Shadowing Practice: How Smart Organizations Will Use AI: Jevons Paradox & Workforce Impact - Learn English Speaking with Video
Ders oluşturuluyor...
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.
📺 Aynı Kanal
B21
Every Generation Thinks This Time Is Different: The AI Job Myth
Business EnglishUniversity StudentsWorking Adults
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
✨ Video Öner
C11
75 cümleler
What AI can (and can't) currently do in a real lab | Jennifer Doudna
IELTS PrepBusiness EnglishUniversity Students
C12
39 cümleler
The Global Power Play
Business EnglishUniversity 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 cümleler
The Great A.I. Debate: Should We Fear the Digital Revolution? [2015] | Intelligence Squared
IELTS PrepBusiness EnglishUniversity Students
C15
182 cümleler
How to Become an AI Product Manager in 2026 | Ex-Google, Microsoft
Business EnglishUniversity StudentsWorking Adults
C12
20 cümleler
Is prompt engineering dead? Advice on optimizing AI interactions | Amazon Web Services
Business EnglishUniversity StudentsWorking Adults
B21
339 cümleler
The (Overdue) Collapse of AI Layoffs (here's the proof)
Business EnglishInterview EnglishUniversity Students
C186 cümleler
The End of Human Mathematics? AI's Recent Breakthrough -- And What's Next
Business EnglishUniversity StudentsWorking Adults
C13
188 cümleler
NVIDIA GTC 2025 - Keynote Highlights by NVIDIA CEO Jensen Huang
Business EnglishUniversity StudentsWorking Adults
C11
85 cümleler
AI Can Write Code. And That’s the Problem.
Business EnglishUniversity StudentsWorking Adults
B21
546 cümleler
Do Elite Degrees Still Matter In The AI Era? | Jamie Beaton from Crimson Education | EP 410
Business EnglishUniversity StudentsWorking Adults
C11
87 cümleler
The AI Atrophy Problem How CIOs Fight It
Business EnglishUniversity StudentsWorking Adults
Bu dersin kelimeleri ve konuşma notları
Bu C1 seviyesindeki konuşma dersi “How Smart Organizations Will Use AI: Jevons Paradox & Workforce Impact” videosuna dayanıyor. En çok tekrarlanan kelimeler: demand, Jevons, cost, coal, smart. Bu videoda gölgeleme çalışması için 104 cümle ve 1240 kelime var. Konuşma bölümü 7:45 sürüyor. Konuşmacı dakikada yaklaşık 160 kelimeyle, günlük konuşmaya yakın doğal bir hızda konuşuyor. Kelimelerin %85’i İngilizcede en sık kullanılan 3.000 kelime arasında; geri kalanına başlamadan önce bakmakta fayda var.
Bu videodaki önemli kelimeler
Videodaki en ileri düzey 15 kelime, telaffuzu ve anlamıyla:
| Kelime | Telaffuz | Anlam |
|---|---|---|
| radiologist isim | /ˌɹeɪ.diːˈɒl.ə.d͡ʒɪst/ | radyolog |
| paradox isim | /ˈpæ.ɹəˌdɒks/ | paradoks, çelişki |
| spreadsheet isim | /ˈspɹɛd.ʃit/ | elektronik tablo, hesap tablosu |
| accountant isim | /əˈkaʊn.tənt/ | muhasebeci, muhasip |
| leverage isim | /ˈlɛv.(ə.)ɹɪd͡ʒ/ | kaldıraç kuvveti |
| assimilate fiil | /əˈsɪm.ɪ.leɪt/ | asimile etmek |
| augment fiil | /ɔɡˈmɛnt/ | çoğaltmak, artırmak |
| godfather isim | /ˈɡɑdfɑðɚ/ | vaftiz baba, kirve |
| humerus isim | /ˈhjuːməɹəs/ | karaca kemiği, kol kemiği |
| personalize fiil | /ˈpɜː.sə.nə.laɪz/ | kişiselleştirmek |
| sponge isim | /spʌnd͡ʒ/ | sünger |
| extinct sıfat | /ɪkˈstɪŋkt/ | söndürülmek |
| dire sıfat | /ˈdaɪ̯ə(ɹ)/ | uğursuz |
| tutor isim | /ˈtjuːtəː/ | lala |
| fracture isim | /ˈfɹæk.t͡ʃʰəː/ | kırık |
Duyacağınız deyimsel fiiller
| Kelime | Anlam |
|---|---|
| figure out fiil | açığa çıkarmak |
Bu videodaki dil bilgisi
Konuşmacının en çok kullandığı yapılar, videodaki sözcüklerin aynısıyla:
| Yapı | Videoda |
|---|---|
| İlgi cümlecikleri who / which + cümle — bir kişi ya da şey hakkında ek bilgi | ones who are · people who are · ones who can |
| Edilgen yapı be + fiilin üçüncü hâli — kimin yaptığı değil, ne olduğu önemli | were now freed · are employed |
Dikkat edilecek telaffuzlar
Konuşmacı don't, didn't, doesn't gibi kısaltılmış biçimleri 16 kez kullanıyor. Bunları duyduğunuz gibi kısa söyleyin.
