Pratica di Shadowing: "AI Existential Risk" Was Invented to Distract Us - Impara a parlare inglese con i video
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So you might have seen this week
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that a charming young man named Jacob Coxon gave the entire
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world a panic attack by quitting his job at the AI company Anthropic
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and saying that he was quitting because he was worried that Anthropic's work could lead to the extinction of humanity.
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And he tweeted that everybody else building AI earnestly believes this.
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Now, the media called him a whistleblower for saying this, but I think that's kind of a weird thing to call him
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when a colleague of his immediately quote tweeted him and said, Jacob is correct, we really do earnestly believe that AI could kill all humans.
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In fact, we think there's a 10% chance within the next decade.
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And then the CEO of the company wrote an entire fucking op-ed saying the exact same thing
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and that we needed to slow down AI development in order to prevent this.
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Oh, and let's not forget that Elon Musk has been saying this shit for the better part of the last decade.
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So how can you be a whistleblower when everybody in your industry not only agrees with you, they also are openly saying the thing you're saying all the time?
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Like, you're not a whistleblower if you quit the hip-hop industry and say, Hey, I'm kind of worried some of those guys are selling drugs.
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Anyway, this has led to, simply put, a culture-wide freakout, where literally everyone in the media,
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in social media, just people who come up to me at the coffee shop and grab me by the lapels is asking, like, is it really gonna happen?
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Is AI really gonna kill all of us?
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Like, people are really afraid about this and they want an answer.
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And I think we need to acknowledge, first of all, this is not an answerable question.
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It's actually designed to be an unanswerable question.
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Like, just the statement, you know, there's a 10% chance that humanity will become extinct in the next decade.
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How would you go about calculating such a thing or even refuting it?
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Like, I can make any argument I want about what LLMs can do and someone can make a counterargument.
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No one is going to be convinced, right?
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But I think there is something more interesting going on in the Jacob Coxon story because it's that phrase,
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everyone at Anthropic believes that AI is an existential risk.
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Everyone in the AI industry believes that that is true.
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Because think about this, every organization, right, has to instill some kind of beliefs among its members in order to do the work it does, right?
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I mean, everybody at Goldman Sachs believes the free market is great, capitalism is the best system, and that they are the wealth creators who deserve big bonuses.
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Everyone in the Mormon Church believes they should all tithe 10% of their income
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and that they each get a special planet when they die.
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And everyone who worked at Philip Morris in the 80s believed
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that cigarettes tasted great and did not cause any of that nasty cancer.
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You know, there's that Upton Sinclair quote, It's difficult to get a man to understand something when a salary depends on his not understanding it.
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While the opposite is also true.
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It's guaranteed that someone will believe something if their salary depends on them believing it.
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Now, let's just grant that all the people in these organizations definitely know things about finance
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and Mormonism and cigarettes and AI that you might not know because they are insiders and you are not.
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They have access to information and experiences that you do not have.
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And that might even make it a little bit difficult for you to win an argument with them.
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But arguing with their belief, trying to figure out whether or not its truth value is true or false, is not the only way to take a skeptical attitude towards it.
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We could also ask, what work is the belief doing for them?
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What does the thing that they believe allow the organization they're a part of to do
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that it wouldn't be able to do if the people in the organization didn't believe that thing?
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And this started to become clearer to me
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when I started listening to the actual claims that Jacob Coxon was making because a lot of them don't really add up.
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Like, here's what he actually said on Anderson Cooper.
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It's easiest to understand it if you think about real things that happened two months ago, OpenAI agents, AIs, hacked into third-party infrastructure entirely at their own accord.
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And this was like a concentrated hacking spree that they carried out of their own volition.
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And I think that if you extrapolate into the future the level of capabilities of these AIs with the same independent volition, they could cause extreme havoc.
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For example, hacking critical infrastructure, building extinction-level bioweapons.
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Only on Tuesday, OpenAI solved a Millennium problem, one of the biggest unsolved open problems in mathematics, purely autonomously using an AI.
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So the idea that AI can build an extinction-level bioweapon is kind of ridiculous.
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Like, here's a thread from David Bellamy, one of the few AI researchers who's actually worked in bioscience, explaining why that's, in his words, bogus.
