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  • A decade ago, robots still seemed pretty limited.

  • Now, not so much.

  • And computers don’t just win chess any more, they can win Jeopardy.

  • Watson.”

  • What is the of the Elegance of the Hedgehog?”

  • They can win Go.

  • There are about 200 possible moves for the average position in Go.”

  • This is all happening really fast.

  • And it’s causing some to forecast a future where humans can’t find work.

  • There will be fewer and fewer jobs that a robot cannot do better.”

  • And what are the people gonna do?”

  • That’s the $64,000 question.”

  • I believe this is going to be one of the biggest challenges we face in the coming decades.

  • People who are not just unemployed.

  • They are unemployable.”

  • But if you ask economists, they tend to have a pretty different view from the futurists

  • and Silicon Valley types.

  • Do you worry that new technologies could cause mass unemployment?

  • Yes. No.

  • I have devoted my career to worrying about the labor market, particularly worrying about

  • the living standards of low and moderate income workers.

  • So I worry a lot about things.

  • I am not worried about this.

  • One of the reasons a lot of economists are skeptical about robots taking all the jobs

  • is that weve heard that before.

  • There was a spike of automation anxiety in the late 20s, early 1930s when machines

  • were starting to take over jobs on farms and also in factories.

  • This article from 1928 points out that there used to be guards who opened and closed the

  • doors on new york subway trains, and people who took tickets before there were turnstiles.

  • And I just love this quote: It saysbuilding materials are mixed like dough in a machine

  • and literally poured into place without the touch of a human hand.”

  • Automation anxiety surged again in the late 1950s, early 1960s.

  • President Kennedy ranks automation first as job challenge.

  • Computers and automation threaten to create vast unemployment and social unrest

  • What should I do Mr. Whipple?”

  • Stop him!”

  • This article from 1958 is about 17,000 longshoremen who were protesting automation on the piers.

  • And if you don't know what longshoremen are, that’s because there aren’t many of them left.

  • Technology destroyed a lot of those jobs.

  • And yet, we didn’t run out of work.

  • This chart shows the percentage of prime-age people with jobs in the US.

  • Ever since women joined the workforce in big numbers, it’s stayed around 80%, outside

  • of recessions.

  • During this period, technology displaced some 8 million farmers in the US, 7 million factory

  • workers, over a million railroad workers, hundreds of thousands of telephone  operators,

  • weve lost gas-pumpers, elevator attendants, travel agents.

  • Tons of jobs have died but work persists.

  • What you realize when you look through those old reports is that it’s really easy for

  • us to see the jobs being replaced by machines.

  • It’s a bit harder to visualize the jobs that come from what happens next.

  • New technology creates jobs in a few ways.

  • There are the direct jobs for people who design and maintain the technology, and sometimes

  • whole new industries built on the technology.

  • But the part we tend to forget is the indirect effect of labor-saving inventions.

  • When companies can do more with less, they can expand, maybe add new products or open

  • new locations, and they can lower prices to compete.

  • And that means consumers can buy more of their product, or if we don’t want any more of

  • it, we can use the savings to buy other things.

  • Maybe we go to more sports events or out to dinner more often.

  • Maybe we get more haircuts or add more day-care for the kids.

  • This process is how our standard of living has improved over time and it’s always required

  • workers.

  • The key economic logic here is automation does indeed displace workers who are doing

  • work that got automated, but it doesn't actually affect the total number of jobs in the economy

  • because of these offsetting effects.

  • Warnings about theend of worktend to focus on this part and not all of this

  • -- like a widely cited study from 2013, “According to research conducted by Oxford

  • University, nearly half of all current jobs in America --” “47 percent of all our

  • jobs--” “47 percent of US jobs in the next decade or two, according to researchers

  • at Oxford, will be replaced by robots.”

  • That study assessed the capabilities of automation technology.

  • It didn’t attempt to estimate the actualextent or paceof automation or the

  • overall effect on employment.

