Shadowing Practice: 3 Ways AI Will Completely Change Your Life by 2029 - Learn English Speaking with Video
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Look around us right now in 2026.
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Artificial intelligence is growing faster than ever before.
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Every single month, a new AI model comes out.
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Every week, there's a new feature like making real -looking videos, writing tough computer code, or speaking in perfect human voices.
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Because things are moving so fast, people mostly think the future of AI will just keep going up in a straight line.
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They think AI will always get bigger, faster, and smarter every single day.
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But if you ask computer engineers, scientists and electricity experts, they will tell you something very different.
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The future of AI is not a straight line.
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Between now and 2029, our world is standing at a giant turning point.
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Depending on how tech, electricity, power grids and human laws clash with each other, our future could go in three totally different directions.
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Now, before we look at how your daily life will change, here are the three big outcomes we are heading towards.
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Outcome 1 will be the super leap, where AI solves huge software and medical problems, doing full jobs all by itself like a digital worker.
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Outcome 2 will be the power wall, where AI runs out of physical electricity and computer parts,
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forcing the whole tech industry to slow down and rebuild.
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And outcome 3 is going to be the trust break, where making fake videos and audio become so cheap and easy that the internet breaks,
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changing our security jobs and laws forever.
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In each of these situations, the job market and the global economy will change in very different ways.
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Let's step into each of these three worlds so you can see what your life and career will actually look by 2029.
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Let's start with outcome 1, the super leap.
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This is the positive future where computer scientists fix all the AI's main problems very fast.
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In 2027, the way we use computer changes forever.
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Right now, you sit down and type questions into the chat box and the AI gives you the answer.
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But in the future, the chat box goes away.
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Instead, we use agent teams, groups of AI tools that work together nonstop.
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Like imagine you want to start a business.
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You do not write the code or build the website yourself.
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You simply tell an AI build a full food delivery app, add a payment system, test it for security bugs and launch it.
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The main AI breaks this big task into 20 smaller jobs.
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One AI writes the code, another designs the screen, another checks for error and another fixes the bug.
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You go to sleep.
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And when you wake up in the morning, your full software product is built and live on the internet.
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By 2028, this massive computer power leaves the screen and enters the real world.
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In science, finding a new life -saving medicine used to take 10 to 15 years of hard lab work.
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Under the super leap, AI can test millions of chemicals, mix on a computer every single minute.
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Scientists can see how chemicals react before even touching a real glass test tube.
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This gives us new medicines and better materials for solar panels in just months instead of decades.
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And by 2029, AI is all around you, invisible and smooth.
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You might wear light smart glasses or simple wireless earbuds.
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The AI listens to what you hear and sees what you see.
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It remembers every meeting you ever had, reminds you of a person's name when you forgot, warns you about your health before you feel sick,
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and manages your daily schedule.
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So in this big leap, this can be the world in next three years.
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In this world, the job market shifts from doing the work to managing the work.
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Companies no longer hire 10 junior software developers or designers.
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Instead, they hire one single AI director who manages a team of AI workers.
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We can see people building billion -dollar companies all by themselves.
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The world economy grows super fast because making digital thing cost almost zero.
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But there is a big risk.
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If a major AI internet network goes offline, all global businesses stop instantly.
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Now let's look at outcome 2, the power wall.
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What happens if AI development slows down?
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Not because the software is bad, but because we ran out of physical electricity.
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Right now, running giant AI system takes a massive amount of electricity.
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Data centers filled with thousands of computer chips use as much power as a small country.
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So now let's see the next three years in this era.
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By 2027, tech companies hit a physical wall.
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To build the next big AI model, companies need huge amount of power.
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But local electricity grids cannot give that much amount of power without causing blackout for normal homes.
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At the same time, factories cannot make advanced chips fast enough and data centers run out of water to cool their machines.
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The fast release of huge new AI suddenly stops.
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And by 2028, businesses fall into what experts call it the 80 -20 trap.
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Company realize that while AI can do 80 % of the job very fast, getting that final 20 % perfectly right without mistake is extremely hard.
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So for reference, if an AI writes an article, a human still has to check it.
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If an AI handles legal papers or medical records, a human expert must carefully read every single line to prevent dangerous mistakes.
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Because hiring human experts to check AI work is costly, companies realize AI does not save as much money as they originally thought.
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And by 2029, the entire tech industry changes its goal.
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Companies give up on building giant expensive AI systems that eat massive amount of electricity.
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Instead, they focus on making things highly efficient.
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They make tiny super fast AI models that run directly on your mobile phones or laptop without needing an internet connection.
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In this world, AI stop feeling like the world -changing science fiction movie and become a simple, helpful daily tool just like electricity or Wi -Fi.
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And what about the job market and economy in this world?
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Experienced human professionals become more valuable than ever because AI cannot be trusted 100%.
