Luyện nói tiếng Anh bằng Shadowing qua video: I think AI slop is about to trigger a renaissance, actually
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Hello, hello, hello, hello.
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Thank you for joining me.
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In 2023, the American Dialect Society picked and shitification as its word of the year.
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That is, online platforms becoming increasingly worse because they know you won't leave and therefore they can just maximize profits.
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In 2024, Oxford picked brain rot as its word of the year.
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And in 2025, Merriam-Webster picked slop.
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Are you seeing a pattern here.
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Because to me, the sentiment behind these three words reminds me of three other words.
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You see, most of the AI conversation right now is centered around fear.
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AI is going to take all the jobs.
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It's going to kill human connection.
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It's going to kill art and creativity.
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Some very serious people say it might even kill everyone.
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And although these concerns are real, I think the more likely danger isn't that AI makes us useless, it's that it makes us comfortable, passive, dependent.
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And here's the messed up part, we might secretly like that because it will feel like abundance.
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Neil Postman put it like this, people will come to love their oppression, to adore the technologies that undo their capacities to think.
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In this episode, I want to show you the invisible trade
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that we risk making as this technology becomes ubiquitous with modern life, but I want to show you why I'm actually feeling hopeful.
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Because as the old world starts to break, there is room for a new one to emerge.
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And when anything can be made in an instant by anyone or anything, value doesn't disappear.
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It moves.
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Value moves towards those people that still have something to say, that still have a perspective to share.
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So by the end of this video, I want to show you exactly what I'm doing to protect, nourish, and foster those skills that will be completely indispensable in the near future.
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My name is Mikey.
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This is In Perspective.
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Let's get into it.
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It's one small step for man, one giant leap for mankind.
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The very first thing we have to talk about is that whenever a new technology is invented, there is an invisible trade that is made that does not show up until much later.
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A sort of second-order consequence that occurs really with anything in life, but it is especially prevalent with technology.
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The most obvious examples of this that people love to quote when they're talking about this are examples like the calculator.
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We used to be able to do mental math and making arithmetic by hand was a very important skill.
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All of a sudden the calculator shows up and that's a skill that atrophies.
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It's a skill that disappears with time.
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Another example would be something like the GPS.
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We used to be able to navigate, to look at highway signs, to look at maps, to find your way.
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Now, of course, GPS is extremely useful, but nobody has developed that skill or nobody maintained that skill of being able to wayfind by themselves.
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But I want to illustrate this idea of invisible trades with a bit deeper examples, unlike the ones you've heard before.
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So it really solidifies in your head of how important this is.
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The first example that I want to give you is cars.
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When cars came about, it is an impossible thing to say no to, right?
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Easy, reliable, affordable travel for the average person, right?
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Cars were an incredible, incredible, incredible invention.
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Obviously, they were not affordable in the beginning, but you know what I mean, eventually.
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Now, what happens is that as soon as people can drive everywhere, all the time, affordably, people no longer need to live in the cities that they work in.
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So what happens is that developers saw this opportunity
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and they started to spread housing far
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and wide They started to buy all of this cheap land around big cities
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and then they just built homes this idea of the suburbs Happened we built highways.
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We built strip malls single-family homes.
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You get a pool.
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You get a pool You get a pool.
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Everybody gets a pool.
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Everybody gets a backyard.
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This was awesome, right?
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This whole idea of the single-family home really exploded because people could afford homes now
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what happens is that you get this phenomenon that if you've studied urban design, you might be familiar with, which is called urban sprawl.
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The trade was communities, right?
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Because when everybody has to drive into the city and then drive back, you lose serendipitous encounters with your neighbors, with your barber, with the butcher.
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You lose third spaces.
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You rob children of their autonomy because now they're dependent on mom
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and dad to drive them everywhere in order to hang out with friends, to ride their bike into the city and do something.
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You rob elderly folk of their independence once they lose the ability to drive.
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Oh, and not to mention that now everybody's driving an hour into work.
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Carbon emissions basically doubled since this happened, right?
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So there's a massive damage to the environment that happens as well.
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Whoops.
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An invention is made.
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There's a technology that is created, but we don't see the ripple effects, the second order consequences, the invisible trades, until much after.
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So now the question becomes, what will the invisible trades, what will the second order consequences of a technology like AI be, right?
