シャドーイング練習: Give Me 18 Minutes and I’ll Make you Dangerously Smart (with AI) - YouTubeで英語スピーキングを学ぶ
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Most people are letting AI destroy their ability to think,
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Most people are letting AI destroy their ability to think,
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training AI to become their own replacement.
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Tragic, because AI can make you dangerously intelligent.
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I went from being homeless to an MIT grad and running and advising AI companies worth billions.
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And here's what I've learned.
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The top 1% use AI backwards.
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They don't prompt to get answers.
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They use it to train their brain and outsmart almost any situation.
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So in this video, I'll break down a counter-intuitive system the top 1% use to get smarter faster with AI.
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Here is the four-step framework.
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Step 1.
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Intelligent laziness.
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A study in Harvard Business Review found that CEOs waste 72% of their time in meetings that don't move the needle.
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We've all experienced those meetings, haven't we?
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The one-hour meeting that needed only 15 minutes to get to a decision.
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But is hard to stop.
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So why do some of the most accomplished folks feel trapped this way?
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Because we all suffer from this biological glitch called completion bias.
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Your brain is wired to seek an immediate dopamine hit that you get from finishing a task.
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So we end up treating all tasks as equal
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because we're going to get roughly the same amount of dopamine
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when you spend time on redrafting an internal email or a million dollar strategy document.
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Everything is priority one, so none of it is.
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So how do you avoid this priority blindness?
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A good way to think about tasks is to see two curves.
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First curve has capped payoffs.
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This curve goes up and then flattens out once it reaches the zone of diminishing returns.
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So tasks like formatting slides or internal emails, expense reports, FYI meetings.
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What happens if you spend additional effort to make the outcome of these tasks pitch perfect?
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Nothing.
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There's no upside here because the value flatlines after a point.
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Nobody cares if you spend hours choosing better fonts or breathtaking designs in internal slides that are seen for six minutes.
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This curve shows you your zone of intelligent laziness.
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There was a Nobel Prize winning economist and computer scientist,
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and his name was Herbert Simon,
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and he came up with a concept called satisficing,
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which pretty much means stop when it's good enough.
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Satisfy and suffice.
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Satisfice.
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Now our second curve is the exact opposite.
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It has uncapped payoff.
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This curve stays flat for a long time,
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but then goes to the moon in a hurry.
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These are tasks like customer interactions,
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product design, pricing model, finding a co-founder or a life partner.
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Being 1% better here does not yield 1% better result.
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It actually solves the rest of the 99% of your problems.
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Pour your soul into this.
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Johnny Ive would obsess for many months on even the internal component design of iPhone.
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But you know, Steve Jobs never said,
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hey, this is costing us a lot of money and who's gonna pry open the iPhone?
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But Steve knew this was the second curve.
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So if the first curve is your zone of laziness,
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your second curve is your zone of obsession.
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Let's talk about how AI can help.
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The top 1% use AI on zone 1 or the zone of laziness.
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The more they outsource Zone 1 to AI,
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the more they can focus on Zone 2, the Zone of Obsession.
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So how do I decide what to outsource to AI, and when?
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So for that, I use a very simple framework called DRAG framework.
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D-R-A-G.
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Four categories of work you immediately should delegate to AI so you can stay in your Zone of Obsession.
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First, D equals drafting.
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This is the blank page problem we all face.
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It's hardest to get from 0 to 1 sometimes.
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AI can help here, tremendously actually.
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Give it a prompt using the AIM protocol that I've shared before.
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Hey AI, act in this role,
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use this input, and this is your mission.
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AIM.
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And that way, you get started very quickly on that email or code or presentation.
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The first draft from AI will be crappy and atrocious, but that's fine.
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Now you have a starting point.
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You're not staring at a blank page anymore.
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Now it'll trigger something in your brain and you're off to the races.
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R equals research.
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This helps you solve the information overload problem.
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Today if something requires deep research it can be dramatically accelerated using AI.
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Summarization, extraction, competitive intel.
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You know don't spend time doing that kind of research.
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Let your friendly neighborhood AI do it for you.
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When you use the deep research feature on ChatGPT or Gemini or Claude,
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it fires off hundreds of secondary search queries.
