Carl Benedikt Frey: "The Technology Trap" | Talks at Google

Thanks. Very much it's a real pleasure to be here and thank, you all for coming despite the, nice. Weather I was slightly. Tempted, to sit down on the terrace myself so it's really nice to see that so many of you and are, here back. In 2013, Michael, husband and I published, a paper in which we estimated, roughly 47% of, jobs are at, risk of automation. And a, question, that we got quite frequently, since then is that is it something there, are something different about this time right because we've been through, periods, of, technological. Change, before. And and, what I would like to do today is to take you through some. Of the history, about. Mechanization. And jobs. And because. One thing that I find quite extraordinary when researching, this book is that technology. Has progressed, enormous. Ly over, the past 200 years but. The debate surrounding. Its effects. Has, not and, as. Many of you will have noted, we are living in a period of automation. Anxiety. Where, few people feel. Enthusiastic. About the tornado that's, coming, for the office and in fact a majority of Americans. Now think. That. Governments, should impose, restrictions. On, how, many machines, businesses. Can install, an implement, in production. And this. Seems puzzling from, an economic, historian point. Of view because if you take a really long view, and what. You see is that economic, growth looks, like this hockey stick right it was slow stagnant. For millennia. And only, took off in extraordinary, fashion, around. 1800. And the standard, story, behind. This, is that this, was roughly the time when, the mechanized, factory, arrived, that with its extreme, divisions, of Labor and the. Implementation. Of machinery, in production, allowed. Us to produce more, with. Fewer people and as, a result of that we. Are roughly, 40. Times richer, today. Adjusted. For, inflation than. We were at in, 1750. At the dawn of the first, Industrial. Revolution and. Needless, to say that.

If. Anything, understates. The transformation, that has taken place because the consumer. Baskets, that you could buy, with. That income today is, so, much more diverse than, it was in. 1750. Right people. Back then could only look at the lives of the, wealthy, and envied, who had servants, to do the most tedious things, for them today, we all have access to the electric, servant, in terms of dishwashers. Washing machines, vacuum. Cleaners, and so on that relieve us of a lot of tedious work not. To mention other minor inventions, like the automobile and. Antibiotics. And if, that isn't evidence. Of progress enough, and. Consider, the fact that. Producing. Those goods and earning. Those higher incomes, is much, more comfortable, today as well back. In 1900. A lot of people still work in, coal mining. Explosions. And cave-ins were part of everyday working life lung, disease came, as part, of the work package, and today. Most of us work in, air-conditioned. Offices. I was, just told, that you have a massage, room next door and the gym that you can go to during. The lunch break if you like so it's quite extraordinary, how. Much, working. Conditions, have improved and, in, large part, because, of, Technology, right even, occupations. That still, exist. Today have. Been transformed. Beyond, recognition back. In 1900. A farmer, would have walked the fields with nothing more than animal, power and and. Today that, same worker can sit in an, air-conditioned. Tracting, a tractor. And listen. To the music of his or her, choice. So. There's, no, doubt that, a lot of progress has been made I'm here, to tell you that unfortunately that, is just half, of the. Story. The Industrial, Revolution. Created. The foundations, for the modern world will live in today but, getting there involved. Painful, transition, in. 1844. Benjamin. Disraeli before. It became Prime Minister of Britain published. A novel, called, Corning speed in which, one character, remarks, that icy cities. People, with. Machines, certainly. Manchester. Must, be the most wonderful, place of modern. Times the.

