Pratica di Shadowing: Every Generation Thinks This Time Is Different: The AI Job Myth - Impara a parlare inglese con i video
Creazione lezione...
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If you're young and you're trying to figure out what to do with your career right now, you're probably hearing this.
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AI is going to take your job.
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And even if you aren't so young, you're probably hearing the same thing loudly from everyone.
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And the honest response to that is every generation has heard some version of it about the machine of the moment.
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Cars, electricity, the PC, the internet, smart phones, every single one of these was predicted to permanently destroy work.
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Yep, and every single one created more total jobs than it destroyed.
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Just different jobs.
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Yes, so Jeff and I want to walk through the pattern because the pattern is real and it's consistent.
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But from the inside the moment, it never looks like a pattern.
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It always looks like the exception.
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It always looks like this time is different.
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Which is where I want to start, because this time has been said a lot of times.
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All right, wave one, cars.
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The turn of the 20th century, one of the biggest employers in most cities was the horse economy.
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Oh, this is going to be my favorite segment.
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You're right.
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You're a barrel racer, so I can see why you would care about this.
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I love me some fast horses, which is very inconvenient for a video about the technology that replaced them.
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Sad.
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But the good news is, nobody has built an AI that can turn a barrel yet.
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And AI better never take the thrill of turning barrels away from me.
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Sorry, go on.
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The horse economy.
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Don't worry, Bree.
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No one wants to watch a robot rodeo.
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So yeah, we've got stable hands, blacksmiths, carriage makers, farriers, grooms, feed suppliers, manure haulers.
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Yeah, that was a real job title, believe it or not, and sometimes sounds a lot like my job at times.
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New York City, around 1900, had roughly 200 ,000 working horses in it, producing millions of pounds of,
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yeah, you guessed it, manure every day.
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Which sounds like a job you'd want a machine to take.
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Yeah, it turns out that you definitely want a machine to do that cars arrived, and within about 30 years, the horse economy had mostly gone.
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Hundreds of thousands of jobs vanished.
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And that's the version of the story that gets told.
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The jobs that disappeared.
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Right.
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The part that doesn't get told, though, is about what happened next.
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We had jobs that started to appear.
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The auto industry created assembly line work, mechanics, gas station attendance, road construction, motels, drive -in restaurants, traffic engineers,
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auto insurance, driver's ed teachers, an entire economy that just didn't exist before.
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More jobs than the ones that were lost.
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Way more and in fact none of them were predictable in 1900.
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Nobody in 1899 said, you know what the future is?
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Motel clerks.
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Because nobody had thought of a motel yet.
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Nobody had thought of a motel yet.
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That's because they lacked the vision to see what was on the other side of the mountain.
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They just saw the mountain.
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Fast forward.
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The same pattern shows up over and over.
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Electricity kills the gaslighting industry.
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I think you mean street lamp lighting industry because gas lighting is a different problem, right?
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I mean the street lamp lighting industry and the ice cutting business more icebreakers That's right,
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but it creates the appliance industry the entertainment industry
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and eventually the entire computer Industry all of which were much bigger than what actually got replaced.
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Yep The PC in the 1980s kills the typing tool and the filing clerk but creates software developers,
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systems analysts, IT support, the entire tech sector.
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The internet in the 90s kills travel agents, video rental stores, and encyclopedia salesmen.
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Well, those encyclopedias were always a little bit cumbersome to carry around after all.
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That's right.
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But it creates e -commerce, digital marketing, UX designers, community managers,
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and roughly every job that ends with the word engineer and did not exist in 1995.
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Then smartphones after 2007 kill the standalone GPS unit and the MP3 player, but create the app economy,
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the gig economy, and the creator economy.
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It was millions of jobs.
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Oh yeah.
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And Jeff, here's the stat I want people to sit with.
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David Otter at MIT has been doing this analysis for years.
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His 2024 paper on new work found that more than 60 % of the jobs Americans do today didn't exist in 1940.