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Once this technology gets diffused into all elements of society, what will we be trading?
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Before we entertain this discussion, I think it's very clear that we get one of the most important pieces of context out of the way,
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which is that many serious scientists are calling this the last invention we'll ever make.
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And this is not to be dramatic or to simply bump up their stock prices, although maybe there's a bit of that as well.
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But this is because the stated mission of every single major AI company right now, OpenAI, Anthropic, Google, Meta, and so on,
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is to get to a point of what is called the recursive self-improvement.
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That is a point in which
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The AI will be able to train the next version of itself because as soon as we can do that, then this sort of exponential growth curve,
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this explosion of intelligence occurs where the AI is now an artificial general intelligence,
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AGI, and it can improve the rate of progress across everything, right? scientific discoveries,
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the optimization of global supply chains, military security, surveillance, healthcare.
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This is why you see people like Sam Altman
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and all these people propping up these AI companies make these crazy claims
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that this technology is going to save humanity and solve everything.
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But there's some truth to this, right?
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Which is that this is what they're building.
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They are building a technology that will be better than the average human at virtually every single cognitive task that exists.
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Now, what are the implications of that?
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And Shanid Bovell wrote a phenomenal Substack article on this
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that I'm just going to read to you because I think it frames this discussion perfectly.
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We are moving towards a future where AI will handle everything, or so we're told, and we'd best start preparing for that.
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With the exception of a few, I think most people, myself included, wouldn't be thrilled about the prospect of not needing to or knowing how to think.
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From a health perspective, use it or lose it is not just a catchy phrase.
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It is a physiological reality.
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A society without thinking skills could face faster cognitive decline and more stable, more unstable democracies.
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And there you have it.
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The main thing that we are at risk of trading, now that you know what these major AI companies are trying to build,
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a machine that outperforms humans at virtually every cognitive task, the thing that we are at risk of losing is our ability to think.
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And this is not an exaggeration.
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Our ability to sit with hard problems for a long time to wrestle with ideas and abstract dense information,
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to sit with a problem for long enough until it becomes interesting and we solve it.
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Another thing it threatens is our ability to develop our taste and our curiosity.
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And this we're already seeing with our hyper-personalized,
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hyper-optimized entertainment algorithms that exist on every single person's Instagram, every single person's TikTok, every single person's LinkedIn,
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every single person's YouTube, right?
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These are hyper-personalized, hyper-optimized, artificially intelligent algorithms that are just feeding you what you want, quote-unquote, right?
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Feeding you what you should want, feeding you what you think you want.
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But in reality, that's not really what you want.
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These are often just the things that are most commercially profitable for them, right?
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They're going to show you the things
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that are most emotionally conducive to keeping you on the platform as long as possible
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so you can see more ads and they make more money.
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Another thing that we subtly lose is our ability to own our thoughts, to own our ideas, to own our outputs.
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What I mean by that is that when you struggle with something, when you wrestle with an idea, when you work on a project and you fail and you fail
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and you fail and you try again and you try again, When you're wrestling with something, whatever output you get at the other side of that, you own that, right?
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If you've spent 100, 200, 1,000 hours working on a PhD dissertation or on a YouTube video that you're creating,
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on a book, on a movie, you own those ideas.
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You feel a deep sense of pride and connection to the arguments, to the nuances, to the failures, the lessons you have to overcome it shapes you.
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But when you're just focused on the output, right?
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When you have this hyper intelligent AI that you're completely offloading all of your thinking, all of your work to, and it's just giving you the output in an instant,
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you lose the connection to that work.
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You're like, sure, I can make a beautiful AI movie, but I'm not going to be connected to the story, to the characters, because it did not come from me.
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It did not come from the toil, the wrestling, the friction.
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Okay, so those are the things that we are at risk of losing.
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But like I promised in the intro, I want to share with you why I'm actually feeling hopeful.
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Because first of all, I think there is a small but noticeable pushback,
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a cultural resistance towards this in-shittification, AI slop, hyper tech accelerationist type of world.
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the first example of that is the words that I listed in the beginning.
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The fact that we've developed cultural language, a cultural vocabulary to describe these shared experiences that we don't really like.
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Words like brain rot, words like doom scrolling, words like AI slop and shittification, touching grass.
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Right?
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Think about all these cultural words and shared experiences that we're having that say, we don't really like where this is going.
