تدريب Shadowing: Will AI Take Your Job in the Next 10 Years? Wrong Question | Vinciane Beauchene | TED - تعلم التحدث بالإنجليزية مع 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)
تنزيل التطبيق
تقييم بالذكاء الاصطناعي لكل جملة تنطقها
TRENDING
الأكثر شعبية
لماذا ممارسة التحدث مع هذا الفيديو؟
في عالم يتغير بسرعة بسبب الذكاء الاصطناعي، يُعد هذا الفيديو فرصة ذهبية لممارسة المحادثة الإنجليزية. من خلال الاستماع إلى Vinciane Beauchene، يمكنك استكشاف أفكار جديدة حول تأثير الذكاء الاصطناعي على سوق العمل، مما يوفر لك سياقًا غنيًا لتطبيق ما تعلمته. ممارسة المحادثة الإنجليزية في سياق مثل هذا تعزز من فهمك وتساعد على تطوير أسلوبك التعبيري، حيث يمكنك التفاعل مع موضوعات تتعلق بالمستقبل وطبيعة العمل.
القواعد والتعبيرات في السياق
في هذا الفيديو، يمكننا ملاحظة استخدام بعض الهياكل اللغوية المهمة التي يمكن أن تساعدك في تحسين مهاراتك:
- if... then: مثال على استخدام الشرط في اللغة الإنجليزية، يوضح كيف يمكن لإنشاء فرضيات أن يغير الفهم.
- not just... but also: تبرز هذه التركيبة أهمية فكرة معينة وتوسيع النقاش حولها.
- to rethink: تعبير يُظهر الحاجة للتفكير مرة أخرى في الأفكار المكتسبة، وهو مهم في النقاشات عندما تتحدث عن مستقبل العمل.
- What remains for humans?: يعد سؤالاً استفسارياً يتطلب إجابة معقدة، ويمكن استخدامه في محادثات حول القيم الإنسانية في عصر التكنولوجيا.
استخدام هذه التعبيرات والهياكل في طريقة التظليل في الإنجليزية سيمكنك من تحسين تعبيرك العام والتواصل بفاعلية أكبر.
فخاخ النطق الشائعة
هناك بعض الكلمات والتعابير في الفيديو التي قد تكون صعبة النطق، ومن المهم أن تكون واعيًا لها لتحسين ممارسة المحادثة الإنجليزية الخاصة بك:
- autonomous: قد تكون هذه الكلمة معقدة بسبب حروفها المركبة، اهتم بنطق كل جزء بدقة.
- intervention: التركيز على الأجزاء الصوتية الساكنة والضغوط التنوينية فيها.
- adapt: يمكن أن يكون نطقه مختلفًا حسب اللهجات، لذا حاول الاستماع جيدًا واستخدامه في shadow speech.
استثمر الوقت في معالجة هذه الفخاخ اللغوية أثناء ممارسة shadow speak لتحسين وضوحك وثقتك في التحدث.
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التظليل الصوتي (Shadowing) تقنية تعلم لغة مدعومة علمياً، طُورت أصلاً لتدريب المترجمين الفوريين المحترفين. الطريقة بسيطة لكنها قوية: تستمع لصوت إنجليزي أصلي وتكرره فوراً بصوت عالٍ — كظل يتبع المتحدث بتأخير 1-2 ثانية. تُظهر الأبحاث تحسناً كبيراً في دقة النطق والتنغيم والإيقاع وربط الأصوات والاستماع والطلاقة.
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