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Because basically, in order for the AI to engineer a deadly virus,
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some humans would have to build a $100 million bio lab that is both capable of being controlled entirely via AI, which has, you know, cold storage and,
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like, cell culture rooms, all of which is API-driven, and which is specifically supplied with the base materials of deadly viruses at scale.
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And, you know, we could all just, um, not do that, right?
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We could just choose not to build the lab.
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In fact, if we were to build such a lab, would it be accurate to say that the AI designed the bioweapon?
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Or would you say that we, the humans, designed the bioweapon by creating the exact, like, necessary conditions for it to happen?
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Then there's the idea that the AI solved a millennium math problem, and yeah, OpenAI did announce that they did this, but then a few days later,
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the mathematician, who was already working on the problem and was about to solve it, said that OpenAI had heard a rumor he was about to solve it, stole the approach he came up with,
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fed it into their AI, and then spent $20 million worth of computation on solving it before he could.
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Now, OpenAI denied this, and the story is pretty complicated, But at a minimum, OpenAI was not truthful when it said that the AI solved the problem all by itself.
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The truth was, they got help through normal human channels.
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The human channels of rumors and stealing.
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And they did not disclose that.
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And finally, there's the idea that a swarm of AIs hacked another company entirely of their own volition.
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So this is the example that freaked people out the most, and it's the one that people throw in my face the most when I express any skepticism about existential risk.
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Adam, didn't you hear?
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You know, the agents are hacking all by themselves!
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Well, we need to ask, like, is this story real?
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And yes, I mean, it did happen, but the question is, how do we frame what happened?
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Because OpenAI framed it as that they gave a swarm of chatbots a hacking problem to solve, but that in order to solve it,
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the chatbots independently decided to hack into another company's servers to see if the answer was there, and that they first hacked into a bunch of insecure message boards
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so they could talk amongst themselves in order to do so.
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And yeah, that sounds like pretty smart behavior, pretty unpredictable behavior.
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But, you know, my friends Ed Zitron and Cory Doctorow have both covered this story, Ed on his wonderful podcast and Cory on his wonderful blog.
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And they explain it much better than I do, so I'll put the links down below.
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But the short version is, if you look into the details of what actually happened in this story, you can frame it quite differently.
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Because what they actually did was they hooked up Python script to an LLM
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that was trained on a database of specifically years of real-life hackers who were completing real-life hacking challenges.
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The database was composed of their code and also the conversations between the hackers
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and you know what those hackers did in that code and in those conversations?
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They hacked into their competitors to see if they had the answers and they conspired about doing so on insecure message boards.
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You know why they did that?
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Because they were trying to complete hacking challenges.
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So it's not surprising that an AI trained almost exclusively on that data set ended up hacking in that particular way.
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In fact, that was entirely predictable.
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It should have been predicted by the people at OpenAI.
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Why the fuck were they acting surprised?
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They basically set up a hacking machine, pressed go, walked away for the weekend, and came back on Monday saying, We're all trying to find the guy who did this.
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So if you look at all the public statements of the companies, the CEOs, Jacob Coxon together, There's a clear pattern where they declare
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that the AI did something on its own
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when really they were the ones who did it They were the droids they're looking for.
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You are Pagliacci motherfuckers.
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The risk, the danger is never their actions The risk is always the thing the AI did
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and if you inflate
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that idea as large as possible you get Existential risk you get the idea
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that the AI is eventually going to do something so dangerous It's going to wipe out all of humanity.
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And what work does that belief do for them?
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Well, it absolves them of any responsibility for their actions now.
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It allows them to justify anything they do.
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Because if they genuinely believe that AI is an existential risk, and they believe that it's going to be built no matter what,
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and they believe that they're the only ones who really understand the existential risk, then that means that they must be the ones to build AI,
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and anything that they do to advance that goal is therefore worthwhile.
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In other words, by focusing on this largely hypothetical existential threat,
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they are able to ignore all the bad shit that they are currently doing right now.
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They're able to ignore the fact that the data centers they're building are using so much energy, they're basically reversing a generation's worth of progress on climate change,
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which is a real threat that is currently killing people around the world.
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They're ignoring the fact
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that their product is currently being used by bosses to fire
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employees in order to put in place an AI system that demonstrably cannot do their jobs yet.
