Shadowing Practice: The Great A.I. Debate: Should We Fear the Digital Revolution? [2015] | Intelligence Squared - Learn English Speaking with Video
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So I've got some good and bad news
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and since we're in England we'll start with the good news because we always need to end with the bad news.
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The good news from your point of view and of course I'm arguing
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that we should be scared but there's one thing we shouldn't be scared of.
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We don't need to fear that in 20 or 30
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or even 50 years we will become as human beings indistinguishable
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from computers in other words in 50 years we could all
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be here it could be like a science fiction movie
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and we won't know whether you're sitting next to a computer
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or not so that's the good news you don't have to worry about singularity
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but that doesn't mean we should not be fearful of robots
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that doesn't mean that we have a lot to be scared about just
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because we're not about to become indistinguishable from robots doesn't mean they're about to take away our livelihood
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and I'm guessing that many of you are lawyers
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or doctors journalists people trained in a field you probably went
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to university you spent years acquiring your intelligence your skill your intellect
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and you sell
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that skill as a teacher as a doctor as an accountant
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as a lawyer your value in the economy is based on that expertise
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and it is you I'm afraid who have the most to fear from this great revolution the digital revolution
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which one set of economists call our second machine age
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because this is as profound as earth shaking as culturally socially
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and above all else economically profound as the first Industrial Revolution of the 19th century.
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What we're on the brink of is a world of increasingly intense, sophisticated, artificial intelligence.
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In Silicon Valley, where I'm from, we call it the machine learning revolution.
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It's the revolution of algorithms, not the traditional science fiction, old -fashioned HG Wells notion,
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Doctor Who, of the robot trundling along the street, the Dalek get
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that image out of your mind think of the algorithm think
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of the self -driving car think of Google think of these incredible new technologies
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which are coming out of Silicon Valley
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which are essentially replacing human labor skilled human labor
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because here's the paradox it's really hard for computers to replicate
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what seems to us to be simple tasks simple tasks like
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doing the garden the washing up cooking cutting someone's hair
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but on the other hand
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and here is the dark scary horrific element to the new
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world we're about to enter it's not difficult to do what seems to us at least to be the difficult things.
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The bad news, and this is really bad news for most of you, and especially for your kids because they are trying to follow in your footsteps,
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is that this world is about to be swept away by the digital revolution.
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Machines will learn how to diagnose diseases.
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What does that say for all doctors around the world?
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We already have software now that grades essays.
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What becomes of school teachers, what becomes of university teachers.
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Two researchers at Oxford University have argued
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that over the next 10 years 47 % of our jobs will become irrelevant
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and those 47 % I'm afraid for you guys are your kind of jobs.
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And it's not just skilled labor, it's not just the professional class, it's not just those people who have been fortunate
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or unfortunate enough to go to university we have a large
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audience a television audience from the developing world these are people
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who are embracing education who see it as a way out
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of poverty i'm afraid the news is really troubling for them
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because they missed the bus development which was always taken for granted no longer will happen.
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And we have these increasing inequalities in Silicon Valley because all the wealth is going to the platform companies.
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All the wealth is going to companies like Amazon and Google
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and the other companies that have harnessed this technology for their own benefit.
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What we're seeing is a hollowing out of the middle class,
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a hollowing out of the kind of jobs that you guys have depended on and a replacement by the algorithm,
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by the machine, and by a tiny group of people who own and control that machine.
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That's the reason, I'm afraid, why you should be afraid, very afraid.
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Thank you.
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Thank you very much.
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So our second speaker is speaking against the motion, Walter Isaacson.
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And Walter became famous for his internationally acclaimed book on the life of Steve Jobs,
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and he gained unprecedented access to Steve Jobs in the last months of his life.
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He's also president and CEO of the Aspen Institute in Washington
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and a former chairman and CEO of CNN and the managing editor of Time magazine.
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How do you fit it all in?
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Thank you for making the time for us today.
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Your time starts when you get to the lectern.
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Thank you.
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Thank you very much to have good news for you
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and good news the good news is you don't have to be afraid
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and the other piece of good news is there's no bad
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news in this the future is really going to be cool since my
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since my distinguished opponent mr keen started with the industrial revolution and said
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that this new revolution would be as disruptive as the industrial revolution let me begin by reminding you
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that the industrial revolution wasn't all that bad
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and at the end of it we had more jobs not
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fewer jobs technology can indeed be disruptive it can disrupt certain jobs as mr keen has said
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but it always has and i submit always will produce more jobs because it produces more wealth more personal income,
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more per capita wealth, and thus more things that we can make and buy.
