Prática de Shadowing: AI & Inequality | Daron Acemoglu: Big Tech poses risks as AI reshapes society - Aprenda a falar inglês com vídeo
Escolha um modo de prática
Cada modo abre uma sala de prática em tela cheia.
74 frases
Se as frases estiverem muito curtas ou longas, clique em Edit para ajustá-las.
1
My name is Dharan Acemoglu.
2
I'm an institute professor at MIT.
3
I am an economist and I study inequality, political economy, and technology.
4
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,
5
but especially in the context of new digital technologies and AI and who will benefit from them.
6
You know, AI is completely unique.
7
Its effects on the economy are going to be unique.
8
But on the other hand, we have so much knowledge from history about how similar breakthroughs in technology have worked out,
9
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.
10
So there's a lot we can learn.
11
And in fact, the British Industrial Revolution,
12
where our prosperity and great technological improvements originate provides ample evidence on how sometimes things went very wrong
13
and poverty and inequality was created out of new technological breakthroughs
14
and how sometimes new technologies together with new institutions became the basis of shared prosperity.
15
When people hear my book, my general arguments from the tech industry, I get a love and hate message.
16
There are some people who think, you know, questioning what the tech industry is doing is sacrilege,
17
that, you know, we are killing the golden goose that's going to deliver prosperity to the United States.
18
And other people are clearly worried about what their industry their own firms are doing
19
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
20
ai machine learning
21
and all sorts of other really impressive digital technologies are going
22
to be as good as what we make of them
23
so it's wrong to ask the question what will ai do
24
to labor The right question is what we will decide to do with AI and how this will impact inequality.
25
There is tremendous potential to use AI for good, but that's not the path we're going.
26
And on our current path, I think AI and ML will be used for monitoring workers, reducing their autonomy.
27
They will be used for automation, sidelining labor, and perhaps disempowering the already weaker members of our society.
28
And if you look at over the last 40 years, we see many digital technologies deepen inequality because they automated work and displaced workers,
29
and they weren't used for creating new jobs for the same workers who were displaced from their jobs.
30
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.
31
I think today we have a more open conversation about how we can use new technologies for workers.
32
Labor unions have become more awake to the issues of digital technologies and AI.
33
And I think there's a broader openness in the U .S society
34
that was absent just four years ago about regulation and reducing the power of big tech.
35
I think all of those are useful developments.
36
I mean, I think it's impossible to predict what these amazingly impressive technologies are going to bring
37
but I would venture the following guesses.
38
I think we're going to see a lot of investment in AI and related technologies
39
and I think that they are going to be rolled out very quickly in some businesses
40
and there's going to be a lot of disappointment.
41
There's going to be a lot of disappointment
42
because in the middle of the hype many businesses are going to try to implement the technologies too fast.
43
In many cases, I think they're going to underappreciate what humans were doing
44
and overestimate what AI can do which is going to lead to disappointing results.
45
That doesn't mean that we're not going to see some impressive applications, we will, but I think on the whole,
46
we're not going to see the sort of amazing productivity promises become realized.
47
I am a big believer in the market process.
48
I don't think there's any alternative but the market to bring more innovation and better prosperity.
49
Central planning is not going to be our future, but that doesn't mean that the market is going to get everything right.
50
And one of the things that it doesn't get right is exactly distributional issues and issues related to the direction of technology.
51
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?
52
It's not the market.
53
It's Google and Facebook and Amazon and Microsoft and OpenAI.
54
That's not the market.
55
We already live in a world in which there are very, very big corporations.
56
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,
57
they have their own profit motives, they have their own business models.
58
I don't think we can just think that there is a miraculous market that's going to solve all problems.
59
When you talk about inequality and worker control, people may get the impression that it's just businesses versus workers.
60
There's an element of that.
61
We live in a society in which there is conflict.
62
It's inevitable.
63
But I also think that there's a path both in the tech sector and in the broader corporate sector where
64
businesses can flourish while doing things that are good for their workers.
65
And I would say a key distinction is whether you see your workers as a cost or as a resource.
66
If they are a cost, you're going to just introduce more and more conflict, you're going to try to cut those costs.
67
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,
68
improving their trainings, their skills.
69
Every political regime depends on information.
70
Every political regime depends on some degree of who controls information, how information is presented, who manipulates whom what agendas are encouraged
71
and AI is changing that completely and it's changing
72
that again in a very lopsided way
73
because AI is very much concentrated in the hands of a few people
74
and a few companies and that raises a big threat to democracy.