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And they're able to ignore the fact that their technology is currently being used to kill civilians in Gaza.
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That is not science fiction.
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That is a threat right now and you'll notice that Jacob Coxon didn't talk about that threat.
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You'll notice that Dario Amade doesn't talk about that threat.
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Why aren't they going on Anderson Cooper and talking about that shit?
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Because if they acknowledge that those risks, those current harms that they are causing,
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were as or more important than their made up 10% risk of extinction in the next decade, well then they wouldn't be able to build AI anymore.
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Or at least they wouldn't be able to build it with a clear conscience.
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It is difficult to get a man to understand something, when his salary depends on his not understanding it.
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In fact, what if his salary depended on the lack of understanding so much, that he had to make sure the rest of us didn't understand it either.
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Because for the last year, we the public have been pretty upset about AI, right?
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But we've been upset about the real harms it's been causing.
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We've been upset about getting fired from our jobs, we've been upset about the data center in our backyard, about the water, about climate change, about our electricity bills going up.
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And as a result, the public really thinks AI bad, right?
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But what if AI was not bad in a way that we could put our finger on?
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What if AI was bad in a hypothetical way?
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Now, because of the existential threat risk, AI bad is getting a little bit confused, isn't it?
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Like, is AI bad because of the data center?
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Or is AI bad because it's going to wipe out all of humanity?
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Which one is the bigger risk?
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Well, there's no way to say.
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Maybe we need to be worried about China building AI before us.
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Maybe the only way to forestall the bad things about AI is to build AI even faster.
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Who's to say?
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And, you know, if the public is confused, if the public can't make up its mind, well then, the people on the inside, the people in the industry,
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the people who all believe that they know what the risk really is, well then, they get to call the shots, don't they?
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Whether it is true or not, and whether it is genuine or not, the belief within the AI community
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that AI represents an existential threat works to push the public's worries about AI into things that are unprovable and hypothetical
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in order to distract us from the current harms the industry is causing.
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That is the work that this belief does for them.
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And as a result, we should be skeptical of it.
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And you know what the most ironic thing is?
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Is that there's
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so many people who have been trying to raise the alarm about the real concrete harms
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that this industry is doing to the world that we live in today.
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There's thinkers like Timny Gebru and Emily Bender who have been calling bullshit on this industry from the beginning.
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There's reporters like Karen Howe.
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There's the average people who show up to their city council meetings to protest at data center.
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There are so many people who are worried about the real harms.
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But those people's tweets don't get 150 million views on X.
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Those people don't get invited onto Anderson Cooper nearly as often
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as the insiders who can tell us what all the people inside the industry believe.
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But you know, when everybody in a group believes
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that the work they are doing has some unmeasurable chance of bringing about the end of the world
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and that's why their precious work cannot be interrupted, that doesn't sound like a company at all.
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That sounds like a cult.
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And you know, if you're dealing with a cult, if you want to know the truth about the things they believe, you don't start by asking the people inside the cult.
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You don't start by asking them, hey, is it true that we're all gonna die unless we do as you say?
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No, you start by listening really, really hard to the actual critics on the outside.
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Vocabolario e note di pronuncia per questa lezione
Questa lezione di conversazione di livello B2 si basa sul video “"AI Existential Risk" Was Invented to Distract Us”. Questo video contiene 162 frasi e 2554 parole da ripetere con lo shadowing. Il parlato dura 13:21. Chi parla va veloce, circa 191 parole al minuto: aspettati suoni legati e ridotti. Il 84% delle parole rientra nelle 3.000 più comuni dell’inglese; conviene studiare le altre prima di iniziare. 31 delle sue 162 frasi sono domande: un buon esercizio per l’intonazione interrogativa e le risposte brevi.