Same Year Frederick, Engels published. His conditions. On the working, classes in, England. Which, was written during, a stay in, precisely. Manchester. And angles. Needless to say had a very different, take on the matter he argued, that machinery. Only. Served to downgrade people. To. Deprive, them of the jobs and, incomes. And, and. As a result of that he, argued that, it was not in the interest of, the working classes, for. Mechanization. To, progress, now. Frederick. Angus was clearly, wrong about. The. Future but. As the economic, historian Bob Allen has pointed out he, was actually right, about, the past, because, for seven, decades, even. As the British economy took off, wages. Were stagnant or. Even, falling at the bottom end of the income distribution the. Wage data for this period is admittedly. Not that great but even if you look at other sources, of data like. Consumption. You, see that spending on non-essentials, for example, declined, during, this period and if, you look at biological. Indicators. Of well-being like, Heights you, find that the courts Boone in, 1750. Was actually caught taller than, the courts born in. 1850. So, it seems that this had also, an impact, on people's, and, incomes. The nutrition, and land. Life, expectancy. More. Broadly. And. The, reason for this was. In large part the, mechanization, of Industry the fact that machines, replaced, the middle-income artisan. Jobs with. Low paid jobs often. Performed, by children, in factories. In fact, early, spinning, machines were, specifically. Designed to, be, tended. By, children, it, was only after, 1840. When steam power became more pervasive in, production. That the adult population, regained. The comparative, advantage, and in. Production, but, it took time for people to learn new skills it, took time for, production. To be standardized, across factories, so, people could. Credibly, threaten to, leave their job for another factory, job which. Increased. Their bargaining, power labor. Unions of course played a role as well but that was actually much later so. The upsurge, in wages, during the later stages of the Industrial Revolution as argue in the book is best, explained. By the industrial. Industrialization. Process itself. But, getting there took, a long, time. Now. One.

Puzzle. Too, many economic, historians, has been why, would people have voluntarily. Agreed. To, participate, in. The industrialization. Process if it. Reduced. Their, utility. The. Simple, answer, is that, they. Didn't, a petition. To Parliament to. Block the introduction, of, labor. Replacing, technologies, and they, frequently, rioted. Against. The mechanistic, mechanized. Factory, some. Of you will have heard about the Luddite riots but, they were only part of a long wave, of riots that, spread, across. Continental. Europe, Britain, and even. China. And and. How did the British government, respond, to those riots, well. Not, to. Unfrequently, and they. Sent up true, against, the rioters and in fact the army, that was sent against the Luddites was, larger, than the army, that, Wellington took, against, Napoleon, in the Peninsular, war of. 1808. So. I think it's important. To remember that. A, lot. Of revolutionary. Technologies, also, spread, a lot of political, revolutionaries. Along. The way what. Began, with the introduction, of the, first machines, in factories, and ended, with, the construction, of the railroads also ended, with, the publication, of the, communist manifesto. Now. I'm, not here to predict, the socialist. Revolution, but. I do know that levels, of income inequality. Have. Increased. Rapidly. In, recent, decades and have been approaching, levels. Not, seen since. The. Industrial, Revolution of, the. 18th and 19th century. And, needless. To say what's. Driving this, is not spinning machines, since steam power but, there's a new technology, it's. Essentially. Computerization. And the. First electronic, computer was, developed at the University of Pennsylvania in. 1947. But, it was probably. Too. Large to, be fitted, into. This room and as a result of that it had virtually no impact on, the labor market and productivity, growth it, was only around, 1980s. With the introduction, of the personal computer that a. Companies. Were able to restructure. Supply. Chains to take advantage, of cheap. Labor in countries. Like China, and B, that. Companies. Became able to, automate, a lot of routine, rule-based. Activities. And that. Have disappeared, in offices. And factories, and. This, automation, has been very good for summers right, so most. People in this room we are able to work. More productively, with the help of computers, and we can reach a global marketplace. To, export. Our ideas but. It hasn't been that great, for everyone and if you look at primates, men with, no more than high school degree, in the, United States they. Wages, have actually fallen, for three consecutive, decades, they. Have been worse off in, the labor market, due. To in. Large part. Automation. Now. We, have already seen, a backlash. Against. Globalization, but. Automation. And globalization, have. Had a very similar. Effects. On the, unskilled, and their. Communities. When. The robots are is also, where many, of America's. Problems. Are and a. Variety of studies, have shown that when, jobs dry, up you, get a lot of social problems in those communities, such as rising cry air crime faltering. Marriage, rates and and, you even see what, economists, and a case and Angus Deaton have called the deaths of despair, a lot.

