쉐도잉 연습: AI & Inequality | Daron Acemoglu: Big Tech poses risks as AI reshapes society - 영상으로 영어 말하기 배우기

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My name is Dharan Acemoglu.

I'm an institute professor at MIT.

I am an economist and I study inequality, political economy, and technology.

And my book, Power and Progress, Our Thousand Year Struggle Over Technology and Prosperity with Simon Johnson, is really at the center of these topics,

but especially in the context of new digital technologies and AI and who will benefit from them.

You know, AI is completely unique.

Its effects on the economy are going to be unique.

But on the other hand, we have so much knowledge from history about how similar breakthroughs in technology have worked out,

under what conditions they have been foundations for shared prosperity, when they have been tools in the hands of a narrow elite to exploit the rest of the population.

So there's a lot we can learn.

And in fact, the British Industrial Revolution,

where our prosperity and great technological improvements originate provides ample evidence on how sometimes things went very wrong

and poverty and inequality was created out of new technological breakthroughs

and how sometimes new technologies together with new institutions became the basis of shared prosperity.

When people hear my book, my general arguments from the tech industry, I get a love and hate message.

There are some people who think, you know, questioning what the tech industry is doing is sacrilege,

that, you know, we are killing the golden goose that's going to deliver prosperity to the United States.

And other people are clearly worried about what their industry their own firms are doing

and they're grappling towards a framework to make sense of it and that's that's what i'm hoping that we contribute to

ai machine learning

and all sorts of other really impressive digital technologies are going

to be as good as what we make of them

so it's wrong to ask the question what will ai do

to labor The right question is what we will decide to do with AI and how this will impact inequality.

There is tremendous potential to use AI for good, but that's not the path we're going.

And on our current path, I think AI and ML will be used for monitoring workers, reducing their autonomy.

They will be used for automation, sidelining labor, and perhaps disempowering the already weaker members of our society.

And if you look at over the last 40 years, we see many digital technologies deepen inequality because they automated work and displaced workers,

and they weren't used for creating new jobs for the same workers who were displaced from their jobs.

So I think those are the pitfalls that we should try to avoid with AI, and I think, again, we are not likely to avoid them unless we do a course correction.

I think today we have a more open conversation about how we can use new technologies for workers.

Labor unions have become more awake to the issues of digital technologies and AI.

And I think there's a broader openness in the U .S society

that was absent just four years ago about regulation and reducing the power of big tech.

I think all of those are useful developments.

I mean, I think it's impossible to predict what these amazingly impressive technologies are going to bring

but I would venture the following guesses.

I think we're going to see a lot of investment in AI and related technologies

and I think that they are going to be rolled out very quickly in some businesses

and there's going to be a lot of disappointment.

There's going to be a lot of disappointment

because in the middle of the hype many businesses are going to try to implement the technologies too fast.

In many cases, I think they're going to underappreciate what humans were doing

and overestimate what AI can do which is going to lead to disappointing results.

That doesn't mean that we're not going to see some impressive applications, we will, but I think on the whole,

we're not going to see the sort of amazing productivity promises become realized.

I am a big believer in the market process.

I don't think there's any alternative but the market to bring more innovation and better prosperity.

Central planning is not going to be our future, but that doesn't mean that the market is going to get everything right.

And one of the things that it doesn't get right is exactly distributional issues and issues related to the direction of technology.

If we leave it to the market, whether we're going to use AI for automating work or monitoring workers or creating new tasks, what does that mean?

It's not the market.

It's Google and Facebook and Amazon and Microsoft and OpenAI.

That's not the market.

We already live in a world in which there are very, very big corporations.

that have an enormous influence on our society, on the future of work, and they're not the market, and they have their own ideology, they have their own priorities,

they have their own profit motives, they have their own business models.

I don't think we can just think that there is a miraculous market that's going to solve all problems.

When you talk about inequality and worker control, people may get the impression that it's just businesses versus workers.

There's an element of that.

We live in a society in which there is conflict.

It's inevitable.

But I also think that there's a path both in the tech sector and in the broader corporate sector where

businesses can flourish while doing things that are good for their workers.

And I would say a key distinction is whether you see your workers as a cost or as a resource.

If they are a cost, you're going to just introduce more and more conflict, you're going to try to cut those costs.

If they are a resource, which I think they are, then businesses can try to flourish while increasing the productivity of their businesses, providing better tools to their workers,

improving their trainings, their skills.

