Shadowing Practice: Will AI Take Your Job in the Next 10 Years? Wrong Question | Vinciane Beauchene | TED - Learn English Speaking with YouTube

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Back in the 50s, Alan Turing came up with an idea.
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Back in the 50s, Alan Turing came up with an idea.
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If you couldn't tell if you were talking to a machine or a human, it meant the machine must be intelligent.
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He coined the Turing test.
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Today, most chatbots pass the test easily.
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But here's the catch.
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I believe the test was wrong.
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Because talking isn't what's going to change the world.
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Doing is. That's why I ask a slightly different question to the leaders I work with.
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On a daily basis, my role is to reshape organizations, trying to find the right mix of strategy, tech and talent.
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And my obsession is to make sure that talents do not get out of the equation.
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So the question I ask my clients is: if an AI could take over all of your team's tasks, who would you keep and why?
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That question is strategic.
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And the answer matters to me, not just intellectually, but because I have two daughters at home.
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They are five and nine.
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And right now, as you can see, they feel invincible.
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But I keep wondering: What is the world of work they will step into?
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We need to build a future where humans matter more, not less.
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Now let me try to illustrate how this is playing out in the field.
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A consumer goods client of mine is all in on AI.
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They didn't want to just deploy the next algo.
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They wanted to rethink the selling process itself.
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The trigger was agents.
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Have you heard about agents?
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They are the latest generation of AI: more autonomous, able to connect across systems, to plan, to take action, to learn, to adapt.
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The James Bond of AI.
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And applied to the selling process, you get an agent that is able to target the customer, make recommendations, negotiate, close the deal.
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All this with no human intervention.
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A fully autonomous sales engine.
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And it was technically feasible.
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But then an exec asked, "Hmm, if the machine does all of this, then what remains for humans?" This cracked everything open because when we looked deeper at their most loyal customers, we saw they weren’t sticking around because of prices or products but because of how the sales rep made them feel.
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So we flipped the model around.
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Humans were no longer going to be about pushing products.
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They were going to be about building relationship, belonging, loyalty.
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Very concretely, this meant new skills, new incentives, a very different mindset.
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Well it changed everything.
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But it worked.
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Because in the age of AI, human value isn't gone.
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It's just moved.
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Now I’m not talking about copilots anymore.
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For a while the narrative has been AI will augment us, not replace us.
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Well this is not where the tech is going today.
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And I believe we have real hard work to do if we want this narrative to stay true.
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So I'll say a few words about what I think needs to be done in a second.
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But first, let me tackle three myths that I think are holding us back.
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I call them "head in the sand" ideology.
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Number one.
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"All of this is overblown. We'll adapt." Yes. We've adapted to electricity, the industrial revolution, the internet.
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But we've done so on the back of generations that did not have the training nor the time to adapt.
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And in the case of this revolution, time is of the essence.
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You may think you have time because agents are just emerging.
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And it's a fact.
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Our research shows that today only 13 percent of companies have embedded agents in their workflows.
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But tech moves exponentially.
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Humans, they crawl linearly.
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If you don't prepare now, you'll struggle to keep up.
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And I'm not talking about science fiction.
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I'm not talking about AGI, artificial general intelligence, this moment where AI will be smarter than us.
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I'm referring here to ACI, artificial capable intelligence.
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The moment when AI will be able to take on ambiguous, complex goals with minimal oversight.
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And while AGI is speculative, ACI is a deadline.
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While we spend hours debating about superintelligence and consciousness, we miss the milestones that ACI is meeting with increasing frequency.
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ACI will change how work is done and by whom.
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Let's shape it, not wait and see.
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Now myth number two.
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"Soft skills are our sweet spot." Yes, it's lovely to believe that empathy, creativity are uniquely ours.
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But evidence says otherwise.