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Every succeeding generation has had a new wave of worry, dire warnings that jobs are being threatened.
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But in each one of these cases, they turned out to be wrong.
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I was at Time magazine i went back to look 50
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years ago 50 years ago to this date almost time magazine did a cover
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just like this just like the uh line
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that we're looking at it said the robots are coming automation
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will take your job it quoted a rather famous um economic historian robert holborn
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or most of you have heard of him he says the new technology is threatening a whole new group of skills.
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Sounded just like Mr. Keene.
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He said the calculating, the remembering, the comparing, the okaying skills,
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the preserve of the office worker will go away and machines will invade society to make that type of human labor redundant.
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Well guess what?
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It's been 50 years and since then, soon after he wrote that, we had the greatest leaps of technology you can imagine.
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The The internet, the personal computer, and the microprocessor all come into play, but nobody has been rendered redundant.
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There's more jobs and more types of jobs now than there were 50 years ago.
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As Marc Andreassen, the person who invented the web browser,
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said, just as most of us today have jobs that weren't invented 100 years ago, the same will be true 100 years from now.
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Let me give some examples.
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There's the app economy.
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It began in 2008
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when Steve Jobs was convinced by other members of his management
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team to allow outsiders to create apps for the iPhone and then the iPad.
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The app store alone since then has created 627 ,000 jobs.
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The app economy last year was $100 billion, far surpassing the film industry.
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This is an industry that did not exist seven years ago.
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Other advances in technology have helped facilitate new forms of work, such as the sharing economy, where people both here, New York,
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New Orleans, can drive cars, be part of Uber, be part of Airbnb, be part of Lyft.
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Likewise, online marketplaces such as Amazon and eBay have enabled the rise of artisans,
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makers, the type of people that existed in the pre -industrial age, people who had creative instincts and then could have connections to customers around the world.
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If you create a book or a song now, you have new ways to publish, as Pippa did with her own book, new ways to distribute.
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If you dream up a new specialty, this world allows you to find customers and provide a service,
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just as if you were an artisan or a service maker in the pre -industrial revolution.
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It even helps long -established companies find markets all over the globe.
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There's a more fundamental shift going on in the economy that's also good.
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We're creating an on -demand or on -tap economy.
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If you need a housekeeper or a handyman, you don't have to go to a particular firm to get it.
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It can be done on tap.
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If new technologies reduce the total number of jobs, we'd all be out of work now.
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And I doubt that Mr. Keene, nor I, nor you, can guess what wondrous jobs technology will bring to our great -grandchildren.
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Thank you.
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Thank you very much indeed, Walter.
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Our second speaker for the motion is economist George Magnus.
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After a long career in finance in the City of London, George has turned to writing, and he's written The Age of Aging,
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a study of how demographics are changing the world, economy, and social systems.
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So, George, please make your way to the lectern and tell us what you think.
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Thank you very much.
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So, we're going to talk economics now, okay?
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Not populism.
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So what I'd like to put to you this evening is
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that these digital and robotic technologies constitute a very powerful economic threat to our livelihoods because of its effect on jobs,
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on income distribution, and because they demand that we focus on coping mechanisms that we do not yet have.
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now our opponents in this debate
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and you've already heard the first will try to convince you
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that because mankind has always adapted to new technologies historically we shouldn't fear the robotic revolution
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but this time as they say it really is different
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and I'm going to tell you why
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so just over 200 years ago 64 men went on trial
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in York these Luddites they went on a rampage They burned mills and machinery and so on, but their campaign, as we know, was myopic because the Industrial Revolution,
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or the first Industrial Revolution, did leave us all better off.
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What we did is we harnessed power, and that exposed the limits of human brawn.
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But it was also complementary to human endeavour.
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This is the key point.
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It allowed us to blend men and machines in ways which boosted employment,
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growth, income, and sustained a rising and prosperous middle class.
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The modern technological revolution is different.
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It's exposing the limits not of human brawn, but of human brain.
