Luyện nói tiếng Anh bằng Shadowing qua video: How Smart Organizations Will Use AI: Jevons Paradox & Workforce Impact
Chọn chế độ luyện tập
Mỗi chế độ mở một phòng luyện tập toàn màn hình.
104 câu
Nếu các câu quá ngắn hoặc quá dài, hãy bấm Edit để chỉnh sửa.
1
Here's a list of the top five companies that cut their way to the top.
2
Yes, these are the ones that figured out a way to move into the number one spot by shrinking rather than growing.
3
Well, The list is empty, you can see.
4
Certainly an organization can improve operational efficiency and cost by reducing fat and overhead.
5
In some cases, it's an essential step to prevent going out of business.
6
But if you want to win big, You won't do it by getting small.
7
You get there.
8
Bye.
9
Investing. by innovating. by growing.
10
These are the things that smart organizations already know.
11
They look at technology as an enabler, a way to achieve strategic competitive advantage.
12
The winners of tomorrow are the ones
13
that are figuring out how to leverage AI today to make their employees more capable and creative.
14
They see AI as augmented intelligence, rather than artificial.
15
Let's see why this is the case.
16
But before we do that, let's take a look at what seems to be the prevailing view of the impact of AI by many.
17
Jeffrey Hinton, often called the godfather of AI, is a truly brilliant man.
18
His work laid the foundation for so much of what we have today.
19
In 2016, he said, and I quote, "People should stop training radiologists now.
20
It's just completely obvious that in five years, deep learning is going to be better than radiologists." Hmm.
21
So that proximal humerus fracture looks familiar, but I digress.
22
All this sounds pretty dire, especially if you're a radiologist.
23
Your whole profession is going away.
24
So let's check in and see how that statement held up.
25
Well, it turns out that 10 years later, not only have radiologists not gone extinct,
26
but we actually are training more of them than we were when Hinton made that statement.
27
So is that because AI failed?
28
No, AI is actually doing amazing things now that we couldn't imagine a decade ago.
29
Part of the answer lies in this thing called Jevons paradox.
30
Let's take a look at that and see what it is.
31
Way back in 1865, while studying coal use in England,
32
a guy named William Stanley Jevons observed that more efficient steam engines reduced the amount of coal needed to power them.
33
So you might think demand for coal would go down.
34
But the opposite occurred.
35
More industries turned to using this more efficient energy source to get more things done.
36
and total coal consumption actually rose instead of falling.
37
In other words, As efficiency went up, Costs went down.
38
and demand increased.
39
That's Jevons' paradox in a nutshell.
40
We all learned in Econ 101 that as costs go down, Demand goes up.
41
That all makes sense, right?
42
Well, cheap energy meant they could start to do things that would have been cost -prohibited before.
43
It allowed them to dream up some new use cases that no one ever considered because it would have been impractical previously.
44
All of that just increases demand even more.
45
But we're talking about AI here, not coal.
46
So where's the connection with all of this?
47
Just hang in here with me.
48
Let's take a look at spreadsheet software.
49
Automated arithmetic reduced accounting effort per task.
50
So now we have spreadsheets who needs accountants.
51
Nobody needs to just sit around and do all that arithmetic.
52
Jevons teaches us that as efficiency goes up, Cost goes down demand increases, and that's exactly what happened again.
53
Demand for financial analysis exploded.
54
All of these accountants that used to labor over their arithmetic were now freed up to do higher -level thinking.
55
Entirely new categories of work emerged.
56
In the end, we needed more, not less, of these people, but with a higher level of skill.
57
Now how about AI?
58
What kind of smarter work could we do if we made use of AI?
59
Well, one area is entirely new categories of work.
60
Things that we never did before.
61
Jobs like AI product managers, safety engineers, prompt engineers.
62
We didn't need those in the past because we didn't have the AI that needed all of those things.
63
So it's actually creating new jobs in support of the AI itself.
64
Expansion of long -tail services.
65
Things that were previously too expensive.
66
Think of stuff like custom tutoring, niche legal analysis, personalized healthcare support.
67
That's something that really only a few people could afford, but now would be available potentially to everyone.
68
And then we're going to raise our expectations for speed.
69
quality, and availability, creating more work around integration, oversight, compliance, and trust.
70
Rather than fewer jobs overall, Jevons' paradox would indicate that what we would have would be fewer of these routine,
71
low discretion roles and more of the high context, high accountability roles such as problem framing and goal setting,
72
things where we need a human in the loop to do the decision making, AI supervision, evaluation and governance, customer facing roles where trust matters,
73
and we need something with an emotional intelligence as well, and then the ability to do cross -functional coordination.