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Hold on.
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According to my calculations, that's more than half.
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That's right.
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More than half.
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Those jobs weren't sitting there waiting to be discovered.
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Humans invented them on top of the tools they were handed.
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Again, these were all waiting just on the other side of the mountain.
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What brings us to the next part, then, is what surprises people the most.
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Bree, when ATMs first got installed everywhere in the 70s and 80s, what were bank tellers supposed to do?
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Disappear, I guess?
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Well, that's what a lot of people were predicting at that time.
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You know, you've got a machine that dispenses cash, and that should be the end of tellers.
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Well, what actually happened was the number of U .S bank tellers went up from around 300 ,000 in the mid -70s,
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closer to 600 ,000 by 2010.
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So, economist James Besson has the numbers on this one. Because?
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Well, because the ATM that made a branch cheaper to run meant fewer tellers per branch, so banks opened more branches is.
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And the job of the teller itself actually shifted from just counting cash to helping customers with more complicated stuff.
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Same title, different work, and actually more of them.
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Right.
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This is a version of a very old economic principle, and this is your territory, Jeff.
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Yeah, the very old stuff is always my territory, thanks.
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Yeah, I'm referring specifically to a thing called Jevons paradox, which I've touched on in a previous video of mine.
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It's wrote a book back in 1865, and no, I was not there when it was written, that was called The Coal Question.
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His observation was simple.
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When steam engines got more efficient, you didn't need as much coal to run one.
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So the conventional wisdom held that coal consumption would go down as a result.
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Plot twist, that's not what happened.
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It went up.
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You've seen this movie, haven't you, Bree?
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Well, no spoilers for the folks at home.
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Yes, it went way up.
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And because the more efficient the machine, the engine, well, then the cheaper it got to operate and it could do more work for you.
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And that meant more usage,
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more people found more uses for these machines and therefore coal consumption actually increased.
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That's right.
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And the same pattern shows up with software.
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That's right.
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Same pattern.
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AI makes writing software faster and cheaper, the naive prediction is great.
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Now we need fewer developers.
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But remember, what the Jevons pattern actually predicts is that more software gets written,
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more things get built, that were too expensive or impractical to build before.
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And demand for developers who can now do more actually goes up.
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Which is not what the headlines usually say.
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No, it turns out headlines don't do 160 -year -old economics
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and headline writers don't often look over the other side of the mountain to see might be waiting there.
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Okay, so here's the part I want people to hear.
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Every generation has this exact conversation.
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And it's with the exact same confidence.
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Oh, yeah.
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In 1930, John Maynard Keynes wrote an essay called Economic Possibilities for Our Grandchildren.
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And in it, he coined the phrase technological unemployment.
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His argument, machines are getting so productive that within 100 years,
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we'd all be working 15 -hour weeks and running out of things to do.
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Yeah, we were supposed to all have personal jetpacks by now, too, though.
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But tell me, how's that working out for you, that 15 -hour work week?
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Not so great, if you ask me.
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I'm doing at least three of them every week.
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Well, more is better, then.
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So tell me about it.
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On second thought, don't.
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But you know what no company ever says?
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I think we're finished.
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We're done.
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Nothing else left to do.
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Nope, they don't say that.
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Nature abhors a vacuum, and so do companies.
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They will always fill the void with, wait for it, more work.
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Right.
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But we keep forgetting that.
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In the 1960s, there was a presidential commission on automation because everyone was convinced the machines were about to make labor obsolete.
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In the 1980s, it was Japanese robotics.
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In the 2000s, it was offshoring.
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Every wave had a very smart person saying, this time is different.
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And each time the tools got adopted and humans reorganized around them.
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Because the pattern is in tech eliminates jobs.
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The pattern is tech eliminates tasks and humans invent new jobs around what's left.
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I like your angle here Bree.
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A job is a bundle of tasks.