Every political regime depends on information.

Every political regime depends on some degree of who controls information, how information is presented, who manipulates whom what agendas are encouraged

and AI is changing that completely and it's changing

that again in a very lopsided way

because AI is very much concentrated in the hands of a few people

and a few companies and that raises a big threat to democracy.

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이 영상으로 배울 실용적인 영어 말하기 기술

이 비디오는 경제학자 Daron Acemoglu의 인터뷰로, 복잡한 주제를 명료하게 전달하는 방법과 논리적 논증을 구성하는 말하기 기술을 연습할 수 있습니다. 특히 "AI와 불평등"과 같은 심도 있는 주제를 다루면서, 의견을 제시하고 예를 들어 설명하는 과정에서 자연스러운 영어 표현을 익힐 수 있습니다. shadowspeak 또는 영어 쉐도잉을 통해 발음 뿐만 아니라 말의 흐름까지 따라할 수 있어, 실제 대화에서도 자신감 있게 말할 수 있게 됩니다.

듣고 주목해야 할 발음 특징

영어의 연결 발음(linking)과 축약 발음(reductions)이 두드러지는 이 영상에서 주목할 점은 다음과 같습니다. "what we will"이 /wɑːtwɪl/로 연결되거나, "I think it's"가 /aɪθɪŋkɪts/로 축약되는 것을 들을 수 있습니다. 또한 "AI and ML"과 같이 약어를 사용할 때의 발음 강세도 중요합니다. 영상 영어 공부를 할 때 이런 세부적인 발음을 주의깊게 듣고 따라하면, 원어민처럼 자연스러운 말을 할 수 있습니다.

원어민처럼 말하는 비결: 리듬과 강세

이 발화자의 말은 논리적이고 강조가 뚜렷한 특징이 있습니다. "the right question is what we will decide to do with AI"에서 "right question"과 "decide to do"에 강세를 두어 중요한 내용을 강조합니다. 또한, 긴 문장을 쉼표나 연결사로 나누어 리듬을 유지하는 방법도 배울 수 있습니다. shadowspeaks 연습을 할 때는 발화자의 강세와 리듬을 정확히 따라가면서, 자신의 말에도 같은 느낌을 담아보세요. 이렇게 연습하면 단순히 발음을 따라하는 것이 아니라, 원어민의 말하기 스타일을 완전히 흡수할 수 있습니다.

이 영상을 통해 영어 쉐도잉을 꾸준히 연습하면, 복잡한 주제도 자연스럽게 표현할 수 있는 실력이 키워질 것입니다. 작은 발전부터 시작해서, 점점 더 원어민 수준의 말하기 실력을 쌓아가세요!

이 영상의 문법

화자가 가장 많이 쓰는 문형을 영상 속 실제 표현과 함께 정리했습니다.

문형	영상 속 표현
수동태 be + 과거분사 — 누가 하는지보다 무슨 일이 일어나는지에 초점	was created · were displaced · be rolled
현재완료 have/has + 과거분사 — 과거의 일이 지금도 관련이 있을 때	have worked · have been · have become

쉐도잉이란? 영어 실력을 빠르게 키우는 과학적 방법

쉐도잉(Shadowing)은 원래 전문 통역사 훈련을 위해 개발된 언어 학습 기법으로, 다언어 학자인 Dr. Alexander Arguelles에 의해 대중화된 방법입니다. 핵심 원리는 간단하지만 매우 강력합니다: 원어민의 영어를 들으면서 1~2초의 짧은 지연으로 즉시 소리 내어 따라 말하는 것——마치 '그림자(shadow)'처럼 화자를 따라가는 것입니다. 문법 공부나 수동적인 청취와 달리, 쉐도잉은 뇌와 입 근육이 동시에 실시간으로 영어를 처리하고 재현하도록 훈련합니다. 연구에 따르면 이 방법은 발음 정확도, 억양, 리듬, 연음, 청취력, 말하기 유창성을 크게 향상시킵니다. IELTS 스피킹 준비와 자연스러운 영어 소통을 원하는 분들에게 특히 효과적입니다.

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쉐도잉 연습: AI & Inequality | Daron Acemoglu: Big Tech poses risks as AI reshapes society - 영상으로 영어 말하기 배우기

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듣고 주목해야 할 발음 특징

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쉐도잉이란? 영어 실력을 빠르게 키우는 과학적 방법