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And instead of being complementary, modern technology is displacing us.
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Capital is being substituted more and more for labour, threatening jobs, living standards and, as we know from contemporary political debate,
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the fabric of the middle class.
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Not all jobs, of course, are at risk, as you've already heard.
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Machines are not sufficiently dexterous to do all kinds of manual work
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and lots of human cognitive and judgmental skills have not been replicated by machines and may not.
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But they've already been doing routine -based or rule -based jobs on the factory floor and in offices for some time.
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Since 2010, the number of low -paying and high -paying jobs has gone up, but the number of middle -level jobs,
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middle -wage -paying jobs, has stagnated or dropped in a pattern
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that is replicated across the whole of Europe in the United States and indeed in some emerging countries, notably in China and India.
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Successful capitalism needs us to be fully engaged, not just as gadgets savoring consumers, which we all are, but also as producers.
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In other words, we need to have stable, productive, high levels of employment, which is what robotics is undermining.
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And because capitalism rewards scarcity, and because the robotics revolution is generating productivity gains that are benefiting a limited number of people,
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The principal rewards of modern technology are accruing to the owners of capital, not the owners of labor in the main.
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Think about the three biggest firms in Silicon Valley.
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They have 137 ,000 people, and these three companies have a market capitalization, in other words,
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they're worth $1 .2 trillion dollars now just cast your mind
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back 25 years to 1990 the three biggest companies in detroit had 10 times as many workers 1 .2 million
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and their combined market value was a mere $36 billion.
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This fundamental change in the relationship between capital
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and labor is also illustrated by what we see in lots
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of surveys about the rising share of profits in national income and the declining share of wages.
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Because as economic inequality rises, so political inequality rises.
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And those that benefit from more political power obviously seek changes
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which further their own economic advantage
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and you could easily end up without coping mechanisms at a very kind of dystopian political future.
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I would remind you of the quip from Lord Keynes the famous British economist who quipped
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that in the long run we're all dead by which he meant
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that the economists focus on the long -run equilibrium was a waste of time because economic circumstances affect us now next year,
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in the next few years, not at some vague point in the unmeasurable future.
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And that's really what is important and brings me to my final point, which is that we need to think about this really seriously and try to develop coping mechanisms.
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There could be many.
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Better education, better training, improved access to capital, job protection schemes for certain occupations,
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high minimum wage, direct transfers, labor -intensive construction, taxation of capital to help displaced workers and so on.
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I'm not commending, ladies and gentlemen, any particular coping mechanism to you tonight,
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merely pointing out that we have few and need many as the robotics revolution evolves.
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Vocabulario y notas de pronunciación para esta lección
Esta lección de conversación se basa en el vídeo “The Great A.I. Debate: Should We Fear the Digital Revolution?”. Este vídeo tiene 183 frases y 2350 palabras para practicar shadowing. La parte hablada dura 16:37. El hablante mantiene un ritmo constante de unas 141 palabras por minuto, cómodo para el shadowing. El 84 % de las palabras está entre las 3.000 más comunes del inglés; conviene repasar el resto antes de empezar.