Of People dying prematurely. Because. Of alcohol, related causes liver, disease and and. Suicide. And and. Not. Too, surprisingly, and these are also the. Electoral. Districts. That, are most likely to opt for radical, political, change, our. Study, shows, that. Much. Of the 2016. Election. And, actually. Played, out in. Electoral. Districts, which adopted. Robots, very, extensively, and if you want to explain why three key. Swing, states like, Michigan Wisconsin. And. Pennsylvania. Reverted. For the Democratic, candidate every, single election since, 1992. All. Of the sudden and ended. Up voting for double donald trump automation. Is definitely, part, of the story, now, the. Worrying part is, that we have seen nothing. Yet, because, past automation. Was, essentially. Based, on, top-down. Computer. Programming, with, the person, specifying. What the, technology, should do at every. Key in contingency, we. Are now in an era of bottom-up. Machine. Learning, where. New, technologies can. Essentially, infer, the rules of the game, themselves. Through. A. Data. Tapping. Into our experience. And trial. And error and. At some risk of, oversimplification. This, is what driving, everything, from, recent developments, in autonomous, driving. To. Google, Translate. Now. When, I make, this presentation I'm sorry to say some people sometimes point out that you know Google Translate, is not, perfect. But. At. The same time it's important, to remember that every, revolution. In technology, began. With imperfect, technology. The, early steam engines, were merely used, to drain coal mines and even. That they, didn't do particularly, well and we seen exponential. Improvements. In many, of these technologies, in, recent. Years, the. Second thing to point out is, that we. Are not perfect, either, right, this, is study of Israeli. Judges, in their decision, making during, the day and what you see here is, that we, make a high, share of favorable, decision, just, after we have our morning, snack and then you, know the, sheer drops down during, the morning and bumps back again as insulin. Levels go up after the, lunch break and so on and so forth, right and perhaps, we can you actually use algorithms. To make better, decisions, in some, domains where. We perform. Poorly. Thirdly. I think it's worthwhile pointing. Out that, much. Automation. Doesn't. Happen. By. Replicating, exactly what. The human worker does right we, didn't automate, laundry, work by building robots, that walked. Out from the kitchen into, the forest shop down trees trees, carried. Wood and buckets, of water into, the home heated. It's under stove and then performed, the, motions of hand washing right we, did that by inventing, the electric washing, machine, in the same way we didn't automate, away the work of lamplighters. By, building, robots. That are capable of climbing lampposts. And engineers. Have, at, least historically been very good at. Circumventing. Some. Engineering. Bottlenecks, by simplifying. Tasks, and I suspect that is likely to continue, that, being said though there are still certain domains, in which computers, perform. Poorly. Simple. Things for us like, deciding. What's a piece of rubbish lying on the floor and what's a really important document is. Still something, that you. Know it's very hard to, and, explain. And there are no general-purpose, robots. That, are able to do all of the things that. You're, cleaner, does for, example, and when. It comes to more complex, tasks. Like creativity, and, complex. Social interactions. We. Also see, that, technologies. Are, still performing, quite, poorly right and I think this is well captured, by the Turing, test where, shatta BOTS try, to convince human. Judges of them being a person and, some people argue that there was a breakthrough a. Couple, of years ago when one shot bottle, actually managed, to convince 30%, of human judges of it. Being a person but it did so by pretending to be a 13 year old orphan, Russian boy speaking, English, as a second, language with no understanding. Of English, culture, and and, if you think about, the variety of much more complex, social interactions. You, do in your daily jobs, I think it's almost inconceivable, that. You will be replaced, in those tasks, in the near future, now. The key question that emerges, from their system how intensive, are our jobs, in, tasks that correspond. To these engineering. Bottlenecks. To automation, according. To our estimates quite, a few are actually not very intensive, in such tasks roughly four to seven percent of, jobs we estimate or at, risk of automation. And that's, no longer just production, jobs is everything, from transportation logic. Stakes warehouses.