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Another prevalent example of this kind of resistance is the very fact
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that this conversation around the damage that social media has done to teenagers and our mental health,
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that is very prevalent in popular culture, popular general culture.
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Jonathan Haidt's book, The Anxious Generation, which is a brilliant book that talks about this kind of stuff.
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That's been in the New York Times bestselling list for over 100 weeks.
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The Social Dilemma, a documentary on this issue, won two Emmys and it got viewed by over 100 million people.
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This is in the general discourse, the general cultural discourse is, hey, we don't really like screens.
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We don't really like brain rot.
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This thing is probably pretty bad for us.
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And right at the same time that this is unfolding is when this whole AI slop,
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hyper accelerationist tech forward conversation is unfolding.
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So there is some sort of resistance or almost repulsion towards AI slop
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and things that are AI generated that feel not human.
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Okay, so that's point number one of why I'm feeling hopeful, right?
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There's some sort of resistance, a cultural resistance that you can feel that is kind of pushing back against this.
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But the second reason why I'm hopeful, which is a much deeper reason, and it doesn't sound like a good thing at first, but I actually think it might be,
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is the fact
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that once we get to this point where an AI can do every single human job better than a human would, and there's this sort of wave of mass unemployment,
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which is pretty much inevitable to happen within the next, you know, 10, 20 years when we get to that point where people no longer are required,
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their skills are no longer required in the marketplace and they don't need to work anymore, the more problematic issue is that this will be a crisis of meaning,
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a crisis of identity for millions and millions of people.
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Because our culture for the past 20,
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30, 50, however many years has made it so that our identities are deeply connected to what we do for work.
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If you're a lawyer, if you're a doctor, if you're an engineer, if you're a plumber, even whatever it may be, there is a deep sense of pride in what you do for work
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and how you earn money and how you provide and how you, that is pivotal to our identities, right?
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One of the first things that people mention in conversation is what do you do for work?
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Or they take pride in that, right?
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So now when you remove that from a person's identity, that is going to be a big deal for a lot of people that a lot of people will struggle with.
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But the reason why I'm saying I'm hopeful is because that is an opportunity, right?
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It is an opportunity for you to really ask yourself the fundamental philosophical existential questions
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that lead to beautiful art and beautiful work and meaning.
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Questions like, who am I?
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Why am I here?
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What do I value?
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What do I want to do?
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Right?
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I think millions of people will be forced to ask
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that question very abruptly because their entire paradigm of how they saw the world, of how they saw work, of what they saw their role in society as,
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that's going to be shattered.
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So they'll be forced to ask those questions.
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And I think while this may be devastating in the short term for a lot of people, I think the people that are aware of this, people that are likely watching videos like this, that is a beautiful opportunity
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because again you are here to create you are here to
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build things you are here to self-actualize to rise to the highest level possible of what you could be
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and to serve others with that unique gift
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and by de-attaching your sense of identity your sense of worth from what you do for work
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which even before you lose your job you should already do that.
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But by doing that is where you create space for you to really answer those questions.
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Who am I?
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Why am I here?
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What do I want?
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What do I value?
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How do I want to spend my time?
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What do I want to create?
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What is my energy good for?
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What should I spend it on?
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Now, the third reason why I'm hopeful
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and I think this technology could lead to a sort of human renaissance is
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because AI does not experience things the way that we do.
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And therefore, whatever it creates,
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no matter how efficient or interesting and productive it may be for the marketplace,
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it can't move us the way that human art, human creation can.
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I want to read you a quote from Rick Rubin, who if you don't know, he's one of the most prolific music producers of all time,
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who's worked with all sorts of amazing He said, one reason art resonates is because human beings are so similar.
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We're attracted to the shared experience held within the work, including the imperfection in it.
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We recognize some part of ourselves and feel understood and connected.
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An AI will always generate responses based on statistical patterns that it found in its training data.
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And it's very good at doing this, right?
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It will come up with novel and interesting solutions because its training data is massive.
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But what we don't know is if and how it understands these things.
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We don't even know if it understands.
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Its thinking is completely alien to us.
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What we do know is that it can't experience things.