Vocabulario clave de este vídeo
15 palabras del vídeo que vale la pena aprender, con su pronunciación y significado:
| Palabra | Pronunciación | Significado |
|---|---|---|
| skill sustantivo | /skɪl/ | destreza, habilidad |
| mechanism sustantivo | /ˈmɛk.ə.nɪ.zəm/ | mecanismo |
| robot sustantivo | /ˈɹoʊ.bɑt/ | robot |
| economist sustantivo | /iˈkɑ.nə.mɪst/ | economista |
| wage sustantivo | /weɪd͡ʒ/ | salario, sueldo |
| algorithm sustantivo | /ˈælɡəɹɪðm̩/ | algoritmo |
| threaten verbo | /ˈθɹɛt.n̩/ | conminar, amagar |
| inequality sustantivo | /ˌɪn.ɪˈkwɑ.lɪ.ti/ | desigualdad |
| replicate verbo | /ˈɹɛplɪkeɪt/ | replicar |
| robotics sustantivo | /ɹoʊˈbɑ.tɪks/ | robótica |
| argue verbo | /ˈɑɹ.ɡju/ | argüir, argumentar |
| fiction sustantivo | /ˈfɪkʃən/ | ficción |
| remind verbo | /ɹəˈmaɪnd/ | (hacer) recordar/arrecordar, hacer acordar/arrecordar (se de) |
| fundamental adjetivo | /ˌfʌn.dəˈmɛn.təl/ | fundamental, cimental |
| reward sustantivo | /ɹɪˈwɔɹd/ | recompensa |
Phrasal verbs que vas a escuchar
| Palabra | Pronunciación | Significado |
|---|---|---|
| end up verbo | terminar, ir a parar | |
| go away verbo | irse, marcharse | |
| go up verbo | subir | |
| point out verbo | señalar, apuntar | |
| sweep away verbo | arramblar | |
| take away verbo | /ˌteɪk əˈweɪ/ | quitar |
Gramática en este vídeo
Las estructuras que más usa el hablante, con las palabras exactas del vídeo:
| Estructura | En el vídeo |
|---|---|
| Present perfect have/has + participio pasado — una acción pasada que sigue importando ahora | have argued · have been · have harnessed |
| Voz pasiva be + participio pasado — importa lo que ocurre, no quién lo hace | is based · be swept · was always taken |
| Oraciones de relativo who / which + oración — información extra sobre una persona o cosa | people who have · development which was · people who own |
Pronunciación a tener en cuenta
El hablante usa 40 contracciones y formas reducidas, como I'm, we're, don't. Dilas en su forma corta, tal como las oyes.
- Los sonidos de “th”: algorithm /ˈælɡəɹɪðm̩/, threaten /ˈθɹɛt.n̩/
- Los sonidos de “sh” y “zh”: fiction /ˈfɪkʃən/, wash /wɑʃ/, essentially /ɪˈsɛnʃəli/, shake /ˈʃeɪk/, artificial /ˌɑː.tɪˈfɪʃ.əl/
- Palabras largas — cuida el acento: mechanism /ˈmɛk.ə.nɪ.zəm/, economist /iˈkɑ.nə.mɪst/, inequality /ˌɪn.ɪˈkwɑ.lɪ.ti/, fundamental /ˌfʌn.dəˈmɛn.təl/, capitalism /ˈkæp.ə.təlˌɪzm̩/
Sonidos difíciles para hispanohablantes:
- s + consonante al inicio — sin añadir una “e” delante: skill /skɪl/, stable /ˈsteɪ.bəl/, scary /ˈskɛə.ɹi/, sweep /swiːp/, specialty /ˈspɛʃ.əl.ti/
- /v/ — no es /b/: los dientes tocan el labio inferior: convince /kənˈvɪns/, invent /ɪnˈvɛnt/, poverty /ˈpɑːvɚti/, productive /pɹəˈdʌk.tɪv/, preserve /pɹəˈzɝv/
- /z/ — sonora, no /s/: mechanism /ˈmɛk.ə.nɪ.zəm/, capitalism /ˈkæp.ə.təlˌɪzm̩/, preserve /pɹəˈzɝv/, expertise /ˌɛkspɜːˈtiːz/, likewise /ˈlaɪkˌwaɪz/
Cómo practicar con este vídeo
- Escucha el vídeo entero una vez sin hablar y anota las palabras que no conoces.
- Haz shadowing frase por frase a velocidad normal, repitiendo cada una hasta que tu ritmo coincida con el del hablante.
- Grábate y compara con el original, prestando atención a palabras como skill, mechanism, robot.
¿Qué es la Técnica de Shadowing?
Shadowing es una técnica de aprendizaje de idiomas respaldada por la ciencia, desarrollada originalmente para la formación de intérpretes profesionales y popularizada por el políglota Dr. Alexander Arguelles. El método es simple pero poderoso: escuchas audio en inglés nativo y lo repites en voz alta de inmediato, como una sombra que sigue al hablante con solo 1-2 segundos de retraso. A diferencia de la escucha pasiva o los ejercicios de gramática, el shadowing obliga a tu cerebro y músculos de la boca a procesar y reproducir simultáneamente patrones de habla reales. Las investigaciones muestran que mejora significativamente la precisión de la pronunciación, la entonación, el ritmo, el habla conectada, la comprensión auditiva y la fluidez al hablar, convirtiéndola en una de las metodologías más efectivas para la preparación del IELTS Speaking y la comunicación en inglés en el mundo real.