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It goes out to the web like a spider and finds hundreds of sites,
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consolidates the results, even checks his own work by asking what's missing,
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and follows up on its own to finally deliver a rich document to you.
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It's like you just hired a consultant for a week-long research project,
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but instead you get there in 10 minutes.
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Third is A for analysis.
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Let AI take the first pass at analyzing,
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summarizing, reasoning, especially if it's all unstructured data
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because AI is going to find patterns that we humans aren't going to be able to.
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So use it for your advantage.
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And finally G is for all the grunt work.
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Tasks like reformatting, translating, tabulating,
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cleaning data, and on and on.
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The boring manual work.
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Just give it to AI.
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So what's the key principle behind drag?
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Apply it only when you are in your zone one.
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That first curve.
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If it requires human interaction or judgment or intuition or decision making or tastes, that's curve two.
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That you've got to do it yourself.
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But you know, I've found that 70 or 80 percent of my repetitive tasks tend to be in zone one.
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And you might find that too.
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So be lazy when you can use drag.
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Be obsessed for everything else.
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Step two, the intelligent hill.
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For 300 years, Isaac Newton convinced us that universe was a clockwork machine.
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Predictable and certain.
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But in 1927, another scientist named Heisenberg shattered those classical beliefs.
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He showed that our universe exists only as a cloud of possibilities at quantum level.
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It was a profound shift.
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You and I have to make a similar shift when we use AI nowadays.
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The first trick is to stop treating AI like a calculator.
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We like to live in a world with clear rules.
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You type 2 plus 2 into a calculator and you get 4.
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Always.
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It's predictable.
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But AI is not a calculator.
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It's a probability engine.
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If you ask the same question to AI again,
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it'll give you a completely different answer.
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It'll happily make things up for you unless you ask it to verify.
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AI is brilliant on some days,
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confused on others but on any given day it refuses to admit that it doesn't know the answer.
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It loves to make things up.
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So you don't just ask AI the way you ask a normal human being.
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You have to architect your questions very carefully.
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Now most people use a tactic called zero shot prompting.
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So for example they would ask give me the best new business idea
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and of course AI will dish out a response and tell you why it's the greatest idea in the world,
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but you're literally rolling the dice and looking to win.
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To get elite results though,
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you must climb the intelligent hill.
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There are four camps on the way.
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Each camp will show you a different way to work with AI.
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Our first camp is called one-shot prompting.
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When you prompt, give one clear example so the model doesn't guess blindly.
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So the prompt would look like,
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write a LinkedIn post about remote work.
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Use this specific post as a style guide.
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And so give it a post,
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give it an example, and paste that post in the prompt as a reference.
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And that simple act is already an upgrade than rolling the dice blindly.
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Second camp, few shot prompting.
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Now here you give AI three or more examples so it can find patterns of style,
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and substance and tone that you desire.
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Attached documents, links, data, or your prior work,
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this is called grounding the model.
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So basically it stops fantasizing and hallucinating and gets grounded to reality.
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Here's an example of a prompt.
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Here are the five of my previous presentations.
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And now write a new presentation based on my tone of voice on topic XYZ.
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And here's the pro tip.
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Ask the AI to explain the pattern back to you first.
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That way, AI is forced to articulate what it's doing,
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and more importantly, you're forced to learn how your brain works.
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How did it come up with those patterns?
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Now, you're being smart about being smart.
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Now let's move to the third camp.
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This one is called chain of thought reasoning.
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Again, fancy name, but the idea is simple.
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Ask the model to think long and hard before it responds.
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Your job is to slow AI down and force explicit clarity by asking it to show its work.
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That's all there is.
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This is also a good way to reduce hallucinations, of course.
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So let's say you're working on some report,
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and so you attach it and write a prompt that could look like this.
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Do not refine my research report yet.
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List the top three most impactful areas of improvement after you analyze it.
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Tell me why you think so and suggest how we address each.
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Think step by step.
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Show me your thinking for each step.
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That last line is the most important one.
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And our fourth and final camp is agents.
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According to Salesforce, AI agents help drive $67 billion in global sales during Cyber Week alone.
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So agents are already here.
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The best way to think about agents is to think about who you would hire for a task.
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So let's say if you wanted to hire a researcher,
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an analyst, and a copywriter.