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It can't feel things the way we can, which means you could ask it to
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write the screenplay for a movie or write a manuscript for a book on trauma
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and sure it has access to every single piece of written work every movie every song every poem
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that has been written with the tone the emotion of trauma and it could produce something interesting
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but it does not know what it feels like to be locked in your room
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when you were seven years old crying and scared shitless
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because your father is screaming at your mother in the kitchen
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and there's dishes breaking and things getting thrown around it doesn't know what
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that feels like and
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that is the beautiful thing about human arts about human creativity
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our perspectives are singular right you could ask the ai to write you
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new scientific research on love and brain chemistry
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and try to understand this phenomenon
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that we've been trying to decipher for hundreds of years millennia
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and sure it could go read all the the research synthesized things it could read all the books
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and shakespeare and whatnot
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but it does not know what it feels like to look at a person in the eyes
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and be like feel like god put this person in front of you just for you
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and they they have the power with a simple smile
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or a look in your eyes to uplift you from the
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darkest places they don't know what it feels like to lose that person
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right and then have these memories flashing in your head of all these mundane
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but beautiful moments of how they brush their teeth
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or the way in which they rub their eyes in the morning
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when they woke up or like the way their face lights up
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when they're eating they take a first bite of something like all those micro experiences
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that are deeply human and visceral to us it can't pull from that, right?
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Which is why we always feel like AI slop is a thing.
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There's something missing.
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There's something uncanny, right?
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AI can write this beautiful email or LinkedIn post or brand marketing campaign or whatever, but there is something missing.
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That thing that's missing is perspective.
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That thing that's missing is experience.
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Experience is what gives us meaning.
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Human experience is singular, informed by all four experiences, biases, dreams, goals, traumas, limitations,
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insecurities, stories, side characters, adventures, and so on.
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We don't have to try to make a point in order for the authenticity of our perspective to shine through.
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Everything we experience and create is constantly being passed through this filter of our experiences, which is beautiful and infinitely unique.
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This is what we have to protect because in a world where machines can think better than us,
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they can synthesize information and create things way faster and way better than we can.
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What is left for us is our taste, our judgment, our ability to think critically,
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to think holistically, to think big picture, right?
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Our ability to use our filter of our experiences and knowledge and biases
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to filter information and organize it in an interesting and unique way, in a way that connects with other people.
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There's this great quote which says, the personal is the universal.
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That's what Rick Rubin was getting at as well.
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Now in this next chapter, I want to share with you the things that I'm doing in my life to nourish those skills, to nourish my taste, to nourish my judgment,
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to foster a perspective, and to protect my ability to think.
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The first thing is to think on paper, right?
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One of the most beautiful things about writing,
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whether it be journaling or writing a letter to a friend or actually writing an essay,
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a video, working on a project on paper by hand, is that writing is a form of thinking.
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how often have you had the experience where you have these abstract ephemeral kind of feelings
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and emotions you think you know something you think you understand your point of view on something
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but as soon as you try to speak it to a friend it comes out a complete jumbled mess
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or as soon as you try to write to yourself about
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it it's not clear it doesn't come through it is
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because writing is thinking speaking is thinking when we use language to organize the abstract world of ideas and emotions and concepts,
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when we use writing and thinking to put it on paper and structure it, we are crystallizing our knowledge.
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We are thinking on paper, right?
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So that is a skill that you have to maintain, that you have to protect, that you have to foster.
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Keeping physical notebooks to jot down ideas, right?
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You go to a meeting, instead of having a little AI note taker instead of taking notes on
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that meeting in a little notion tab
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or google doc take notes by hand right journal every single
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morning clarify your thoughts clarify your intentions clarify your goals work
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through whatever emotions problems in your life you're going through think
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on paper connected to this idea of thinking on paper is
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creating clear boundaries as to what will stay human and what you are comfortable offloading to an AI, right?
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I'm not telling you to never use AI.
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AI is an amazing tool and we're going to get into that in a second, but you have to create clear boundaries for yourself as to what you will keep uniquely human.
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For example, which might not be relevant for you guys, I will never use AI to script a YouTube video.
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I don't even script these videos, as you can probably tell.
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But that is something that I want to keep uniquely human.
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Because for me, the process of reading, learning things, writing things by hand, wrestling with ideas, that is me protecting my ability to think clearly,
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to organize thoughts, to organize my ideas.
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Me practicing, turning on a camera, not reading a script, and just speaking about these ideas in a cohesive way.