  • Now, all this doesn’t mean that the new jobs will show up right away or that theyll

  • be located in the same place or pay the same wage as the ones that were lost.

  • All it means is that the overall need for human work hasn’t gone away.

  • Technologists and futurists don’t deny that’s been true historically, but they question

  • whether history is a good guide of what’s to come.

  • Fundamentally the argument is that this time it’s different.

  • That’s what I think.

  • Imagine a form of electricity that could automate all the routine work.

  • I mean, that’s basically what we are talking about here.

  • And so It’s going to be across the board.

  • And it is easy to underestimate technology these days.

  • In a 2004 book, two economists  assessed the future of automation and concluded that

  • tasks like driving in traffic would beenormously difficultto teach to a computer.

  • That same year, a review of 50 years of research concluded thathuman level speech recognition

  • has proved to be an elusive goal.”

  • And now?

  • Ok Google.

  • How many miles has google’s autonomous vehicle driven?”

  • According to Recode, that’s because the company announced its self-driving car project,

  • which was created in 2009, has racked up over two million miles of driving experience.”

  • This is the textbook chart of advancement in computer hardwareit’s the number

  • of transistors that engineers have squeezed onto a computer chip over time.

  • Already pretty impressive, but notice that this isn’t a typical scale: these numbers

  • are increasing exponentially.

  • On a typical linear scale it would look more like this.

  • It really is hard to imagine this not being massively disruptive.

  • And as the authors of The Second Machine Age point out, processors aren’t the only dimension

  • of computing that has seen exponential improvement.

  • The idea of acceleration in your daily life

  • when do you encounter that?

  • Maybe in a car for a few seconds?

  • In an airplane for seconds again?

  • The idea that something can accelerate for decades literally just continuously is just

  • not something that we deal with.

  • I mean, we think in straight lines.

  • But even though there’s been all this innovation, it’s not showing up in the data.

  • If we were seeing this big increase in automation we would see productivity growing much more

  • rapidly now than it usually does, and we are instead seeing the opposite.

  • Labor productivity is a measure of the goods and services we produce divided by the hours

  • that we work.

  • Over time it goes up - we do more with less labor.

  • Were more efficient.

  • If we were starting to see a ton of labor-saving innovation you’d expect this line to get

  • steeper, but when you look at productivity growth, you can see that it has been slowing

  • down since the early 2000s, and not just for the US.

  • It’s possible that new technologies are changing our lives without fundamentally changing

  • the economy.

  • So will this all change?

  • Will today’s robots and AI cause mass unemployment?

  • There’s reason to be skeptical, but nobody really knows.

  • But one thing we do know is that the wealth that technology creates, it isn’t necessarily

  • shared with workers.

  • When you account for inflation, the income of most families has stayed pretty flat as

  • the economy has grown.

  • One of the problems we've seen over the last 40 years is that we have seen all of this

  • rising productivity growth but actually hasn't been broadly shared, it's been captured by

  • a thin slice of people at the top of the income distribution.

  • Even if unemployment stays low, automation might worsen economic inequality, which is

  • already more extreme in the US than it is in most other advanced countries.

  • But technology isn’t destiny.

  • Governments decide how a society weathers disruptions, and that worries people on both

  • sides of the debate about the future of work.

  • Weve adopted policies that instead of really trying to counteract the trend caused by technology

  • and globalization and other things, weve in many cases exacerbated them.

  • Weve put a wind in the back of them and made them more extreme.

  • And that’s a big problem.

  • We will probably always be fascinated by the prospect of robots taking our jobs.

  • But if we  focus on things we can’t really control, we risk neglecting the things we can.

A decade ago, robots still seemed pretty limited.

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ロボットの台頭が仕事の終わりを意味しない理由 (Why the rise of the robots won't mean the end of work)

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    陳思源 に公開 2021 年 01 月 14 日
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