74
So think of it this way: AI reduces the labor required per task, but dramatically expanding what is economically feasible to do.
75
It can increase the total amount of work humans are employed to support.
76
In other words, Efficiency goes up.
77
Cost goes down.
78
and demand increases. for people.
79
And we need more people then, not less, because of AI.
80
Smart companies understand Jevons paradox and they realize they're going to need more
81
and smarter employees to run their operations that leverage AI.
82
And smart employees will be the ones who are able to do these kinds of AI era skills.
83
I think one of the most important is adaptability and flexibility.
84
We don't know where all of this is going to go, so the people who are light on their feet and able to adjust, will be some of the winners.
85
You need to be lifelong learners as well.
86
You've got to enjoy this technology, enjoy the ride, soak it all up like a sponge
87
because the information is coming at us faster and faster and the ones who can learn and assimilate
88
and adjust will be again the winners.
89
They need to be able to think critically.
90
AI doesn't always get everything right.
91
And even when it does, it doesn't mean that's what we wanted it to do.
92
So we have to think and we have to be the ones that are in control.
93
The human in the loop ultimately makes the decisions.
94
We need to decide what the system should do and why it should do it.
95
We apply meaning to it.
96
And the system then does whatever we ask and does it at speed.
97
And don't forget creativity.
98
Because again, we don't know what the possibilities are here.
99
So people who can think outside the box, you're actually going to have more time to do that because AI is going to automate much of the mundane stuff.
100
So you have more time to think the big picture thoughts.
101
The not so smart organizations will be
102
so busy trying to cut their way to the top that they'll miss this train that's already pulling away from the station.
103
ways to innovate and branch into new use cases and business opportunities where AI provides a competitive advantage.
104
And the smart employees will be the ones who are skilling up to take advantage of this new dynamic.
Tải Ứng Dụng
Mọi thứ bạn cần để nói trôi chảy
Chấm điểm AIChấm từng câu nói
Luyện IPAThành thạo mọi âm
Từ vựngMở rộng vốn từ
Game Từ vựngHọc qua chơi
📺 Cùng kênh
B21
Every Generation Thinks This Time Is Different: The AI Job Myth
Daily ConversationWorking Adults
C12
What is Event Driven Architecture (EDA)?
Daily ConversationUniversity StudentsWorking Adults
C11
Agentic AI Frameworks Explained: Workflows, Multi-Agent, & Production
Daily ConversationUniversity StudentsWorking Adults
C12
What Is Jev? The AI Model That Doesn't Generate Text
Daily ConversationUniversity StudentsWorking Adults
C18
AI, Machine Learning, Deep Learning and Generative AI Explained
Daily ConversationUniversity StudentsWorking Adults
C11
Spec-Driven Development: AI Assisted Coding Explained
Daily ConversationUniversity StudentsWorking Adults
C15
AI Agents vs Business Rules: Which Should Make Decisions?
Daily ConversationUniversity StudentsWorking Adults
C13
AI & Education: Generative AI & the Future of Critical Thinking
Business EnglishUniversity StudentsWorking Adults
C12
EDR vs. EPP vs. NGAV
Business EnglishWorking Adults
C13
MCP vs ADK: How Modern AI Agents Connect and Work Together
University StudentsWorking Adults
C11
Cybersecurity Architecture: Data Security
Business EnglishUniversity StudentsWorking Adults
C113
The 7 Skills You Need to Build AI Agents
Business EnglishUniversity StudentsWorking Adults
C111
What are AI Agents?
Business EnglishUniversity StudentsWorking Adults
C16
Cybersecurity Architecture: Five Principles to Follow (and One to Avoid)
Business EnglishUniversity StudentsWorking Adults
C11
Zero Trust Explained in 4 mins
Business EnglishUniversity StudentsWorking Adults
✨ Video gợi ý
C15
103 câu
Everyone Is Wrong About AI Coding
Business EnglishUniversity StudentsWorking Adults
C11
725 câu
Stanford Leadership Forum 2026: Rewiring the Workforce in the Age of AI
Business EnglishUniversity StudentsWorking Adults
C14
76 câu
The Limitless AI Lie. The Bubble Is Slowly BURSTING.
Business EnglishDaily ConversationUniversity Students
C11
315 câu
how AI broke the SWE Career Ladder
Business EnglishInterview EnglishUniversity Students
C1465
25 câu
The Human Economy in the Age of AI | Ben Pascut | TEDx
IELTS PrepBusiness EnglishUniversity Students
C11
141 câu
How AI is Changing Data Scientist's Workflow
Business EnglishUniversity StudentsWorking Adults
C19
171 câu
ENGLISH SPEECH | JD VANCE: The Future of AI (English Subtitles)
IELTS PrepBusiness EnglishUniversity Students
C120 câu
Alexandr Wang on what matters in an age of abundant intelligence
Daily ConversationUniversity StudentsWorking Adults
C13
54 câu
Did Google just kickstart the intelligence explosion?