Retailing. Construction. And so on and so forth, and when, we published this study a couple, of years ago we actually published, a very detailed list of 702. Occupations. And their, relative, and exposure. To automation, and, you can imagine that quite a lot of people dug through this list and try to come, up with silly, examples. And my. Friend can cook here at the Economist used to tease us because we found that fashion models are. Highly exposed to. Automation. These models on these pictures actually don't exist they've, been created, by generative, adversarial. Networks. Which, have generated. Them from thousands, of pictures and they're already being used by some. Companies, like, Dior, at. The same time though we did. Say. That. Technology. Is, clearly. Not the only factor. That drives. Decisions. To automate right when, Nissim produces, cars in Japan it relies heavily on. Robots, but, it does the same thing in India. It relies, heavily. More. Heavily on cheap labor. When. Tractors. Were first invented, they. Were long not, adopted, because there, weren't any, operatives. That could actually, run, the machines and the New York Times noted. In eighteen in, 1918. That the, tractor, is too good a machine to be put in the hands of the poor operator, and to. Spur adoption. Colleges. Were actually, created. That provided training, courses for. Tractor. Operators, to spur adoption. And, they. Are, essentially. Restaurants, today which are vending machines which could have cut a cut, out the, weight from. The. Process. And. That may be good, for certain. Events. Like, going, for a quick lunch but. We are likely to prefer. Having. An automated waiter for. A pleasant, dinner right so, consumer, choices. Also. Matter a lot for decisions. Toward. And, even if Google Translate, became perfect, tomorrow. Human. Translators. Still. Or a certain, document you still need certification. So. Unless. We certify, Google. Translate, those, jobs are not going to be replaced, tomorrow. And. Lastly. As, I pointed out earlier, adverse. Public, opinion, can matter as well, these, are dock workers, who went on strike in, Los Angeles last. Month because, of the introduction of machinery. In. The. Harbor in which they, were and. I think that a big difference, between today, and, Industrial. Revolution is, that. People today actually. Have, at. Least and Industrial West political. Rights and, I. Think that the economists learnt if was on to something when he suggested. That. If. Horses, could have joined the Democratic, Party and vote, what, happened, on the farms might have turned out differently, they, may have used the political rights to bring the spread of the tractor, to, a halt and in, the case of the Luddites was essentially, hopeless right because in the 19th century Britain property. Ownership was still a requirement, for, voting. So, the voice was essentially, left, and, unheard. Now. I'm actually, an, optimist. About our, long-run future, I'm, 100%. Certain. That. Artificial, intelligence are. Going to make. Education, and medicine, better, it, will rise. Productivity. Boost. Some people's wages it's. Going also to create lot. Of new jobs that we can't even, imagine, today. And. It's. Already, created. New, jobs in recent, years LinkedIn. Recently. Did a survey on their platform, where they looked at the fasting growth occupations. And among, those who find jobs like iOS. Developers, social, media intern, big data architects. But, also Zumba. Instructors, and you, find jobs like digital. Marketing specialist and also Beachbody. Coaches. And I. Think, this, reflects. A broader trend that. We are actually seeing in recent years with, tech jobs, clustering. In skilled cities, like London, like, Stockholm, in the Bay Area and so on and those, people. Demanding. More. Specialized. In-person type, of services, and the. Result of this, is, that. More, people are, clustering. In these places and and. That. Has been great for, cities like London, but, it hasn't been great for certain people people. In the countryside who, have seen jobs vanish, due. To automation. And, this, is created, very. Much of the divide that we are seeing today, between. These, hubs for technology, and. The. Rest essentially. And and. I would predict, that unless. We. Do something about this, these, trends, are likely, to continue. The. Book is called. The technology trap and the.