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That is me protecting and nourishing this skill.
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For you, maybe you're in school, maybe you tell yourself, I'm only going to use AI for the research portion of this thing that I'm working on,
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or I'm only going to use it to stress test my ideas, but I'm actually going to type everything.
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Great.
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Whatever it may be for you that is relevant in your work, but you have to create clear boundaries as to what you will keep human.
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The next thing is to introduce cognitive friction into your life.
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And what I mean by cognitive friction is to read.
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Read.
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Consume long format media, right?
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Instead of doomscrolling all the damn time, consume long YouTube videos like this.
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Consume podcasts.
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Consume lectures.
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Watch a documentary.
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When you allow your brain to engage with and wrestle with long, complex, dense, abstract ideas and really think through them slowly,
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methodically, without even trying, you are automatically training your brain to think critically
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because you're engaging with an idea long enough for your own thinking to kick into place and start judging, critiquing, questioning.
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Another form of introducing cognitive friction is to stress test your beliefs and ideas in conversations.
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Call your friend, call a brother, have communities where you can have interesting conversations about the things that you're thinking about and wrestling with.
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Test them in person.
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Don't just hold these beliefs.
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Mikey told me this thing about where AI is going, so now I'm going to believe him.
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Yeah, this is going to be an AI renaissance.
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Great, because Mikey told me.
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No, I could be lying to you.
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These are my thoughts.
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I'm explaining the world to myself in public.
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Go and test these ideas in the world.
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Go have a conversation with a friend about it.
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See what they think.
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See what you think.
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Write about it.
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Journal about it. With everything.
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That's what thinking critically is.
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It's questioning.
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The next thing, which I kind of alluded to earlier, is learning to curate and create your own sort of algorithm, right?
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It's so fascinating to me that because our algorithms have gotten
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so good and they are amazing at feeding us content
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that is related to our interests and the things that we possibly want to learn about.
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I'm not discounting that, right?
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The engineers and people that work at Google, at Meta, at TikTok, these are brilliant people and they've designed a fascinating thing.
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But we forget that we can create our own sort of algorithm.
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We forget that we can pursue our own curiosity.
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You can grab a pen and paper, write your name at the very top in like a little bubble chart and then write a line.
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What are the things that I care about?
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Self-actualization.
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I care about fitness.
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I care about psychology.
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I care about clean energy.
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I care about birds, whatever it may be.
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And then you, from those bubbles, you extend them out.
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Okay, what are some other topics that I want to explore related to that?
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You can literally create your own sort of map of curiosity, your own adventure map of knowledge that you can then explore.
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And instead of using an algorithm
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and letting Mark Zuckerberg design this thing of what he's going to feed you every single morning with your Cheerios, you can decide to be like, okay, what are the top 10 books on psychology?
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Who are the three best thinkers, the leading thought leaders on clean energy?
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Okay, do they post on LinkedIn?
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Have they written a book?
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Do they have lectures?
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Do they have interviews?
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Let me go consume them.
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You can choose your own path.
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You can, if you care about a specific thing, instead of just going to Amazon and, you know, asking the Amazon algorithm to give you the top 10 books on this thing,
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you can walk into a local bookstore and talk to the person at the shop.
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You can walk into a local bookstore and just sit there for three hours,
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read the first 10 pages of five different books and see what speaks to you, right?
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So don't forget that you can pursue your own curiosity.
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That is very, very important.
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That is how you develop taste.
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That is how you develop judgment.
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Now let's talk about using AI
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Because the interesting thing about AI is
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that it is simultaneously the most incredible tool that's ever been created for learning and understanding things better,
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while also being the worst possible thing that we've ever created.
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Because it completely, we can completely offload all of our thinking
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and all of our cognition to this thing and never have to think, never have to write an essay again, never have to literally do anything ever again.
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so it is like the epitome of a double-edged sword right
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it is up to you to use it well right do
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not become this person that's like fuck technology technology is horrible
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it's gonna ruin society i'm just never gonna touch this stuff no use ai right
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if you have if you've done those other things
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that we've talked about you've pursued your own curiosity you've read books you're consuming podcasts, you're having conversations with friends, you're in university maybe, you're asking questions to your professor, you're reaching out to people,
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hey, do you want to grab coffee for 20 minutes?