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Jobs for skilled humans, checkers, senior engineers, lawyers, and healthcare workers are very safe and high -paying.
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The economic boom moves away from pure software and shifts into physical industries, electricity grades, nuclear energy, chip making, and green power.
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The economy grows at a normal steady pace and businesses use a balanced mix of human experts and local AI tools.
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Finally, we have outcome 3, the trust break.
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What happens if AI moves faster than human society laws and security just can't handle it?
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To understand why this scenario is so real, just look at what is happening right now, today.
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Criminals are using short audio clips from social media to copy people's voices in just three seconds.
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In this real world scammers have used fake video calls of
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company bosses to trick employees into sending millions of dollars like there were many news around i've seen
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so what will happen if this continues
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and what will be the world in three years
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so by 2027 making super real fake videos fake voice calls
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and fake photo cost almost zero money anyone with a basic computer can download free AI tools
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and make a real looking video of anyone on earth saying or doing anything.
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When fake content becomes that cheap and instant, the internet faces a crisis called the dead internet.
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You can no longer trust a video or social media, a news report, or even a phone call from a friend or family member.
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Scammers use automated voice bots to call thousands of people at once, copying their relatives' voices to ask for emergency money.
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Now, because trust is broken, governments are forced to pass strict new laws.
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Like by 2027, every camera, phone, or news agency must use secure digital stamps inside their devices.
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This is to prove that the video or photo was taken by a real camera lens and was not made by AI.
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And by 2028, office jobs face huge problems.
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Simple starting jobs like basic data entry, basic computer coding, customer service chats and filing papers are taken over by AI very quickly.
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Colleges and governments training programs struggle to train millions of young workers fast enough.
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This creates a big gap between old -style workers and people who know how to manage AI tools.
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And by 2029, countries enter an AI cold war.
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Government decides that advanced AI models are dangerous national security tools.
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The United States, Europe, and Asia put strict bans on sharing advanced chips, computer hardware, and code.
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Instead of one open global internet, the digital world splits into closed, heavily guarded national networks.
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Now, obviously, in this era, we have to talk about the job market and economy as well.
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The job market sees a massive shake -up, like entry -level office jobs disappear rapidly,
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making it hard for fresh college graduates to start traditional corporate careers.
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But at the same time, new high -demand jobs open up, like cybersecurity security expert, digital fraud checker, hardware tester, and identity protection agent,
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the world economy becomes heavily protected by national borders.
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Taxes on tech items will rise initially
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and businesses have to spend billions of dollars on security and legal approval just to run safely.
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So now you know all the three outcomes.
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But the question is which of these three outcomes will actually happen by 2029?
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The truth is, the real future will not be 100 % of just one timeline.
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Instead, our world will be a mix of all three.
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We will experience the amazing scientific and medical breakthroughs from the super leap that was the first world we created,
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the real world electricity problem from the second world that was the power wall,
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and the digital security challenges from the third world that was the trust break.
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And no matter which outcome takes the lead, two things are clear.
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Your job will require managing AI, not just competing with it.
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Real economic values will belong to people who can solve real world problems and check if information is actually legitimate.
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And if I talk about the main lesson, it's simple.
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Tech itself is neutral.
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But how we prepare for it makes all the difference.
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The people who succeed in 2029 will not be the ones who ignore AI
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and they won't be the ones who blindly trust everything they see on the screen.
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The winners will be the people who learn how to manage AI tools,
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check real information, and adapt as the world changes because adaptation is the biggest thing.
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Now according to you which outcome do you think is most likely to happen over the next three years?
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Are we heading for the super leap, the power wall or the trust break?
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Drop your thoughts in the comment below, hit the like button if you enjoy the breakdown and subscribe
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so you don't miss out next deep dive into the future of technology.
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So this is Akash Fiyas, you are watching Sharian CI School.
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Till then, bye -bye.
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Woordenschat en spreektips bij deze les
Deze spreekles is gebaseerd op de video “3 Ways AI Will Completely Change Your Life by 2029”. Deze woorden komen het vaakst terug: outcome, computer, electricity, super, fast. Deze video bevat 130 zinnen en 1839 woorden om na te spreken. Het gesproken deel duurt 10:26. De spreker praat in een natuurlijk tempo van ongeveer 176 woorden per minuut, dicht bij een alledaags gesprek. 85% van de woorden hoort bij de 3.000 meest gebruikte Engelse woorden; de rest kun je beter vooraf bekijken.