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So you've got some tasks in the bundle that get automated.
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Well, the bundle regroups.
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Sometimes new bundles form, sometimes people just get to do more interesting parts.
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The Bay Teller got to spend less time counting 20s and start actually helping people.
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The developer today gets to stop writing boilerplate code and start solving the actual problem.
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And from inside the moment this always looks like the exception
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because you can see the tasks getting eliminated in real time and you cannot see the jobs that haven't been invented yet.
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That's because they're not on the other side of the mountain.
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In 1918 -99 nobody saw the motel clerk over here.
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And nobody in 2019 saw the prompt engineer.
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Which is a six figure job now.
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Which is a six figure job now.
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That's exactly the point.
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Somebody watching this video is going to have a job in 2040 with a title
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that would sound completely made up if we said it out loud right now.
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And they're going to be very good at it.
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So if you're early in your career and the headlines are telling you your future is cooked, I'm going to let you in on a little secret.
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You're actually not that special because we've done this before.
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Right.
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They're telling you what everybody's grandparents were told.
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The tools change what the work looks like.
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They don't change the fact that there's still more work to do than we have actual humans to do it.
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Yep.
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So learn the tools.
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Get good at the parts of the work the tools can't do.
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Get comfortable inventing the jobs that don't exist yet, because that's what every generation has actually done.
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Even the ones that we're sure this time is going to be different.
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Especially those.
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In fact, despite what the prophets of doom have been saying,
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the unemployment rate both in the US and globally has remained largely unchanged since the admin of generative AI.
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So what that means is for every horror story of AI caused layoffs, many of
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which were really just a way of hiding poor hiring practices
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there must be a relatively equal number of hirings otherwise the rate would change
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so jeff what's on the other side of this ai mountain well nobody knows for sure
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but just remember this curious people don't get replaced they get liberated
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Vocabolario e note di pronuncia per questa lezione
Questa lezione di conversazione di livello B2 si basa sul video “Every Generation Thinks This Time Is Different: The AI Job Myth”. Questo video contiene 182 frasi e 1877 parole da ripetere con lo shadowing. Il parlato dura 12:33. Chi parla ha un ritmo naturale di circa 150 parole al minuto, vicino a una conversazione quotidiana. Il 84% delle parole rientra nelle 3.000 più comuni dell’inglese; conviene studiare le altre prima di iniziare.
Vocaboli chiave di questo video
Le 15 parole più avanzate del video, con pronuncia e significato:
| Parola | Pronuncia | Significato |
|---|---|---|
| teller sostantivo | /ˈtɛləɹ/ | cassiere |
| motel sostantivo | /moʊˈtɛl/ | motel, autostello |
| invent verbo | /ɪnˈvɛnt/ | inventare |
| bundle sostantivo | /ˈbʌn.dl̩/ | insieme, fascina |
| headline sostantivo | /ˈhɛd.laɪn/ | titolo |
| developer sostantivo | /dɪˈvɛləpɚ/ | sviluppatore, sviluppatrice |
| clerk sostantivo | /klɝk/ | impiegato, impiegata |
| predict verbo | /pɹɪˈdɪkt/ | profetizzare |
| eliminate verbo | /ɪˈlɪm.ɪ.neɪt/ | eliminare |
| barrel sostantivo | /ˈbæɹəl/ | barile, botte |
| manure sostantivo | /məˈnʊɹ/ | letame, stallatico |
| encyclopedia sostantivo | /ɪnˌsaɪkləˈpidi.ə/ | enciclopedia |
| automobile sostantivo | /ˈɔː.tə.məˌbil/ | automobile, auto |
| lamp sostantivo | /ˈlæ̝mp/ | lampada, lampadina |
| disappear verbo | /dɪsəˈpɪɹ/ | sparire, scomparire |
I phrasal verb che sentirai
| Parola | Pronuncia | Significato |
|---|---|---|
| go up verbo | salire | |
| turn out verbo | risultare | |
| figure out verbo | scoprire, rendersi conto | |
| look over verbo | esaminare | |
| make up verbo | /ˌmeɪk ˈʌp/ | comporsi |
Frasi da ripetere
Frasi brevi e complete del video che puoi riutilizzare nella conversazione di tutti i giorni:
- According to my calculations, that's more than half.