American AccentBusiness EnglishDaily ConversationUniversity Students
C111
145 câu
Which Commercial property sectors will benefit from AI? | The Market in Minutes
Business EnglishUniversity StudentsWorking Adults
C15
317 câu
Give Me 18 Minutes and I’ll Make you Dangerously Smart (with AI)
Business EnglishUniversity StudentsWorking Adults
Về Bài Học Này
Bài học hôm nay tập trung vào cách mà các tổ chức thông minh sử dụng trí tuệ nhân tạo (AI) để nâng cao hiệu suất làm việc và khả năng sáng tạo của nhân viên. Chúng ta sẽ tìm hiểu cách mà AI không chỉ là một công cụ, mà còn là một nguồn lực mạnh mẽ để phát triển và cải thiện quy trình làm việc. Bạn sẽ được trải nghiệm cách mà các khái niệm như Jevons Paradox liên quan đến việc sử dụng AI trong công việc hàng ngày.
Từ Vựng & Cụm Từ Quan Trọng
- Trí tuệ nhân tạo (AI): Công nghệ giúp máy tính thực hiện các nhiệm vụ thông minh.
- Hiệu suất (efficiency): Khả năng đạt được kết quả mong muốn với ít tài nguyên hơn.
- Chi phí (cost): Số tiền cần thiết để thực hiện một công việc hay mua một sản phẩm.
- Cạnh tranh (competitive advantage): Lợi thế mà một tổ chức có được so với đối thủ.
- Phân tích tài chính (financial analysis): Quá trình đánh giá tình hình tài chính của một tổ chức.
- Đổi mới (innovation): Tạo ra những sản phẩm hoặc dịch vụ mới nhằm cải thiện và phát triển.
Mẹo Thực Hành
Khi thực hành với video này, hãy chú ý đến tốc độ và ngữ điệu của người nói. Bạn có thể sử dụng phần mềm shadowing để dễ dàng nghe và bắt chước cách phát âm tiếng Anh chuẩn. Cố gắng lặp lại các câu nói ngay sau khi nghe, điều này sẽ giúp bạn cải thiện khả năng phản xạ trong giao tiếp.
Nếu video có tốc độ nhanh, hãy tạm dừng sau mỗi câu để bạn có thời gian ghi nhớ và lặp lại. Thực hành thường xuyên không chỉ giúp bạn nâng cao kỹ năng ngôn ngữ mà còn khiến bạn tự tin hơn khi giao tiếp. Hãy nhớ rằng, mỗi lần bạn thực hành, bạn đang tiến gần hơn đến việc trở thành một người nói tiếng Anh lưu loát!
Ngữ pháp trong video
Những cấu trúc người nói dùng nhiều nhất, kèm đúng cụm từ trong video:
| Cấu trúc | Trong video |
|---|---|
| Mệnh đề quan hệ who / which + mệnh đề — thêm thông tin về người hoặc vật | ones who are · people who are · ones who can |
| Câu bị động be + quá khứ phân từ — nhấn vào việc xảy ra, không phải người làm | have been cost · were now freed · are employed |
Phương Pháp Shadowing Là Gì?
Shadowing là kỹ thuật học ngôn ngữ có cơ sở khoa học, ban đầu được phát triển cho chương trình đào tạo phiên dịch viên chuyên nghiệp và được phổ biến rộng rãi bởi nhà đa ngôn ngữ học Dr. Alexander Arguelles. Nguyên lý cốt lõi đơn giản nhưng cực kỳ hiệu quả: bạn nghe tiếng Anh của người bản xứ và lặp lại to ngay lập tức — như một "cái bóng" (shadow) đuổi theo người nói với độ trễ chỉ 1–2 giây. Khác với luyện ngữ pháp hay học từ vựng bị động, Shadowing buộc não bộ và cơ miệng phải đồng thời xử lý và tái tạo ngôn ngữ thực tế. Các nghiên cứu khoa học xác nhận phương pháp này cải thiện đáng kể phát âm, ngữ điệu, nhịp điệu, nối âm, kỹ năng nghe và độ lưu loát khi nói — đặc biệt hiệu quả cho người luyện IELTS Speaking và muốn giao tiếp tiếng Anh tự nhiên như người bản ngữ.