Shadowing Practice: "AI Existential Risk" Was Invented to Distract Us - Learn English Speaking with 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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Vocabulary and speaking notes for this lesson
This B2 speaking lesson is built on the video “"AI Existential Risk" Was Invented to Distract Us”. This video has 162 sentences and 2554 words to shadow. The speech runs for 13:21. The speaker talks fast, about 191 words per minute, so expect linked and reduced sounds. 84% of the words are among the 3,000 most common in English; the rest is worth studying before you start. 31 of its 162 sentences are questions, so it is good practice for question intonation and short answers.
Key vocabulary in this video
The 15 most advanced words in the video, with pronunciation and meaning:
| Word | Pronunciation | Meaning |
|---|---|---|
| existential adjective | /ˌɛɡzɪˈstɛnʃl̩/ | Of or relating to existence. |
| bioweapon noun | /ˈbaɪ.oʊˌwɛ.pən/ | Any weapon designed to be used in biological warfare. |
| extinction noun | /ɪkˈstɪŋkʃən/ | The action of making or becoming extinct; annihilation. |
| depend verb | /dɪˈpɛnd/ | To be contingent or conditioned; to have something as a necessary condition |
| volition noun | /voʊˈlɪʃ(ə)n/ | A conscious choice or decision. |
| hypothetical adjective | /ˌhaɪpəˈθɛtɪkəl/ | Based upon a hypothesis; conjectural. |
| hacker noun | /hækəɹ/ | Someone who hacks. |
| tweet noun | /ˈtwiːt/ | The sound of a bird; any short high-pitched sound or whistle. |
| chatbot noun | /ˈtʃætbɑt/ | A computer program that holds conversations through a chat room. |
| earnestly adverb | /ˈɝnɪstli/ | In an earnest manner; being very sincere; putting forth genuine effort. |
| swarm noun | /swɔɹm/ | A large number of insects or other bugs (e.g. centipedes), especially when in motion or (for bees) migrating to a new colony. |
| skeptical adjective | /ˈskɛptɪkəl/ | Having, or expressing doubt; questioning. |
| millennium noun | /mɪˈlɛnɪəm/ | A period of time consisting of one thousand years. |
| insecure adjective | /ɪnsəˈkjʊɹ/ | Not secure. |
| rumor noun | /ˈɹumɚ/ | A statement or claim of questionable accuracy, from no known reliable source, usually spread by word of mouth. |
Phrasal verbs you will hear
| Word | Pronunciation | Meaning |
|---|---|---|
| make up verb | /ˌmeɪk ˈʌp/ | To constitute, to compose. |
| wipe out verb | To destroy (especially, a large number or complete set of people or things); to obliterate. | |
| add up verb | To take the sum of; to total. | |
| come up to verb | To approach. | |
| come up with verb | To manage to produce, deliver, or present (something) by inventing, creating, thinking of, or obtaining it. | |
| end up verb | To bring to a conclusion. | |
| figure out verb | To come to understand; to discover or find a solution; to deduce. | |
| go up verb | To move upwards. |
Sentences worth repeating
Short, complete lines from the video that you can reuse in everyday conversation:
- We could also ask, what work is the belief doing for them?
- Adam, didn't you hear?
- You know why they did that?
Grammar in this video
The structures the speaker uses most, with the exact words from the video:
| Structure | In the video |
|---|---|
| Present perfect continuous have/has been + -ing — an action that started earlier and is still going on | has been saying · it's been causing · have been trying |
| Relative clauses who / which + clause — extra information about a person or thing | people who come · everyone who worked · guy who did |
| Passive voice be + past participle — the focus is on what happens, not who does it | being controlled · is specifically supplied · was trained |
| Present perfect have/has + past participle — a past action that still matters now | has led · have been · we've been |
Pronunciation to watch
The speaker uses 41 contractions and reduced forms, such as they're, don't, didn't. Say them the short way, as you hear them.
- The “th” sounds: hypothetical /ˌhaɪpəˈθɛtɪkəl/, mathematics /mæθ(.ə)ˈmæt.ɪks/, mathematician /ˌmæθ.(ə.)məˈtɪʃ.ən/, thinker /ˈθɪŋ.kɚ/, truthful /ˈtɹuːθ.f(ə)l/
- The “sh” and “zh” sounds: existential /ˌɛɡzɪˈstɛnʃl̩/, extinction /ɪkˈstɪŋkʃən/, volition /voʊˈlɪʃ(ə)n/, computation /ˌkɑmpjʊˈteɪʃn̩/, mathematician /ˌmæθ.(ə.)məˈtɪʃ.ən/
- Long words — get the stress right: bioweapon /ˈbaɪ.oʊˌwɛ.pən/, hypothetical /ˌhaɪpəˈθɛtɪkəl/, mathematics /mæθ(.ə)ˈmæt.ɪks/, demonstrably /diˈmɑnstrəbli/, extrapolate /ɛkˈstɹæp.əˌleɪt/
How to practise with this video
- Listen to the whole video once without speaking and note the words you do not know.
- Start at 0.75× speed, shadow it sentence by sentence, then go back to normal speed once it feels easy.
- Record yourself and compare with the original, paying attention to words like existential, bioweapon, extinction.
What is the Shadowing Technique?
Shadowing is a science-backed language learning technique originally developed for professional interpreter training and popularized by polyglot Dr. Alexander Arguelles. The method is simple but powerful: you listen to native English audio and immediately repeat it out loud — like a shadow following the speaker with just a 1–2 second delay. Unlike passive listening or grammar drills, shadowing forces your brain and mouth muscles to simultaneously process and reproduce real speech patterns. Research shows it significantly improves pronunciation accuracy, intonation, rhythm, connected speech, listening comprehension, and speaking fluency — making it one of the most effective methods for IELTS Speaking preparation and real-world English communication.