- “th” sesleri: arithmetic /æɹɪθˈmɛtɪk/, godfather /ˈɡɑdfɑðɚ/
- “sh” ve “zh” sesleri: spreadsheet /ˈspɹɛd.ʃit/, nutshell /ˈnʌt.ʃɛl/, discretion /dɪˈskɹɛʃən/, coordination /kəʊˌɔːdɪˈneɪʃən/, supervision /ˌs(j)uːpəˈvɪʒən/
- Uzun kelimeler — vurguyu doğru yere koyun: radiologist /ˌɹeɪ.diːˈɒl.ə.d͡ʒɪst/, arithmetic /æɹɪθˈmɛtɪk/, adaptability /ədæptəˈbɪlɪti/, assimilate /əˈsɪm.ɪ.leɪt/, impractical /ɪmˈpɹæktɪkəl/
Türkçe konuşanların zorlandığı sesler:
- Kelime başındaki ünsüz kümesi — araya ünlü eklemeyin: spreadsheet /ˈspɹɛd.ʃit/, humerus /ˈhjuːməɹəs/, proximal /ˈpɹɒksɪməl/, prohibit /pɹəˈhɪbɪt/, prevail /pɹɪˈveɪl/
- /æ/ — “e”den daha açık: paradox /ˈpæ.ɹəˌdɒks/, arithmetic /æɹɪθˈmɛtɪk/, adaptability /ədæptəˈbɪlɪti/, impractical /ɪmˈpɹæktɪkəl/, fracture /ˈfɹæk.t͡ʃʰəː/
Bu videoyla nasıl çalışılır
- Videonun tamamını konuşmadan bir kez dinleyin ve bilmediğiniz kelimeleri not edin.
- 0,75× hızla başlayın, cümle cümle tekrar edin ve kolaylaşınca normal hıza dönün.
- Kendinizi kaydedin ve orijinaliyle karşılaştırın; radiologist, paradox, spreadsheet gibi kelimelere özellikle dikkat edin.
Gölgeleme Tekniği Nedir?
Gölgeleme, başlangıçta profesyonel tercüman eğitimi için geliştirilen ve çok dilli Dr. Alexander Arguelles tarafından popüler hale getirilen, bilim destekli bir dil öğrenme tekniğidir. Yöntem basit ama güçlüdür: ana dili İngilizce olan bir sesi dinler ve hemen yüksek sesle tekrar edersiniz — konuşmacıyı 1-2 saniye gecikmeyle takip eden bir gölge gibi. Pasif dinleme veya dilbilgisi alıştırmalarının aksine, gölgeleme beyninizi ve ağız kaslarınızı gerçek konuşma kalıplarını eşzamanlı olarak işlemeye ve yeniden üretmeye zorlar. Araştırmalar, telaffuz doğruluğu, tonlama, ritim, bağlı konuşma, dinleme anlama ve konuşma akıcılığını önemli ölçüde geliştirdiğini göstermektedir — bu da onu IELTS Konuşma hazırlığı ve gerçek dünya İngilizce iletişimi için en etkili yöntemlerden biri yapar.