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You can do that with a single agentic prompt that looks like this.
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Do deep research on trends on topic XYZ,
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analyze and cross-reference all the trends to find the three most important ones,
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and draft a one-page memo summarizing the findings.
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Now, what is actionable?
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Try this framework tonight.
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Open your favorite AI app and take any prompt that you were about to use.
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Just try to get to the next camp.
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That's how you start climbing up the intelligent hill.
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Remember, when you were dealing with a drunk genius,
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make sure you were the one driving the car.
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So now, at this point,
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everything we have done has made you fast and efficient.
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You're delegating better, you're prompting smarter,
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you're moving up the hill,
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and there's less friction than before.
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And that's exactly where most people would stop.
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But here's the plot twist.
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The top 1% go one step further.
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They slow things down deliberately.
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Why is that important?
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The trick that top 1% know is this.
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They know when to shift the gear.
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Because long-term intelligence isn't built through convenience, it's built through resistance.
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and that's why we need to go to step three, the intelligent gym.
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Most people use AI as wheelchair for the mind and if you sit in a wheelchair when you can still walk,
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eventually your legs stop working,
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atrophy and today is happening faster than at any point in human history but the top 1% use a very different principle.
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For information tasks, use AI to remove friction.
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For transformation tasks, use AI to add friction.
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When you go to a physical gym,
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we all know how muscles are built, right?
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Through resistance.
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You lift increasingly heavier weights to introduce wear and tear to your muscle fibers,
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so they break and they grow back stronger.
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That is called progressive overload.
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But when it comes to our minds,
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we do the exact opposite somehow.
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We avoid resistance.
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We use AI to outsource our thinking.
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Write my LinkedIn post, fix my resume, summarize this book.
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That's like going to the gym and asking someone else to lift weights on your behalf.
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You know, when astronauts spend months in zero gravity,
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their muscles and bones atrophy dramatically, up to 20%.
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AI is like zero gravity for your thinking.
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No friction, no load, no growth.
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The intelligent gym is not about information.
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It's about transformation.
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For things where you need to be smart and capable,
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you can think of AI as your spotter.
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In any gym, a spotter doesn't lift the weight for you.
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They stand next to you and help you lift.
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They also make sure that you don't get crushed when you're lifting the weight.
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So do the same with AI.
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Here's a concrete example.
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If you want to learn a concept,
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study it first yourself and then go to your spotter, your AI.
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Paste the concept text and then prompt AI.
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I need to master this concept.
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Quiz me on it.
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And now comes the most important part of your intelligent gym.
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Ask AI to apply progressive overload.
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Four levels.
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Level one, quiz me like I am a high school student.
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Level two, ask me questions like I am a college student.
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Level three now grill me like you're interviewing me for an executive job
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and level four now challenge me like an irate boss Who thinks I'm unprepared
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so that truly strengthens and deepens your understanding on that concept
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So now we have covered three key steps to learn how the top 1% Become smarter by using AI
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but there is one internal adjustment that changes everything and that is our final step step number four The intelligent fool.
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You know, the biggest obstacle to intelligence isn't ignorance, it's ego.
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That's why the smartest people are obsessed with what they don't know.
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And this is what I call the fool's advantage.
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Let me give you an example.
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Microsoft went from $300 billion to $300 trillion in market cap with just one mental, cultural shift.
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When Satya Nadella became the CEO of Microsoft in 2014,
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they had missed two huge disruptions, search and mobile.
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The cloud race was ongoing,
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but it was slipping away from them with Amazon becoming the 800 pound gorilla.
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And the culture inside the company was toxic and political.
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And everyone was terrified to admit that there were gaps in their knowledge.
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Satya made one cultural move.
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He told the entire company,
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were switching from a culture of know-it-alls to learn-it-alls.
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A complete reboot of Microsoft culture.
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The smartest people in the room were finally given permission to say,
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I don't know, or I was wrong,
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and to embrace that beginner's mind.
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Now, Wall Street was skeptical at first,
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but the market cap eventually went from $300 billion to over $3 trillion.
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keeps growing.
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10x growth in a decade.
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And here's why this matters.
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Neuroscience tells us that our brain can rewire all the time.
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It's called neuroplasticity.
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This rewiring happens only at the edge of your ability.
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It happens when you are making errors.
