ago. 425 00:46:57,620 --> 00:47:11,470 Around a thousand years ago in the song Dynasty, China was an incredibly innovative place with the invention of gunpowder, compasses. 426 00:47:11,470 --> 00:47:15,910 Printing money. The printing press. All these kind of things. 427 00:47:15,910 --> 00:47:27,450 It was it was a time of rich innovation. And the reason was because that dynasty ran a very decentralised empire. 428 00:47:27,450 --> 00:47:32,430 Essentially, it was a series of city states that were self-governing, that were run by merchants. 429 00:47:32,430 --> 00:47:37,170 They could do what they want. They could trade. They could experiment. They could innovate. 430 00:47:37,170 --> 00:47:44,040 Then after Ramon Mongul interregnum, along comes the Ming Empire and says no, from now on, we are going to tell you what you can do from the centre. 431 00:47:44,040 --> 00:47:50,250 The capital is going to be full of mandarins who are going to organise the economy. They banned foreign trade. 432 00:47:50,250 --> 00:47:54,720 They told merchants that they could not leave their home town without a permit. 433 00:47:54,720 --> 00:48:02,970 They told them that they must send a memo to a Mandarin every month describing how much stock they 434 00:48:02,970 --> 00:48:10,440 had in their warehouse so that the mandarins could calculate how to feed the people of China. 435 00:48:10,440 --> 00:48:18,200 The result was disaster. The result was the total impoverishment of the Chinese nation for many centuries. 436 00:48:18,200 --> 00:48:27,360 So China does teach the lesson that freedom is important, but innovation. 437 00:48:27,360 --> 00:48:32,310 This is what innovation has done to the human race. This is GDP per capita. 438 00:48:32,310 --> 00:48:39,490 Since sixteen hundred, the most extraordinary hockey stick of a graph you will ever see. 439 00:48:39,490 --> 00:48:46,620 Data visualisation by our world in data. Max here in Oxford and. 440 00:48:46,620 --> 00:48:53,380 At every stage in. Intellectual people have said, by the way, this can't carry on. 441 00:48:53,380 --> 00:49:00,300 It's about to stop. We're about to hit the buffers. Pessimism has always been a bestseller. 442 00:49:00,300 --> 00:49:10,710 Throughout this period, just one example, Thomas Babington, Macaulay Macaulay, writing in 1830 reviewing a pessimistic book by Robert Subi, 443 00:49:10,710 --> 00:49:16,020 says, We cannot absolutely prove that those are in error, who say society's reached a turning point. 444 00:49:16,020 --> 00:49:20,260 We have seen our best days, but so said all who came before us. 445 00:49:20,260 --> 00:49:25,890 And with just as much apparent reason or more principle is that with nothing but improvement behind US rhetoric, 446 00:49:25,890 --> 00:49:36,910 expect nothing but deterioration before us. So actually, because of innovation, we face a bright future. 447 00:49:36,910 --> 00:49:45,380 Thank you very much. I will now. Stopped sharing my slides. 448 00:49:45,380 --> 00:49:50,210 OK, so are we. I enjoyed that lecture very, very much. 449 00:49:50,210 --> 00:49:55,160 We are struggling at the moment with the connexion to match for a Q and A, 450 00:49:55,160 --> 00:50:00,920 we know he's only got a few minutes, so it could conceivably be that he's been pulled out. 451 00:50:00,920 --> 00:50:09,470 We literally on the case. Now, if you go to the Q and A bar, you can enter some questions. 452 00:50:09,470 --> 00:50:15,980 We've already got one question in from Jeremy Gibbons. I've read it out. Jeremy says, You observed that innovation is serendipitous. 453 00:50:15,980 --> 00:50:19,820 What do you think about the incentives placed on academics by national research funders such 454 00:50:19,820 --> 00:50:24,200 as you can go awry towards planned innovation and research projects rather than serendipity? 455 00:50:24,200 --> 00:50:35,900 Wouldn't we be better with reliable, modest funding for following curiosity rather than a lottery for fewer targeted grants? 456 00:50:35,900 --> 00:50:40,630 Some interesting observations about artificial intelligence. And it would be fascinating. 457 00:50:40,630 --> 00:50:49,430 We could have an entire we could have an entire discussion about artificial intelligence are suspect and where that's going. 458 00:50:49,430 --> 00:50:55,100 We've got another question. Impacts of trade, limitations between countries on innovation. 