Belangrijke woorden in deze video
15 woorden uit de video die het leren waard zijn, met uitspraak en betekenis:
| Woord | Uitspraak | Betekenis |
|---|---|---|
| leap werkwoord | /ˈliːp/ | springen, wippen |
| chip zelfstandig naamwoord | /t͡ʃɪp/ | fiche |
| hire werkwoord | /ˈhaɪɹ/ | huren |
| scientist zelfstandig naamwoord | /ˈsaɪəntəst/ | wetenschapper, wetenschapster |
| solve werkwoord | /sɒlv/ | oplossen |
| hardware zelfstandig naamwoord | /ˈhɑɹdˌwɛɹ/ | ijzerwaren |
| strict bijvoeglijk naamwoord | /stɹɪkt/ | strak |
| grid zelfstandig naamwoord | /ɡɹɪd/ | raster |
| ignore werkwoord | /ɪɡˈnɔː/ | negeren |
| relative zelfstandig naamwoord | /ˈɹɛl.ə.tɪv/ | familielid, bloedverwant |
| lesson zelfstandig naamwoord | /ˈlɛs.ən/ | les |
| carefully bijwoord | /ˈkɛɹf(ə)li/ | voorzichtig |
| fiction zelfstandig naamwoord | /ˈfɪkʃən/ | fictie |
| helpful bijvoeglijk naamwoord | /ˈhɛlp.fl̩/ | behulpzaam |
| worker zelfstandig naamwoord | /ˈwɝ.kɚ/ | arbeider, arbeidster |
Phrasal verbs die je zult horen
| Woord | Uitspraak | Betekenis |
|---|---|---|
| slow down werkwoord | afremmen | |
| come out werkwoord | /ˌkʌm ˈaʊt/ | uitkomen |
| go away werkwoord | weggaan | |
| sit down werkwoord | gaan zitten | |
| take over werkwoord | overnemen |
Grammatica in deze video
De structuren die de spreker het meest gebruikt, met de exacte woorden uit de video:
| Structuur | In de video |
|---|---|
| Lijdende vorm be + voltooid deelwoord — het gaat om wat er gebeurt, niet om wie het doet | is built · cannot be trusted · is broken |
| Betrekkelijke bijzinnen who / which + zin — extra informatie over een persoon of ding | people who know · people who can · people who succeed |
Uitspraak om op te letten
De spreker gebruikt 4 samentrekkingen en verkorte vormen, zoals can't, don't, I've. Spreek ze kort uit, zoals je ze hoort.
- De “th”-klanken: smooth /smuːð/, breakthrough /ˈbɹeɪk.θɹuː/
- De klanken “sh” en “zh”: fiction /ˈfɪkʃən/, efficient /ɪˈfɪʃənt/, shake /ˈʃeɪk/, artificial /ˌɑː.tɪˈfɪʃ.əl/, adaptation /ˌæd.æpˈteɪ.ʃən/
- Lange woorden — let op de klemtoon: electricity /ɪˌlɛkˈtɹɪsɪti/, artificial /ˌɑː.tɪˈfɪʃ.əl/, legitimate /lɪˈd͡ʒɪt.ɪ.mət/, developer /dɪˈvɛləpɚ/, invisible /ɪnˈvɪzəb(ə)l/
Klanken die Nederlandstaligen lastig vinden:
- Stemhebbende eindmedeklinker — /b/, /d/, /g/, /z/, /v/ niet verscherpen: solve /sɒlv/, grid /ɡɹɪd/, relative /ˈɹɛl.ə.tɪv/, fraud /ˈfɹɔːd/, remind /ɹəˈmaɪnd/
- /æ/ — opener dan de Nederlandse “e”: rapidly /ˈɹæpɪdli/, trap /tɹæp/, laptop /ˈlæp.tɑp/, react /ɹiːˈækt/, stamp /stæmp/
- /g/ — een harde plofklank, geen Nederlandse “g”: grid /ɡɹɪd/, ignore /ɪɡˈnɔː/, bug /bʌɡ/
Zo oefen je met deze video
- Luister de hele video één keer zonder te spreken en noteer de woorden die je niet kent.
- Begin op 0,75× snelheid, spreek zin voor zin na en ga terug naar normale snelheid zodra het makkelijk gaat.
- Neem jezelf op en vergelijk met het origineel; let daarbij op woorden als leap, chip, hire.
Wat is de Shadowing-techniek?
Shadowing is een wetenschappelijk onderbouwde taalleermethode die oorspronkelijk is ontwikkeld voor professionele tolkentraining en gepopulariseerd door polyglot Dr. Alexander Arguelles. De methode is eenvoudig maar krachtig: je luistert naar native Engelse audio en herhaalt het onmiddellijk hardop — als een schaduw die de spreker volgt met slechts 1–2 seconden vertraging. In tegenstelling tot passief luisteren of grammaticadrills, dwingt shadowing je hersenen en mondspieren om echte spraakpatronen tegelijkertijd te verwerken en te reproduceren. Onderzoek toont aan dat het de uitspraaknauwkeurigheid, intonatie, ritme, verbonden spraak, luisterbegrip en spreekvaardigheid aanzienlijk verbetert — waardoor het een van de meest effectieve methoden is voor IELTS Speaking-voorbereiding en echte Engelse communicatie.