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I really like this work that you're doing here and I'm really interested in learning more.
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You're doing all those things.
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At the same time, you can be using AI to stress test your thinking.
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You can be using AI to speak to it, tell it what you're thinking, tell it what you're learning about, tell it what you're curious about, tell it where to guide you to find new interesting sources.
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You should absolutely be using this tool to learn, right?
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But if you use it to give you the result without doing any of the work yourself, that is where you fuck up.
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So you have to be, you have to experiment.
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There's no formula I can give you here.
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You have to experiment, right?
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Sometimes you might try something and it'll be like, that didn't feel good.
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That felt too AI that I didn't hear myself.
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When I wrote that, I didn't hear myself.
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I didn't see myself.
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maybe you try something that didn't feel right.
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Maybe you try something and it felt great.
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And I was like, oh, that's a good use case for AI, right?
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There's all sorts of interesting tools.
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I'll give you one specific example of how I like to use AI.
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Google has this tool called notebook LM.
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One thing I like to do is when I'm already wrestling with different ideas, different concepts, I might grab a book that I've already read and I've already understood.
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And maybe I grab a long format lecture from a similar-ish topic that I've also already read, already consumed.
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So I'm not asking it to summarize these things for me, but I'll grab these two, three different sources and I'll put it into notebook.lm and it'll create a podcast about these topics,
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synthesizing this information.
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And then I'll go on an hour long walk.
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I'll go on a run.
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I'll go to the gym and I'm just listening to this podcast
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that is like a synthesis of these two things that I've already combined.
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Cool.
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Interesting use case, right?
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So there is ways in which you can use AI that you absolutely should experiment with, but be very, very, very careful offloading your cognition, offloading the work to it.
393
Because the struggle, the friction is what gives it meaning.
394
The struggle, the friction is what gives you a sense of ownership over the work.
395
That's all I have for you today.
396
I hope this helps.
397
I hope this has given you some hope.
398
AI will transform the world.
399
It really, really will.
400
But I think if you are intelligent in how you pursue your own curiosities and how you create things, make sure you are creating things, you're putting original work out there,
401
I think there is an opportunity for truly a new kind
402
of renaissance to emerge where we'll see a resurgence of great movies, of great music, of great books,
403
of new other new technologies, these other new companies that really resonate, that really feel human, that really help.
404
Right?
405
And I think you watching this can be part of that wave
406
if you do some of the things that we talked about in this video.
407
Anyways, I hope this served you.
408
I'll see you next week.
409
Peace.
Tải Ứng Dụng
Mọi thứ bạn cần để nói trôi chảy
Chấm điểm AIChấm từng câu nói
Luyện IPAThành thạo mọi âm
Từ vựngMở rộng vốn từ
Game Từ vựngHọc qua chơi
Cùng kênh
FOR YOU
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Từ vựng và ghi chú luyện nói cho bài học này
Bài luyện nói trình độ C1 này dựa trên video “I think AI slop is about to trigger a renaissance, actually”. Video này có 409 câu và 5274 từ để luyện shadowing. Phần lời nói dài 31:01. Người nói nói với tốc độ tự nhiên, khoảng 170 từ mỗi phút, gần với hội thoại hằng ngày. 85% số từ nằm trong 3.000 từ tiếng Anh thông dụng nhất; phần còn lại nên xem trước khi luyện.
