Prática de Shadowing: "AI Existential Risk" Was Invented to Distract Us - Aprenda a falar inglês com vídeo
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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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Vocabulário e dicas de fala para esta lição
Esta aula de conversação de nível B2 usa o vídeo “"AI Existential Risk" Was Invented to Distract Us”. Este vídeo tem 162 frases e 2554 palavras para praticar shadowing. A fala dura 13:21. O falante fala rápido, cerca de 191 palavras por minuto, então espere sons ligados e reduzidos. 84% das palavras estão entre as 3.000 mais comuns do inglês; vale a pena estudar o restante antes de começar. 31 das 162 frases são perguntas, por isso é um bom treino para a entonação de perguntas e respostas curtas.
Vocabulário principal deste vídeo
As 15 palavras mais avançadas do vídeo, com pronúncia e significado:
| Palavra | Pronúncia | Significado |
|---|---|---|
| existential adjetivo | /ˌɛɡzɪˈstɛnʃl̩/ | existencial |
| bioweapon substantivo | /ˈbaɪ.oʊˌwɛ.pən/ | arma biológica |
| extinction substantivo | /ɪkˈstɪŋkʃən/ | extinção |
| depend verbo | /dɪˈpɛnd/ | depender |
| volition substantivo | /voʊˈlɪʃ(ə)n/ | volição |
| hypothetical adjetivo | /ˌhaɪpəˈθɛtɪkəl/ | hipotético |
| tweet substantivo | /ˈtwiːt/ | pio |
| chatbot substantivo | /ˈtʃætbɑt/ | chatbot |
| swarm substantivo | /swɔɹm/ | enxame, nuvem |
| skeptical adjetivo | /ˈskɛptɪkəl/ | cético, céptico |
| millennium substantivo | /mɪˈlɛnɪəm/ | milénio, milênio |
| insecure adjetivo | /ɪnsəˈkjʊɹ/ | inseguro |
| rumor substantivo | /ˈɹumɚ/ | rumor, boato |
| wipe verbo | /waɪp/ | esfregar, enxugar |
| cigarette substantivo | /ˈsɪɡəɹɛt/ | cigarro |
Phrasal verbs que você vai ouvir
| Palavra | Pronúncia | Significado |
|---|---|---|
| make up verbo | /ˌmeɪk ˈʌp/ | compensar |
| wipe out verbo | aniquilar, exterminar | |
| come up with verbo | pensar (em), alcançar | |
| end up verbo | terminar, acabar | |
| figure out verbo | descobrir, deduzir | |
| go up verbo | subir | |
| hook up verbo | conectar | |
| set up verbo | /ˌsɛt ˈʌp/ | preparar |
Frases que vale a pena repetir
Frases curtas e completas do vídeo que você pode usar na conversa do dia a dia:
- We could also ask, what work is the belief doing for them?
- Adam, didn't you hear?
- You know why they did that?
Gramática neste vídeo
As estruturas que o falante mais usa, com as palavras exatas do vídeo:
| Estrutura | No vídeo |
|---|---|
| Present perfect continuous have/has been + -ing — uma ação que começou antes e continua | has been saying · it's been causing · have been trying |
| Orações relativas who / which + oração — informação extra sobre uma pessoa ou coisa | people who come · everyone who worked · guy who did |
| Voz passiva be + particípio passado — o foco está no que acontece, não em quem faz | being controlled · is specifically supplied · was trained |
| Present perfect have/has + particípio passado — uma ação passada que ainda importa agora | has led · have been · we've been |
Pronúncia para ficar de olho
O falante usa 41 contrações e formas reduzidas, como they're, don't, didn't. Diga-as na forma curta, do jeito que você ouve.
- Os sons de “th”: hypothetical /ˌhaɪpəˈθɛtɪkəl/, mathematics /mæθ(.ə)ˈmæt.ɪks/, mathematician /ˌmæθ.(ə.)məˈtɪʃ.ən/, thinker /ˈθɪŋ.kɚ/, truthful /ˈtɹuːθ.f(ə)l/
- Os sons de “sh” e “zh”: existential /ˌɛɡzɪˈstɛnʃl̩/, extinction /ɪkˈstɪŋkʃən/, volition /voʊˈlɪʃ(ə)n/, computation /ˌkɑmpjʊˈteɪʃn̩/, mathematician /ˌmæθ.(ə.)məˈtɪʃ.ən/
- Palavras longas — acerte a sílaba tônica: bioweapon /ˈbaɪ.oʊˌwɛ.pən/, hypothetical /ˌhaɪpəˈθɛtɪkəl/, mathematics /mæθ(.ə)ˈmæt.ɪks/, demonstrably /diˈmɑnstrəbli/, extrapolate /ɛkˈstɹæp.əˌleɪt/
Sons difíceis para falantes de português:
- Consoante final — sem acrescentar um “i” depois: depend /dɪˈpɛnd/, tweet /ˈtwiːt/, chatbot /ˈtʃætbɑt/, wipe /waɪp/, cigarette /ˈsɪɡəɹɛt/
- /l/ final — a língua toca o céu da boca, não vira “u”: hypothetical /ˌhaɪpəˈθɛtɪkəl/, skeptical /ˈskɛptɪkəl/, answerable /ˈæn.səɹ.ə.bl/, forestall /fɔː(ɹ)ˈstɔːl/, instill /ɪnˈstɪl/
- /h/ — um sopro suave, diferente do “r”: hypothetical /ˌhaɪpəˈθɛtɪkəl/, hacker /hækəɹ/, havoc /ˈhævək/
Como praticar com este vídeo
- Ouça o vídeo inteiro uma vez sem falar e anote as palavras que você não conhece.
- Comece na velocidade 0,75×, faça shadowing frase por frase e volte à velocidade normal quando ficar fácil.
- Grave a sua voz e compare com o original, prestando atenção a palavras como existential, bioweapon, extinction.
O que é a Técnica de Shadowing?
Shadowing é uma técnica de aprendizado de idiomas com base científica, originalmente desenvolvida para o treinamento de intérpretes profissionais. O método é simples, mas poderoso: você ouve áudio em inglês nativo e repete imediatamente em voz alta — como uma sombra seguindo o falante com 1-2 segundos de atraso. Pesquisas mostram melhora significativa na precisão da pronúncia, entonação, ritmo, sons conectados, compreensão auditiva e fluência na fala.