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More and more humans like to interact with AI because they feel it's more empathic.
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And why not?
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I mean, AI doesn't get tired, doesn't get cranky, doesn't judge you.
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So this moat we thought was ours, it's shrinking.
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And we need to stop asking what AI can't do and focus on where humans make a difference and why.
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At this stage, I'm sure you would love me to come up with the list of human qualities that will remain ours forever.
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But my point is, there is no universal list.
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Each company needs to figure it out based on its strategic positioning.
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This is hard, uncomfortable work, but it's work that you as leaders need to take on.
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Now myth number three.
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My preferred one. I'm French.
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"We need to protect jobs." Yes. I see where this one is coming from.
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Today, 41 percent of employees believe that their job will vanish in the next decade because of AI.
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But protecting jobs is like anchoring a boat in a storm.
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Jobs are fixed.
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The human potential to grow and adapt, on the other hand, is not.
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This is where we need to invest.
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The challenge is our organizations are not geared for that today.
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Org charts are static.
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Career paths are narrow.
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Training is occasional.
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This system will fall apart the day that the boundaries of jobs start melting away fast.
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So what do we need to do?
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Let me take you to an ideal company.
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Not a theoretical one, just the blend of the boldest clients I've worked with.
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First, they don't start with tech.
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They start with strategy.
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They focus on the outcomes that truly differentiate them on the market.
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They understand how agents will allow them to deliver against those outcomes in totally different ways.
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And they look at where people still make a difference for the better.
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As you can see, this is not incremental redesign of your operating model.
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It's radical AI-first reinvention.
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And we did this work for an industrial goods client of mine.
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Imagine having to go through 50 “hack a future” workshops, looking at how AI is going to disrupt each of your businesses, each of your function.
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Comfortable? It is not.
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But it allowed the leaders to align on a vision of where agents win, people matter and how best to pair them.
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Now once you have this vision, you want to translate it into a workforce model.
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How many people do I need?
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With what skills?
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No more guesswork, just informed, intentional reinvention.
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A multiyear skills forecast.
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And this is something we built for a consumer goods client that was facing a massive challenge.
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Imagine having to reformulate your entire product portfolio while keeping the leadership and innovation.
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Of course, AI unlocked the productivity that was required, but the work was much deeper.
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They needed to reinvent the role of the researcher.
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From chemist to data-driven biologist, from solo expert to multifunctional teammates.
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And they made it happen because they mapped very precisely the future skills that they needed, and they built a very effective upskilling and mobility engine.
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Then you want to publicly commit to taking your talents to their fullest potential.
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Now I know what you're going to tell me.
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Vinciane, why would we invest in talent if an AI can do their job faster, cheaper and without complaining?
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Well because the day that interacting with an AI becomes the new norm, a commodity, the interaction with humans is going to take an entire new meaning.
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Trust, authenticity, accountability.
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Those are the values we will anchor on.
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So the smartest companies will invest in talent.
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Not only tech talent, all talent.
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Not once, but systematically.
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And they will protect time to learn.
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Because today, while freelancers spend on average four hours per week learning, employees spend none.
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So no, the future isn't about being more human.
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It's about building the systems that will allow humans to do what matters most.
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This is not a story about job loss.
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It is a story about human differentiation.
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AI will keep on climbing. That is not up to us.
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But how fast we climb with it, that is up to us.
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So we need to stop asking: Will there still be jobs for humans?
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And focus on answering: What do we want humans to be best at?
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Because in the age of AI, being human isn't a fallback, it's a practice.
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Let's make it exceptional.
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Thank you. (Applause)
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Context & Background