Từ vựng quan trọng trong video
15 từ khó nhất trong video, kèm phiên âm và nghĩa:
| Từ | Phiên âm | Nghĩa |
|---|---|---|
| algorithm danh từ | /ˈælɡəɹɪðm̩/ | thuật toán |
| friction danh từ | /ˈfɹɪkʃən/ | ma sát |
| consume động từ | /kənˈsum/ | dùng, tiêu thụ |
| curiosity danh từ | /ˌkjʊɹ.iˈɑ.sə.ti/ | tính/sự tò mò, tính/sự ham biết |
| invisible tính từ | /ɪnˈvɪzəb(ə)l/ | vô hình, tàng hình |
| organize động từ | /ˈɔɹɡənaɪz/ | sắp xếp, tổ chức |
| prevalent tính từ | /ˈpɹɛvələnt/ | phổ biến, thông thường |
| renaissance danh từ | /ɹəˈneɪs(ə)ns/ | phục hưng |
| invention danh từ | /ɪnˈvɛnʃən/ | phát minh, sáng chế |
| consequence danh từ | /ˈkɑn.sɪ.kwəns/ | hậu quả |
| cognition danh từ | /kɑɡˈnɪʃ.ən/ | nhận thức |
| calculator danh từ | /kæl.kjə.leɪ.tɚ/ | máy tính cầm tay, máy tính cơ khí |
| notebook danh từ | /ˈnoʊtˌbʊk/ | tập, vở |
| dense tính từ | /ˈdɛns/ | đặc, dày đặc |
| creativity danh từ | /kri.eɪˈtɪv.ᵻ.ti/ | óc sáng tạo, tính sáng tạo |
Cụm động từ bạn sẽ nghe
| Từ | Phiên âm | Nghĩa |
|---|---|---|
| wake up động từ | /ˌweɪk ˈʌp/ | thức dậy, dậy lên |
Những câu đáng luyện lại
Các câu ngắn, trọn ý trong video mà bạn có thể dùng lại khi giao tiếp hằng ngày:
- Questions like, who am I?
- What do I want to do?
- How do I want to spend my time?
- What do I want to create?
- What is my energy good for?
Ngữ pháp trong video
Những cấu trúc người nói dùng nhiều nhất, kèm đúng cụm từ trong video:
| Cấu trúc | Trong video |
|---|---|
| “Used to” used to + động từ — thói quen hoặc tình trạng trong quá khứ nay không còn | used to be |
| Thì hiện tại hoàn thành have/has + quá khứ phân từ — việc đã xảy ra nhưng còn liên quan đến hiện tại | has developed · you've heard · you've studied |
| Câu bị động be + quá khứ phân từ — nhấn vào việc xảy ra, không phải người làm | is centered · can be made · is invented |
| Mệnh đề quan hệ who / which + mệnh đề — thêm thông tin về người hoặc vật | with, which is · Generation, which is · hopeful, which is |
Phát âm cần chú ý
Người nói dùng 118 dạng rút gọn, ví dụ I'm, you're, don't. Hãy nói theo dạng ngắn đúng như bạn nghe.
- Âm “sh” và “zh”: friction /ˈfɹɪkʃən/, nourish /ˈnʌɹ.ɪʃ/, invention /ɪnˈvɛnʃən/, cognition /kɑɡˈnɪʃ.ən/, implication /ˌɪmpləˈkeɪʃən/
- Từ dài — đặt trọng âm cho đúng: curiosity /ˌkjʊɹ.iˈɑ.sə.ti/, invisible /ɪnˈvɪzəb(ə)l/, critically /ˈkɹɪt.ɪ.kə.li/, personalize /ˈpɜː.sə.nə.laɪz/, calculator /kæl.kjə.leɪ.tɚ/
Cách luyện với video này
- Nghe hết video một lần, chưa cần nói, và ghi lại những từ bạn chưa biết.
- Bắt đầu ở tốc độ 0,75×, nói đuổi từng câu, rồi quay lại tốc độ bình thường khi đã quen.
- Ghi âm giọng mình rồi so với bản gốc, chú ý các từ như algorithm, friction, consume.
Phương Pháp Shadowing Là Gì?
Shadowing là kỹ thuật học ngôn ngữ có cơ sở khoa học, ban đầu được phát triển cho chương trình đào tạo phiên dịch viên chuyên nghiệp và được phổ biến rộng rãi bởi nhà đa ngôn ngữ học Dr. Alexander Arguelles. Nguyên lý cốt lõi đơn giản nhưng cực kỳ hiệu quả: bạn nghe tiếng Anh của người bản xứ và lặp lại to ngay lập tức — như một "cái bóng" (shadow) đuổi theo người nói với độ trễ chỉ 1–2 giây. Khác với luyện ngữ pháp hay học từ vựng bị động, Shadowing buộc não bộ và cơ miệng phải đồng thời xử lý và tái tạo ngôn ngữ thực tế. Các nghiên cứu khoa học xác nhận phương pháp này cải thiện đáng kể phát âm, ngữ điệu, nhịp điệu, nối âm, kỹ năng nghe và độ lưu loát khi nói — đặc biệt hiệu quả cho người luyện IELTS Speaking và muốn giao tiếp tiếng Anh tự nhiên như người bản ngữ.