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It happens when you're frustrated,
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when you're feeling that discomfort.
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And if you aren't feeling stupid, you aren't learning.
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And aren't you glad that AI has just handed you the ultimate training ground to be a student again?
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You can bring your beginner's mind to AI all day long.
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Ask questions you would never ask your colleagues out of fear of embarrassment.
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AI doesn't roll its eyes.
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Pick one thing that you don't understand in your field.
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Something that everyone else thinks you know,
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but you know you don't.
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And then ask AI the most basic questions about that topic that you can think of.
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And then ask.
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Can you explain it to me in a simpler way?
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Teach me like I am 10 years old.
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I ask these questions all the time.
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In fact, I ask three times in a row to simplify again and again.
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And sure, I guarantee you,
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you'll feel ridiculous at first.
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I do all the time.
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But that's the whole point.
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Have the courage to play the fool today so you can be the genius tomorrow.
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The trick to mastery is going back to simplicity itself.
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If you examine some of the greatest masters across human history,
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you'll see one consistent pattern.
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Every master is a student for life.
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And you can be a genuine student if you're hiding behind a mask of mastery.
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You know, the biggest benefit of intelligence is not the end of ignorance,
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it's the end of pretending.
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You know, we're surrounded by endless images of flawless people in their flawless poses, flawlessly photoshopped.
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But in the end, all art is about asymmetry.
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We're beautiful because we're broken.
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Because the real purpose of intelligence,
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of this thing called life,
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is to travel far and wide only to return to yourself and fully accept who you are.
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That is your truest intelligence.
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If you like this video, don't forget to subscribe.
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If you want to use AI to start a business,
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here's another video where I walk you through exactly what I would do.
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Thank you and I love you.
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このレッスンについて
このレッスンでは、AIを活用した思考法について学びます。AIを使用している多くの人々は、その能力を低下させてしまうことが多いですが、トップ1％の人々は異なるアプローチを取ります。彼らはAIを単なる答えを求める道具としてではなく、自分の思考をトレーニングするために利用します。このレッスンでは、思考を改善するための4つのステップフレームワークを紹介します。これにより、英語スピーキング練習や英語シャドーイングにも役立つ知識を得ることができるでしょう。
重要な語彙とフレーズ
- 知的怠惰 (Intelligent laziness)
- 完成バイアス (Completion bias)
- サティスファイシング (Satisficing)
- カスタマーインタラクション (Customer interactions)
- 製品デザイン (Product design)
- 無制限の報酬 (Uncapped payoff)
- 有限の報酬 (Capped payoffs)
- 戦略文書 (Strategy document)
練習のヒント
このビデオの内容を効果的に学ぶためには、英語シャドーイングのテクニックを用いることをお勧めします。特に、ビデオのスピードが速いので、shadow speechを利用して、話すスピードやイントネーションを真似ることが効果的です。この方法で、英語の発音を良くするだけでなく、自分自身の考えを明確にする力も向上します。
具体的には、以下のステップに従ってください：
- ビデオを数回視聴し、全体の内容を把握します。
- 初めてのシャドーイングは、少し遅めの速度で練習し、徐々にスピードを上げていきます。
- 特に重要なフレーズや語彙は繰り返し練習し、自分のものにします。
- 録音して自分の発音を確認すると、自分の成長を感じられます。
これらの練習を通じて、英語スピーキング練習がより充実したものになりますので、積極的に取り組んでみてください。
シャドーイングとは？英語上達に効果的な理由
シャドーイング（Shadowing）は、もともとプロの通訳者養成プログラムで開発された言語学習法で、多言語習得者として知られるDr. Alexander Arguelles によって広く普及されました。方法はシンプルですが非常に効果的：ネイティブスピーカーの英語を聞きながら、1〜2秒の遅延で声に出してすぐに繰り返す——まるで「影（shadow）」のように話者を追いかけます。文法ドリルや受動的なリスニングと異なり、シャドーイングは脳と口の筋肉が同時にリアルタイムで英語を処理・再現することを強制します。研究により、発音精度、抑揚、リズム、連音、リスニング力、そして会話の流暢さが大幅に向上することが確認されています。IELTSスピーキング対策や自然な英語コミュニケーションを目指す方に特におすすめです。