- I'm doing at least three of them every week.
- They're telling you what everybody's grandparents were told.
La grammatica di questo video
Le strutture che chi parla usa di più, con le parole esatte del video:
| Struttura | Nel video |
|---|---|
| Present perfect continuous have/has been + -ing — un’azione iniziata prima e ancora in corso | has been doing · have been saying |
| Forma passiva be + participio passato — conta ciò che accade, non chi lo fa | was predicted · has been said · were lost |
| Present perfect have/has + participio passato — un’azione passata che conta ancora adesso | has heard · has been said · has built |
Pronuncia a cui fare attenzione
Chi parla usa 42 contrazioni e forme ridotte, come don't, you're, didn't. Pronunciale nella forma breve, così come le senti.
- I suoni “th”: blacksmith /ˈblæk.smɪθ/, thrill /θɹɪl/
- I suoni “sh” e “zh”: vanish /ˈvænɪʃ/, calculation /ˌkælkjuˈleɪʃn̩/, automation /ˌɔ.təˈmeɪ.ʃən/, offshore /ɒfˈʃɔː(ɹ)/, prediction /pɹɪˈdɪkʃən/
- Parole lunghe — attenzione all’accento: developer /dɪˈvɛləpɚ/, eliminate /ɪˈlɪm.ɪ.neɪt/, encyclopedia /ɪnˌsaɪkləˈpidi.ə/, automobile /ˈɔː.tə.məˌbil/, generative /ˈd͡ʒɛnəɹətɪv/
I suoni difficili per chi parla italiano:
- /h/ — va soffiata, non è muta: headline /ˈhɛd.laɪn/, hauler /hɔlɚ/
- Consonante finale — senza aggiungere una vocale dopo: invent /ɪnˈvɛnt/, clerk /klɝk/, predict /pɹɪˈdɪkt/, eliminate /ɪˈlɪm.ɪ.neɪt/, lamp /ˈlæ̝mp/
- /æ/ — più aperta della “e”: barrel /ˈbæɹəl/, lamp /ˈlæ̝mp/, blacksmith /ˈblæk.smɪθ/, grandparent /ˈɡɹæn(d)pɛəɹənt/, impractical /ɪmˈpɹæktɪkəl/
Come esercitarsi con questo video
- Ascolta tutto il video una volta senza parlare e annota le parole che non conosci.
- Inizia a velocità 0,75×, fai shadowing frase per frase e torna alla velocità normale quando diventa facile.
- Registrati e confronta con l’originale, facendo attenzione a parole come teller, motel, invent.
Cos'è la tecnica dello Shadowing?
Shadowing è una tecnica di apprendimento delle lingue supportata da studi scientifici, originariamente sviluppata per la formazione dei traduttori professionisti e resa popolare dal poliglotta Dr. Alexander Arguelles. Il metodo è semplice ma potente: ascolti un audio in inglese di madrelingua e lo ripeti immediatamente ad alta voce — come un'ombra che segue il parlante con un ritardo di solo 1–2 secondi. A differenza dell'ascolto passivo o degli esercizi di grammatica, lo shadowing costringe il tuo cervello e i muscoli della bocca a elaborare e riprodurre simultaneamente i modelli di discorso reale. La ricerca dimostra che migliora significativamente la precisione della pronuncia, l'intonazione, il ritmo, il discorso connesso, la comprensione dell'ascolto e la fluidità del parlato — rendendolo uno dei metodi più efficaci per la preparazione alla prova di speaking dell'IELTS e per la comunicazione reale in inglese.