Vocaboli chiave di questo video
Le 15 parole più avanzate del video, con pronuncia e significato:
| Parola | Pronuncia | Significato |
|---|---|---|
| existential aggettivo | /ˌɛɡzɪˈstɛnʃl̩/ | esistenziale |
| depend verbo | /dɪˈpɛnd/ | dipendere |
| volition sostantivo | /voʊˈlɪʃ(ə)n/ | volontà, volizione |
| hypothetical aggettivo | /ˌhaɪpəˈθɛtɪkəl/ | ipotetico |
| hacker sostantivo | /hækəɹ/ | principiante |
| swarm sostantivo | /swɔɹm/ | sciame, nugolo |
| skeptical aggettivo | /ˈskɛptɪkəl/ | scettico |
| millennium sostantivo | /mɪˈlɛnɪəm/ | millennio |
| insecure aggettivo | /ɪnsəˈkjʊɹ/ | insicuro, malsicuro |
| rumor sostantivo | /ˈɹumɚ/ | voce, voci di corridoio |
| insider sostantivo | /ɪnˈsaɪdɚ/ | iniziato, basista |
| wipe verbo | /waɪp/ | asciugare, pulire |
| cigarette sostantivo | /ˈsɪɡəɹɛt/ | sigaretta |
| mathematics sostantivo | /mæθ(.ə)ˈmæt.ɪks/ | matematica |
| acknowledge verbo | /əkˈnɑ.lɪd͡ʒ/ | riconoscere, ammettere |
I phrasal verb che sentirai
| Parola | Pronuncia | Significato |
|---|---|---|
| make up verbo | /ˌmeɪk ˈʌp/ | comporsi |
| wipe out verbo | obliterare, spazzare via | |
| add up verbo | sommarsi | |
| come up with verbo | ideare, escogitare | |
| end up verbo | andare a finire, finire | |
| figure out verbo | scoprire, rendersi conto | |
| go up verbo | salire | |
| set up verbo | /ˌsɛt ˈʌp/ | preparare, installare |
Frasi da ripetere
Frasi brevi e complete del video che puoi riutilizzare nella conversazione di tutti i giorni:
- We could also ask, what work is the belief doing for them?
- Adam, didn't you hear?
- You know why they did that?
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 saying · it's been causing · have been trying |
| Frasi relative who / which + frase — un’informazione in più su una persona o una cosa | people who come · everyone who worked · guy who did |
| Forma passiva be + participio passato — conta ciò che accade, non chi lo fa | being controlled · is specifically supplied · was trained |
| Present perfect have/has + participio passato — un’azione passata che conta ancora adesso | has led · have been · we've been |
Pronuncia a cui fare attenzione
Chi parla usa 41 contrazioni e forme ridotte, come they're, don't, didn't. Pronunciale nella forma breve, così come le senti.
- I suoni “th”: hypothetical /ˌhaɪpəˈθɛtɪkəl/, mathematics /mæθ(.ə)ˈmæt.ɪks/, mathematician /ˌmæθ.(ə.)məˈtɪʃ.ən/, thinker /ˈθɪŋ.kɚ/, truthful /ˈtɹuːθ.f(ə)l/
- I suoni “sh” e “zh”: existential /ˌɛɡzɪˈstɛnʃl̩/, extinction /ɪkˈstɪŋkʃən/, volition /voʊˈlɪʃ(ə)n/, computation /ˌkɑmpjʊˈteɪʃn̩/, mathematician /ˌmæθ.(ə.)məˈtɪʃ.ən/
- Parole lunghe — attenzione all’accento: bioweapon /ˈbaɪ.oʊˌwɛ.pən/, hypothetical /ˌhaɪpəˈθɛtɪkəl/, mathematics /mæθ(.ə)ˈmæt.ɪks/, demonstrably /diˈmɑnstrəbli/, extrapolate /ɛkˈstɹæp.əˌleɪt/
I suoni difficili per chi parla italiano:
- /h/ — va soffiata, non è muta: hypothetical /ˌhaɪpəˈθɛtɪkəl/, hacker /hækəɹ/, havoc /ˈhævək/
- Consonante finale — senza aggiungere una vocale dopo: depend /dɪˈpɛnd/, tweet /ˈtwiːt/, chatbot /ˈtʃætbɑt/, wipe /waɪp/, cigarette /ˈsɪɡəɹɛt/
- /æ/ — più aperta della “e”: hacker /hækəɹ/, chatbot /ˈtʃætbɑt/, mathematics /mæθ(.ə)ˈmæt.ɪks/, absolve /æbˈzɑlv/, answerable /ˈæn.səɹ.ə.bl/
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 existential, depend, volition.
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.