459 00:50:55,100 --> 00:51:13,080 That's published on. 460 00:51:13,080 --> 00:51:19,770 I believe the vaccination map mentioned two referred to rather than variation, exposure to people to small amounts of the true smallpox virus. 461 00:51:19,770 --> 00:51:36,130 It wasn't quite the vaccination, but the somewhat truly dangerous variation. 462 00:51:36,130 --> 00:51:58,900 In your book, you're quite dismissive about the role of academia and government in promulgating innovation. 463 00:51:58,900 --> 00:52:03,600 Do you think any apparent inevitability of particular innovations when we look back is an illusion, 464 00:52:03,600 --> 00:52:09,300 where we just tell us after a story that something was inevitable to make sense of history in hindsight? 465 00:52:09,300 --> 00:52:12,130 I personally think there's a good deal of truth to that. 466 00:52:12,130 --> 00:52:23,170 I think we do tend to create stories to explain things in a way that doesn't necessarily reflect what actually happened on the ground. 467 00:52:23,170 --> 00:52:27,520 I suspect that innovation cannot be free for all, especially when it comes to medicine or weaponry or DNA data. 468 00:52:27,520 --> 00:52:48,370 What goals should future governments play? While we're waiting, let me just do a shout out again to Oxford Asset Management, 469 00:52:48,370 --> 00:52:53,770 our sponsors, but the tremendous over the last few years and as I said at the beginning, 470 00:52:53,770 --> 00:53:01,120 we've been able to bring in speakers that we simply wouldn't have been able to previously and to greatly expand the range of these these lectures. 471 00:53:01,120 --> 00:53:08,630 So we really are very, very grateful. And as I said earlier, Oxfam are hiring and they would love to hear from you if you're interested in finance, 472 00:53:08,630 --> 00:53:17,570 machine learning, artificial intelligence generally. And you could easily find them online. 473 00:53:17,570 --> 00:53:23,600 Okay, I'm afraid bad news. So it seems we've lost maths East has to get on at this point now to another engagement. 474 00:53:23,600 --> 00:53:28,310 That's a tremendous pity because I thought that was a really, really wonderful lecture. 475 00:53:28,310 --> 00:53:32,540 And we've got some great questions. So I am very sorry for that. 476 00:53:32,540 --> 00:53:36,140 Everybody, tech glitches, these things happen, it seems. 477 00:53:36,140 --> 00:53:42,650 Matt was having some connexion problems with teams and then just timed out and had to get off to another engagement. 478 00:53:42,650 --> 00:53:48,740 Well, I'm very, very grateful for Matt for a really, really thought provoking lecture. 479 00:53:48,740 --> 00:53:57,290 Can I suggest Matt is on Twitter, very active on Twitter. And perhaps one way forward might be to post some of the questions on Twitter. 480 00:53:57,290 --> 00:54:00,440 But I say I thought that was a genuinely fascinating lecture. 481 00:54:00,440 --> 00:54:04,730 Something a bit different, but something very, very thought provoking and something very, 482 00:54:04,730 --> 00:54:13,790 very relevant for a Department of computer science for which innovation is is is absolutely central to what we do now. 483 00:54:13,790 --> 00:54:16,190 So thank you, everybody. Thank you again to our sponsors. 484 00:54:16,190 --> 00:54:22,700 Apologies that we weren't able to deliver the Q&A session, but we were able to deliver, I think, a wonderful lecture. 485 00:54:22,700 --> 00:54:28,880 We will not be back to life straight. He lectures next term and I suspect we will not be back in Trinity term, 486 00:54:28,880 --> 00:54:33,290 even though I think the world will be looking at a lot better by Trinity term. 487 00:54:33,290 --> 00:54:40,910 In no small part, thanks, of course, to the wonderful work of our colleagues at Oxford and the development of the Oxford vaccine. 488 00:54:40,910 --> 00:54:43,370 But we will be having Straight's lectures. 489 00:54:43,370 --> 00:54:48,710 Clearly, we will have learnt from the experience today and we'll be able to deliver a much more polished Q and A, 490 00:54:48,710 --> 00:54:55,250 and I hope that by then I will have learnt to finally share my slides when I do my introduction. 491 00:54:55,250 --> 00:55:02,676 So thank you everybody for joining and we hope to see you again in Hilary to thank you.