Technology, Trap actually refers to pre-industrial, times. When. Workers. Frequently. Resisted. The implementation, of new technologies, and, governments. Fearing, social unrest. Essentially. Sided. With. Angry. Workers. And as, a result, of that new. Technologies, were. Often, resistant, and often. Outright. Blocked, and this, meant that economic, growth was, also slow, for. A very, long time the, question I asked in the book is could we return, to, this technology trap in which government's, tax, robots, and him break, up technology, companies, and, essentially. Try, to hinder the, spread of automation. Technologies. The. Simple truth is that I'm far. From sure about. That but, I do think, that it is a real risk and I think to. Harvest, the long-term gains from, artificial, intelligence, and other technologies, on the rice and we, need to think through, the, short-term dynamics. Quite, carefully, and and. I, think that's probably a good place to open up for questions so thank you all for coming and. Great. To be with you. So. If you were then advising, policymakers. On what action, should they be taking knowing, these trends, what. Would be the big policies, that you think they should be prioritizing, I think the key word there is in a way big because everybody. Thinks that you, have a big challenge and you need a big policy, change to. Sort. Of solve it and and. Unfortunately I don't think that there is this one big policy, and that. To deal with the challenges, that we face is more of a package, of many, things that. Individually. May sound minor but. That collectively, can. Make a big difference and so. To take one example I, grew up in, southern. Sweden close to the city called Malmo. Amalga. Was a city that specialized. In building, ships an industry. That went down in the 1990s. And the city was actually doing quite poorly for, a long time and essentially, don't it took off again with the construction of the bridge to. Copenhagen, which meant that people could, stay put in malmö where, housing was cheap, commuting. To Copenhagen, where there was a greater abundance of, new jobs spend. Their money locally. In a manner which gave a boost, to the local service economy, there and essentially.

Created, This, virtuous, cycle and, and, I think that one of the key. Drivers of both. Income. And wealth inequality has. Actually. Been, that. There, are. Significant. Constraints. On housing, supply, to. Places, like London where, these new jobs. Are emerging. And a, lot of people can actually not afford, to live in places. That. You know provide most opportunity. And that this reason why some people are not leaving the Bay Area for places like Austin because it makes. It harder to actually. And attract. Talent so. I think that a lot can actually be achieved by, building, more in a, in places and that. Are expanding, and be. Connecting. Them through, investments. In smart infrastructure. Because. People, ideally. Want to stay put in their communities, right, and if you can you know connect. Declining. Places, to expanding, once a lot can be achieved now, you, know looking into the future, you. Know there may be better. Transportation. Technologies, and we have now this, currently feasibility, study being done of. Connecting. Cleveland, and Chicago with, the Hyperloop so that's currently a six hour drive if. That, was, to be successful at some point that, would be a 28-minute. Commute, so to labor markets, would, essentially be one and I, also think that a, lot. Can be achieved, by investing, more in early childhood dedication so you don't know exactly what the, skills of the future will be but, we know what some of the. Hurdles. To, acquiring new skills are and if you have early deficits. In math and basically reading, you're much, less, likely to learn. New. Skills later on you're much less likely to go, to college and you. Much less likely to participate. In, civic activities, and. So on so I think by investing. In early childhood. Education particularly. The private areas loss can be shoed as well if you ask, people. In many of those towns that say we don't want to be a dormitory town, to a big capital city we want good. Jobs back, like we've had before like farming. Jobs fishing, jobs manufacturing jobs. Would. Your argument be war that, would effectively be like, the Luddites were trying to do hanging onto jobs that will no longer exist or would your argument be you need to invest in those other kind of jobs as well, yes. I mean I don't believe, in conserving. Old jobs and. I mean, bringing. Old jobs back is essentially, conserving. In the past and if we would, have done that, for. The past hundred years a lot of people will still work in coal mining and coal. Mining communities, might, have been better off then, in a way than they are now, but, an average, you know we're so much more better, off because, of the changes, in the labor market and the changes, in technology we've seen over, the long-run and. I think you know in the short run a lot. Of people. Who.

