Практика Shadowing: How Smart Organizations Will Use AI: Jevons Paradox & Workforce Impact - Изучайте разговорный английский по видео
Создание урока...
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.
📺 Тот же канал
C12
What is Event Driven Architecture (EDA)?
Business EnglishUniversity StudentsWorking Adults
C12
What Is Jev? The AI Model That Doesn't Generate Text
Business EnglishUniversity StudentsWorking Adults
C18
AI, Machine Learning, Deep Learning and Generative AI Explained
Business EnglishUniversity StudentsWorking Adults
C11
Spec-Driven Development: AI Assisted Coding Explained
Business EnglishUniversity StudentsWorking Adults
C15
AI Agents vs Business Rules: Which Should Make Decisions?
Business EnglishUniversity 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
✨ Рекомендуемое видео
C11
87 предложений
The AI Atrophy Problem How CIOs Fight It
Business EnglishUniversity StudentsWorking Adults
C13
188 предложений
NVIDIA GTC 2025 - Keynote Highlights by NVIDIA CEO Jensen Huang
Business EnglishUniversity StudentsWorking Adults
C11
315 предложений
how AI broke the SWE Career Ladder
Business EnglishUniversity StudentsWorking Adults
B21
339 предложений
The (Overdue) Collapse of AI Layoffs (here's the proof)
Business EnglishInterview EnglishUniversity Students
C11
315 предложений
How Disruptive Will Generative AI Be? A Micro-Level Analysis of Evidence and Expectations
IELTS PrepBusiness EnglishUniversity Students
C186 предложений
The End of Human Mathematics? AI's Recent Breakthrough -- And What's Next
Business EnglishUniversity StudentsWorking Adults
C15
182 предложений
How to Become an AI Product Manager in 2026 | Ex-Google, Microsoft
Business EnglishUniversity StudentsWorking Adults
C12
39 предложений
The Global Power Play
Business EnglishUniversity StudentsWorking Adults
B21
49 предложений
AI & Future Jobs: Skills You NEED Now!
Business EnglishUniversity StudentsWorking Adults
C11
74 предложений
AI & Inequality | Daron Acemoglu: Big Tech poses risks as AI reshapes society
IELTS PrepBusiness EnglishUniversity Students
Контекст и основные идеи видео
Видео рассказывает о том, как умные компании используют ИИ не для замены сотрудников, а для усиления их возможностей. Оно затрагивает парадокс Джевонса — явление, когда повышение эффективности технологии не уменьшает, а увеличивает спрос на неё. Например, с появлением таблиц Excel работа бухгалтеров стала эффективнее, но вместо сокращения их числа выросла потребность в финансовом анализе. Это важный контекст для понимания современных трендов в бизнесе и технологиях, который также поможет в практике разговорного английского, так как разговор затрагивает актуальные темы и профессиональный лексикон.
5 ключевых фраз для повседневной коммуникации
- "cut their way to the top" — "достичь вершины, сокращая расходы" (пример: "Some companies try to cut their way to the top, but it's not always effective").
- "strategic competitive advantage" — "стратегическое конкурентное преимущество" (пример: "Leveraging AI gives a strategic competitive advantage").
- "augmented intelligence" — "увеличенный интеллект" (в контексте ИИ: "AI should be seen as augmented intelligence, not a replacement").
- "prevailing view" — "преобладающее мнение" (пример: "The prevailing view about AI is changing rapidly").
- "cost-prohibitive" — "недоступный по цене" (пример: "Old technologies were cost-prohibitive for small businesses").
Пошаговое руководство по shadowing для этого видео
Shadow speech — отличный способ улучшить произношение и интонацию. Вот как работать с этим видео:
- Посмотрите видео без субтитров, чтобы понять общую идею. Обратите внимание на ритм и акценты спикера.
- Выберите отрывок длиной 30 секунд (например, про парадокс Джевонса). Прослушайте его, затем повторите за спикером сразу же, стараясь копировать интонацию и скорость — это shadowing. Делайте это 5-7 раз.
- Используйте транскрипцию (если есть), чтобы проверить, какие слова вы не расслышали. Запомните их и повторите отрывок снова.
- Запишите себя и сравните с оригиналом. Обратите внимание на различия в произношении и поправьте их.
Такой подход поможет вам не только улучшить разговорный английский, но и научиться понимать сложные темы на слух. Для практики можно использовать shadowing site, где собраны подобные видео с транскрипциями.
Грамматика в этом видео
Конструкции, которые говорящий использует чаще всего, с точными словами из видео:
| Конструкция | В видео |
|---|---|
| Придаточные определительные who / which + предложение — уточнение о человеке или предмете | ones who are · people who are · ones who can |
| Пассивный залог be + причастие прошедшего времени — важно, что происходит, а не кто это делает | were now freed · are employed |
Что такое техника Shadowing?
Shadowing — это научно обоснованная техника изучения языка, изначально разработанная для подготовки профессиональных переводчиков и популяризированная полиглотом доктором Александром Аргуэльесом. Метод прост, но эффективен: вы слушаете аудио на английском от носителей языка и немедленно повторяете вслух — как тень, следующая за говорящим с задержкой в 1–2 секунды. В отличие от пассивного прослушивания или грамматических упражнений, Shadowing заставляет мозг и мышцы рта одновременно обрабатывать и воспроизводить реальные речевые паттерны. Исследования показывают, что это значительно улучшает точность произношения, интонацию, ритм, связную речь, понимание на слух и беглость речи — что делает его одним из самых эффективных методов для подготовки к IELTS Speaking и реального общения на английском.