シャドーイング練習: AI & Inequality | Daron Acemoglu: Big Tech poses risks as AI reshapes society - 動画で英語スピーキングを学ぶ

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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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このクリップのスピーキング目標

経済やテクノロジーに関する議論をスラストよく伝えるための、英語スピーキング練習に最適な内容です。特に、複雑なアイデアを明確に述べるための構成力や、抽象的な概念を説明する際の語彙力を養います。IELTS スピーキング対策でも重要な「議論の展開」や「反論の提示」のテクニックも含まれています。

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「...is really at the center of these topics」（...がこれらのトピックの核心にある）
「under what conditions they have been foundations for...」（どのような条件下で...の基礎となったか）
「grappling towards a framework to make sense of it」（それを理解するための枠組みを模索する）
「the pitfalls that we should try to avoid」（避けるべき落とし穴）
「venture the following guesses」（以下のような推測を述べる）

弱点を直そう

このビデオは、shadowing（シャドーイング）練習に最適です。特に、長い文を流暢に話すためのリズムとイントネーションの調整が必要です。発音のポイントとしては、「inequality」「autonomy」「productivity」などの多音節語のアクセント位置を確認しましょう。また、「you know」「I think」などのフィラーワードの使い方も、自然な会話のリズムを作るコツです。英語シャドーイングのサイトで繰り返し練習することで、これらのポイントをマスターできます。

市場と技術の関係についての議論は、shadowspeakの練習にもぴったりです。文の構造を覚えながら、論理的な展開を口に出すことで、スピーキングの流暢さが向上します。ぜひ、このビデオを使って、深い話題も自信を持って話せる力をつけましょう。

この動画の文法

話し手がよく使っている文型を、動画の実際の表現とともに紹介します。

文型	動画での表現
受動態 be + 過去分詞 — 誰がするかより、何が起きるかに焦点を当てる	was created · were displaced · be rolled
現在完了形 have/has + 過去分詞 — 過去の出来事が今も関係している	have worked · have been · have become

シャドーイングとは？英語上達に効果的な理由

シャドーイング（Shadowing）は、もともとプロの通訳者養成プログラムで開発された言語学習法で、多言語習得者として知られるDr. Alexander Arguelles によって広く普及されました。方法はシンプルですが非常に効果的：ネイティブスピーカーの英語を聞きながら、1〜2秒の遅延で声に出してすぐに繰り返す——まるで「影（shadow）」のように話者を追いかけます。文法ドリルや受動的なリスニングと異なり、シャドーイングは脳と口の筋肉が同時にリアルタイムで英語を処理・再現することを強制します。研究により、発音精度、抑揚、リズム、連音、リスニング力、そして会話の流暢さが大幅に向上することが確認されています。IELTSスピーキング対策や自然な英語コミュニケーションを目指す方に特におすすめです。

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シャドーイング練習: AI & Inequality | Daron Acemoglu: Big Tech poses risks as AI reshapes society - 動画で英語スピーキングを学ぶ

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シャドーイングとは？英語上達に効果的な理由