Are, Likely to be made worse of by, changes, in technology. I, think, a problem problem when economists speak about the short-run is that we are usually. Not very specific but what, that means and whether it's 20 hours 20 days or 20 years, kind. Of, matters, during the industrial revolution, that was a long time but, in sort of the grand, scheme, of things right, later. Generations. That we made so much better off as a consequence, of that and if we value later, generations. As we value, current ones and then. We should think that it's instilled. In the greater good I was. Interested by the robot, map if you will showing, kind. Of that correlation, if. There is a correlation because. I guess the loudest explanation, that I've heard about. Why kind, of the the u.s. shifted. Was. Offshoring. Of jobs. Do. You think that there's maybe, a lack of awareness. Among. Those that are kind, of a greatest risk of automation. I know you showed kind, of the the. 47%. Statistic. In the LA Harbor but do you think there's a great recognition of that and do you think that kind, of narratives gonna get louder over time yes. I think, first. Of all I mean offshore is enabled, by a technology, as well so let's. Disentangle. The two is. Tricky. But. It's absolutely, clear that both, offshoring, and, automation. Has, contributed. To the industrialization, and if you look at the United States you see that manufacturing, employment peaked, in mountains Denine and. The manufacturing, employment share has, fallen steadily. Since. Then. But. The output. Share of. The. Economy. Has actually made, been. Constant, over the same period of time there's, still a lot of stuff being produced in, the US but, with a few, people, and and. I, think. As. I mentioned globalization. And. Automation. Have both played, a significant, role I think looking forward, though the, rise of China has, already happened we already seen, a lot of offshoring. Most. People today actually work in non-traded. Sectors, of the economy that, can't, be and, exported. And, so they are relatively, shielded, actually, from future. Globalization. But, they aren't shielded from automation, right so they're roughly 3.5, million, cashiers, in the US which. Are exposed to technologies, like Amazon. Go the, three point another 3.5, track bus. And taxi drivers which. Are exposed to autonomous. Vehicles and so. There are a lot of jobs that are. Are. Not of sharable, but automatable. And. I think and, that. Is also one. Of the reasons, to be concerned that, it may, actually shift, more towards technology. Facebook. Recently, made. The argument, against. The, breakup, of big tech that if big. Tech is being broken up, somebody. Else sees much in this case Chinese, company, would take over. Do. You believe that we. Reached a point where. Globalization. Trump's. The, power. Of, single. Governments, to. Stop. Or in, this case accommodation, would. Encourage. Or, accelerate, the, spread. Of automation, so. One of the key reasons that Industrial Revolution happened, in Britain was not that book there was an absence, of resistance to, technological change right, quite. The contrary and the, reason that it happened in Britain was that governments, for the first, invent. Sided. With innovators. And pioneers. Of, industry. And and. The, reason for that in term was. In. Large, part actually. Early globalization. And competition, between nation states so. The craft guilds for example, which, sort. Of forcefully. Resisted, new, technologies, became. Weakened, by globalization. Because. Their political. Clouds, didn't, extend. Beyond the city in which. They worked and so.