Baixar aplicativo
Tudo o que você precisa para falar fluentemente
Pronúncia com IANota em cada frase
Prática de IPADomine cada som
VocabulárioMonte seu banco de palavras
Jogo de vocabulárioAprenda brincando
Mesmo canal
FOR YOU
Vídeo recomendado
C11
105 frases
AI Governance Explained: Ethical, Transparent & Accountable AI for the Future
Daily ConversationUniversity StudentsWorking Adults
C141 frases
No, Really — Is A.I. a Bubble? | The Ezra Klein Show
Daily ConversationUniversity StudentsWorking Adults
C11
745 frases
Jack Ma: Love is Important In Business | Davos 2018
Daily ConversationUniversity StudentsWorking Adults
C114
20 frases
Alexandr Wang on what matters in an age of abundant intelligence
Daily ConversationUniversity StudentsWorking Adults
![The Great A.I. Debate: Should We Fear the Digital Revolution? [2015] | Intelligence Squared](https://img.youtube.com/vi/QWUeu3TLZN0/mqdefault.jpg)
C11
183 frases
The Great A.I. Debate: Should We Fear the Digital Revolution? [2015] | Intelligence Squared
Daily ConversationUniversity StudentsWorking Adults
C11
315 frases
How Disruptive Will Generative AI Be? A Micro-Level Analysis of Evidence and Expectations
Daily ConversationUniversity StudentsWorking Adults
B21
546 frases
Do Elite Degrees Still Matter In The AI Era? | Jamie Beaton from Crimson Education | EP 410
Daily ConversationUniversity StudentsWorking Adults
C18
75 frases
What AI can (and can't) currently do in a real lab | Jennifer Doudna
Daily ConversationUniversity StudentsWorking Adults
C11
83 frases
Leading AI CEOs Warn UN Security Council of Existential Risks | Sam Altman On AI Controls | N18G
Business EnglishDaily ConversationUniversity Students
C12
74 frases
How AI is helping brands identify consumer trends faster
Daily ConversationUniversity StudentsWorking Adults
C12
136 frases
Is ML Engineering Dead? (AI vs ML Engineer)
Daily ConversationUniversity StudentsWorking Adults
C13
85 frases
AI Will End Philosophy, Physicist Claims
Daily ConversationUniversity StudentsWorking Adults
Contexto e Fundo
No vídeo, o economista Daron Acemoglu, professor do MIT, discute como a IA e as grandes tecnologias podem moldar a sociedade, especialmente em relação à desigualdade. Ele compartilha insights de seu livro Power and Progress, comparando a revolução digital atual com a Revolução Industrial, e alerta para os riscos de que a IA seja usada para monitorar trabalhadores, reduzir sua autonomia e aprofundar desigualdades. A conversa também aborda a necessidade de correções no caminho atual e a importância de regulamentação e participação de sindicatos.
5 Frases Chave para Comunicação Diária
- "We have so much knowledge from history" – Útil para argumentar com base em experiências passadas.
- "There's a lot we can learn" – Ideal para mostrar disposição a absorver novas ideias.
- "I think we're going to see a lot of investment" – Frequentemente usada em discussões sobre tendências econômicas.
- "That doesn't mean that we're not going to see" – Excelente para contrariar uma ideia sem negar totalmente.
- "I am a big believer in the market process" – Perfeita para expressar convicções sobre sistemas econômicos.
Guia Passo a Passo para Shadowing
O shadowing em inglês é uma técnica poderosa para melhorar a pronúncia e a fluência. Aqui está como aplicá-la nesse vídeo:
- Escute e observe: Assista o vídeo sem legendas, focando na entonação de Acemoglu, que fala com clareza mas com ritmo moderado. Note como ele usa pausas para enfatizar pontos-chave.
- Repita imediatamente: Após cada frase curta (2-3 segundos), pause e repita em voz alta, tentando imitar o tom e a velocidade. Isso ajuda no shadow speech, treinando o cérebro a associar sons a significados.
- Use legendas como apoio: Se houver dificuldade, ative as legendas em inglês por 10 segundos, depois desative e repita. Isso fortalece a conexão entre o que se ouve e o que se lê.
- Foque nas frases chave: Escolha as 5 frases listadas acima e pratique-as repetidamente. Elas são exemplos de estruturações comuns na língua inglesa.
- Grave e compare: Grave sua voz e compare com o áudio original. Perceba diferenças de pronúncia e ajuste-as. Plataformas de shadowing site podem ajudar nessa etapa, mas até mesmo um celular serve.
Aprender inglês com vídeos como esse não só melhora a linguagem, mas também expõe o aluno a temas atuais. Com consistência, o shadowing se torna uma ferramenta essencial para se sentir mais confiante na comunicação.
Gramática neste vídeo
As estruturas que o falante mais usa, com as palavras exatas do vídeo:
| Estrutura | No vídeo |
|---|---|
| Voz passiva be + particípio passado — o foco está no que acontece, não em quem faz | was created · were displaced · be rolled |
| Present perfect have/has + particípio passado — uma ação passada que ainda importa agora | have worked · have been · have become |
O que é a Técnica de Shadowing?
Shadowing é uma técnica de aprendizado de idiomas com base científica, originalmente desenvolvida para o treinamento de intérpretes profissionais. O método é simples, mas poderoso: você ouve áudio em inglês nativo e repete imediatamente em voz alta — como uma sombra seguindo o falante com 1-2 segundos de atraso. Pesquisas mostram melhora significativa na precisão da pronúncia, entonação, ritmo, sons conectados, compreensão auditiva e fluência na fala.