In a thought-provoking TED talk, Vinciane Beauchene challenges the prevailing narrative surrounding artificial intelligence and its impact on the workforce. She references seminal ideas, like the Turing test, to highlight how AI has evolved and the complex questions it raises about human labor. Rather than focusing on whether AI will replace jobs, she urges us to consider what remains uniquely human in a landscape increasingly dominated by technology. Her insights suggest that the future will require us to rethink our roles, emphasizing relationships and the human touch in professional settings.

Top 5 Phrases for Daily Communication

  • “Who would you keep and why?” – A question prompting reflection on human value in work.
  • “Humans matter more, not less.” – A powerful reminder of the importance of human skills.
  • “Building relationships, loyalty, and belonging.” – Key aspects of successful interactions.
  • “If the machine does all of this, then what remains for humans?” – A critical question about AI's role.
  • “New skills, new incentives, a very different mindset.” – Emphasizes the need for adaptability in our approaches.

Step-by-step Shadowing Guide

To effectively use the shadowing technique based on Vinciane Beauchene's talk, follow this structured approach, perfect for your IELTS speaking practice:

  1. Listen Attentively: Watch the video and listen for expressions and phrases that stand out. Focus especially on the numbered list of phrases shared above.
  2. Pause After Each Segment: After each sentence or key phrase, pause the video. Repeat what she said out loud, mimicking her intonation and pronunciation.
  3. Record Yourself: Use a recording device to capture your shadow speech. Listen back to identify areas for improvement, such as clarity or rhythm.
  4. Practice Regularly: Dedicate 15-20 minutes each day to shadowing this talk or similar content. Frequent practice helps internalize the phrases for natural usage.
  5. Engage with Others: Share your experience with peers or through a shadowing site. Exchange ideas on adapting the phrases to your daily conversations or work scenarios.

By applying this step-by-step guide, you'll enhance your spoken English skills and deepen your understanding of the nuanced conversations around AI and work, making each session valuable for your growth as an English learner.

What is the Shadowing Technique?

Shadowing is a science-backed language learning technique originally developed for professional interpreter training and popularized by polyglot Dr. Alexander Arguelles. The method is simple but powerful: you listen to native English audio and immediately repeat it out loud — like a shadow following the speaker with just a 1–2 second delay. Unlike passive listening or grammar drills, shadowing forces your brain and mouth muscles to simultaneously process and reproduce real speech patterns. Research shows it significantly improves pronunciation accuracy, intonation, rhythm, connected speech, listening comprehension, and speaking fluency — making it one of the most effective methods for IELTS Speaking preparation and real-world English communication.

How to Practice Effectively on ShadowingEnglish

  1. Choose your video: Pick a YouTube video with clear, natural English speech. TED Talks, BBC News, movie scenes, podcasts, or IELTS sample answers all work great. Paste the URL into the search bar. Start with shorter videos (under 5 minutes) and content you find genuinely interesting — motivation matters.
  2. Listen first, understand the context: On your first pass, keep the speed at 1x and just listen. Don't try to repeat yet. Focus on understanding the meaning, picking up new vocabulary, and noticing how the speaker stresses words, links sounds, and uses pauses.
  3. Set up Shadowing mode:
    • Wait Mode: Choose +3s or +5s — after each sentence plays, the video pauses automatically so you have time to repeat it out loud. Choose Manual if you want full control and press Next yourself after each repetition.
    • Sub Sync: YouTube subtitles sometimes appear slightly ahead or behind the audio. Use ±100ms to align them perfectly so you can follow along accurately.
  4. Shadow out loud (the core practice): This is where the real work happens. As soon as a sentence plays — or during the pause — repeat it out loud, clearly and confidently. Don't just mouth the words: mirror the speaker's exact rhythm, stress, pitch, and connected speech. Aim to sound like a shadow of the speaker, not just a word-by-word recitation. Use the Repeat feature to drill the same sentence multiple times until it feels natural.
  5. Scale up the challenge: Once a passage feels comfortable, push your limits. Increase speed to <code>1.25x</code> or even <code>1.5x</code> to train high-speed language reflexes. Or set Wait Mode to <code>Off</code> for continuous shadowing — the most advanced and rewarding mode. Consistent daily practice of 15–30 minutes will produce noticeable results within weeks.

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