As A result of that the threat from the below was. Essentially, reduced, and and. Because, governments. Increasingly, realized. That. You. Know their, military. Muscle depended. On their. Economic. Strength. They. Also invested. More in mechanization. And and, allowed it to thrive and, I think that essentially goes to your question in. The sense that you, know we are concerned. About. An. Outside. Threat. To competitor. Gaining. From. You, know, imposing. Essentially, new technologies, potentially. On the population. Even if there is resistance. To. Them and now. In. Most. Modern democracies. You know we're more worried, about, the short run then. You know the Chinese government, is for, example and, you, know whether we. Have Jeremy Corbyn, or Boris Johnson, in office they, all worried about being, elected in the next general. Election, so they, are much more, likely to take you know the, democratic. Process, or the threat from below if you like and more. Seriously. Then. Let's say the, Chinese, government. Is so I mean, I I take, the point that, you. Know China may have an advantage, in. That regard, but, I still think you know it's an it's a difficult selling, proposition. To, voters, and say look. You. Know it may be your, jobs, that. Are at stake but we are still going to implement. These technologies, because. Of, you. Know competition with China's another place one, question I have is one of the kind. Of things, are components of the processes. That are happening today, is the. Environmental. Challenges. Limits. That we're reaching how. Do you see this play, out within, the kind, of processes, that are occurring. Right now and do you see this different, from before so you're, asking about the environmental. Challenges, related, to automation. Okay. So, I mean I don't, have a strong. View on, that. So I think my my. There's. A tendency of new industries, to be, you. Know less. Carbon-intensive. Than. Past industries, and I. Think as the economy. Dematerializes. And that, is going to be less of an issue with new and, innovations. I, mean. If we if you speak to our group of, year engineering, at. Also Martin school they, actually think that to reach the 2% target you. Need you know technical, solutions, because even if you stop, carbon, emissions tomorrow. You're not going to reach it so, I think sort, of stopping the technological, clock due. To environmental. Concerns which, I take, to be slightly implicit in your question maybe. It was not. It's. Not a great idea but my. Question was more about whether, you think that the. Limits. That were reaching are. Kind. Of configuring, a different, scenario to what was happening in the previous Industrial Revolution when. Those, limits, just simply, were in there because we, had like all of the resources, to use, and I, was wondering, whether. You. See this factor, play. Out within the processes, that are occurring, right now about. You then, said you kind of answered so. But. There were actually some significant. Limits erm in the early Industrial Revolution in, part what's happened in northern England because it was close to coal and. Transportation. Cost was still relatively high. There, was actually a constraining. Factor in, the early days industrialization, as well can, you mention it in the introduction of the book that was also the impact, on communities, so for example in doing the industry revolution, and. What we have witness until now probably social order is very similar right roughly. Right I mean like people, moved into factories, they still work together the, community was much more stronger, well actually now, with technology I, think there is a much more shifting individualism.

The. Concentration. Of power even more in less people how do you compare. The. Societal, impact of, Technology. During, the industrial revolution versus. I. Think, in that regard Industrial. Revolution was mainly more disruptive, in the sense that a lot of people said we still you know people, still worked, but few people actually had jobs right most people were worked, at their own pace and at. Home often you know close to their, relatives. And children, and you know everybody, was, under one roof and what the factory city essentially, did is to take, a lot of people from various places, across the country and bringing. Them all together in. Rather. Unhealthy. Aesthetically. Unappealing. Environments. And, you. Know at wages. Which hardly, compensated. For, those working. Conditions, so I think in, that sense the Industrial Revolution might, have been more disruptive, and what. We've seen. Today. You've. Touched a little bit about the policy, level and some of the things you could do there what. Would be your advice to at, the individual, level if, you're speaking to somebody who is facing say imminent. Threat. To their role may, be due. To the Amazon type of situation, of an automation, of checkout, or something, is is it simply re-skill and, also. Is there a role the government ought to be playing in terms of helping them find that next role in. Terms of that rescaling journey all, right there's, a great question, I'm, an academic not, a career advisor but. Broadly. Speaking I think you do well and focus on the things that machine's to do poorly so, I think a lot of work. That involves complex social interactions, creativity, for example, it's. A good start I do, know that you. Know computer. Science we, struggled, to keep PhD, students for the first, six months right, because they get, hired by Google and, other companies. And. It's. Clearly in a skill set that's enormous. Ly in-demand. Broadly. Speaking I mean also if you think that, data, is the new oil it's, a cliche, but nonetheless. Statistics. And. Machine. Learning, generally, it's. Probably a good idea, but. I think people need to figure out for themselves what they enjoy him what a good as well so I don't ever very. Strong opinion on that I, see. Technology is something that. Essentially. Humans, created to make their lives easier so even if there was a limit. Imposed by an, authoritative. Body on. Technology. Progressing, the, humans will always find a way to make their lives easier, would. The question not be, about. Say, the distribution. Of resources and, only mentioned this because you mentioned the Communist Manifesto. Earlier, in your presentation, but. Isn't that essentially one of the questions that Marx answered. When. We reach a certain level of technology that resources, have to be distributed. Obviously he vision, a world where you, know robots working in the farm some people are frolicking about picking, flowers and, stuff but. Yeah. So most thought that people, would have to acquire, the means of production it, didn't think that wages will. Rise as, mechanization. Progress, things. Happen, quite.

Differently. Well. I mean. I'm. Not sure that I. Agree, with the basic premise that people just innovate, to make their own lives, easier. So I think a lot of innovation, is happening. In businesses. Today and it's happening, to, meet you know sudden. Consumer. Demand. But I do agree that you know it's, very much a distributional. Issue. If you look at the country like Saudi, Arabia and a country like Norway right they both have oil they've essentially, you know black. Gold coming out of the ground, but. They're very different economies, they're very different societies, it's. More widely shared in one place than. The other and obviously that, is you know due to the result of, institutions. And culture and, you. Know factors. That have nothing to do with, technology in itself clearly. That's, right. You. Drew the parallels between the. Rise. Of automation in certain just parts of America. And the, rise of Republicans. Switch, to the public and vote, so. I'm furthering the parallel between the rise of populism, with. That are. There any kind of parallels than what happened with in Dutch Revolution and is there any sort of light at the end of the populist, tunnel that we seem to be going down at the moment. Sorry. There's a parallel with the rise of populism, in with, the rise of with, with, the automation how. Did that pan out in a similar way back. In the Revolution was there a shift, in politics, and how that. Responded. To that and then how did it evolve once things that established. Themselves right, so not really I think one one, key difference is sort of actually in the the sphere of economic ideas, so, lots of people at the time Industrial, Revolution still, believed that the world was Malthusian. Right that, was the idea that larger. Higher, incomes, would only result. In larger populations. With, no. Benefit. To the average. People in a capital terms and as, a result of that it was also believed, that any sort of redistribution.

Was. Essentially meaningless because it would only translate. Into a larger population and and. This idea was actually very, popular, it, led to the, reform. Of the poulos, in, 1834. Which. Essentially, you know took. Away the, safety. Net and that. Had existed, so the, policy direction in, that regard was more, sort of, the way around I think, today there's actually, most. People realized that there are things that governments, can do to smoothen. The transition, and you know the other big, difference is that even. With the reformer, Act of. 1867. Property. Ownership, still, remained, a requirement. For virgin so most people were essentially politically, disenfranchised. You. Made the point that perhaps. If horses. Had. Had the vote then, maybe the Industrial, Revolution wouldn't. Have played out as planned. You. Could say that some of the beneficiaries, of technology. Change. Have, the vote state but many don't, and so. In advanced, Western democracies. How, does this all play out so. I'm not not. Sure if I'm following your question you know in a world where everyone, had where in advanced, economies where most people have the votes but. Perhaps. Many people won't be beneficiaries, of technology, change how, does this play out in a democracy. Yes. I think that that's the key point right so I mean if people are, not happy with the verdict of the market they, can opt against, it through, various. Mechanisms and, I think. That somebody, who is sort of tapping into this concern like Andrew yang in the United States today and, it's gaining a lot of traction and. On, that so I think it's extremely. Hard. To predict how this is going to play out and that's sort of also one of the key points and of. The book because, this. 47% study that we published back, in 2013. In. A sense you. Know created. Literature, in which people were trying to predict exactly how many jobs that were going to disappear or or appear by 2030. And so on and, we mainly looked at potential scope, of automation I think the pace of it is much, more, complex, it depends, on what we do it depends, of acceptance. For. New technology, and much. Of that sort of labs going, to play out in the sphere. Of political, economy and we struggle to predict, the outcome of the general election, and the very same days I think we need to be rather, humble about our ability. To predict such. You.

2019-08-18 16:19

Other news