쉐도잉 연습: "AI Existential Risk" Was Invented to Distract Us - 영상으로 영어 말하기 배우기

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So you might have seen this week

that a charming young man named Jacob Coxon gave the entire

world a panic attack by quitting his job at the AI company Anthropic

and saying that he was quitting because he was worried that Anthropic's work could lead to the extinction of humanity.

And he tweeted that everybody else building AI earnestly believes this.

Now, the media called him a whistleblower for saying this, but I think that's kind of a weird thing to call him

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.

In fact, we think there's a 10% chance within the next decade.

And then the CEO of the company wrote an entire fucking op-ed saying the exact same thing

and that we needed to slow down AI development in order to prevent this.

Oh, and let's not forget that Elon Musk has been saying this shit for the better part of the last decade.

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?

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.

Anyway, this has led to, simply put, a culture-wide freakout, where literally everyone in the media,

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?

Is AI really gonna kill all of us?

Like, people are really afraid about this and they want an answer.

And I think we need to acknowledge, first of all, this is not an answerable question.

It's actually designed to be an unanswerable question.

Like, just the statement, you know, there's a 10% chance that humanity will become extinct in the next decade.

How would you go about calculating such a thing or even refuting it?

Like, I can make any argument I want about what LLMs can do and someone can make a counterargument.

No one is going to be convinced, right?

But I think there is something more interesting going on in the Jacob Coxon story because it's that phrase,

everyone at Anthropic believes that AI is an existential risk.

Everyone in the AI industry believes that that is true.

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?

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.

Everyone in the Mormon Church believes they should all tithe 10% of their income

and that they each get a special planet when they die.

And everyone who worked at Philip Morris in the 80s believed

that cigarettes tasted great and did not cause any of that nasty cancer.

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.

While the opposite is also true.

It's guaranteed that someone will believe something if their salary depends on them believing it.

Now, let's just grant that all the people in these organizations definitely know things about finance

and Mormonism and cigarettes and AI that you might not know because they are insiders and you are not.

They have access to information and experiences that you do not have.

And that might even make it a little bit difficult for you to win an argument with them.

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.

We could also ask, what work is the belief doing for them?

What does the thing that they believe allow the organization they're a part of to do

that it wouldn't be able to do if the people in the organization didn't believe that thing?

And this started to become clearer to me

when I started listening to the actual claims that Jacob Coxon was making because a lot of them don't really add up.

Like, here's what he actually said on Anderson Cooper.

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.

And this was like a concentrated hacking spree that they carried out of their own volition.

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.

For example, hacking critical infrastructure, building extinction-level bioweapons.

Only on Tuesday, OpenAI solved a Millennium problem, one of the biggest unsolved open problems in mathematics, purely autonomously using an AI.

So the idea that AI can build an extinction-level bioweapon is kind of ridiculous.

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.

Because basically, in order for the AI to engineer a deadly virus,

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,

like, cell culture rooms, all of which is API-driven, and which is specifically supplied with the base materials of deadly viruses at scale.

And, you know, we could all just, um, not do that, right?

We could just choose not to build the lab.

In fact, if we were to build such a lab, would it be accurate to say that the AI designed the bioweapon?

Or would you say that we, the humans, designed the bioweapon by creating the exact, like, necessary conditions for it to happen?

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,

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,

fed it into their AI, and then spent $20 million worth of computation on solving it before he could.

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.

The truth was, they got help through normal human channels.

The human channels of rumors and stealing.

And they did not disclose that.

And finally, there's the idea that a swarm of AIs hacked another company entirely of their own volition.

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.

Adam, didn't you hear?

You know, the agents are hacking all by themselves!

Well, we need to ask, like, is this story real?

And yes, I mean, it did happen, but the question is, how do we frame what happened?

Because OpenAI framed it as that they gave a swarm of chatbots a hacking problem to solve, but that in order to solve it,

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

so they could talk amongst themselves in order to do so.

And yeah, that sounds like pretty smart behavior, pretty unpredictable behavior.

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.

And they explain it much better than I do, so I'll put the links down below.

But the short version is, if you look into the details of what actually happened in this story, you can frame it quite differently.

Because what they actually did was they hooked up Python script to an LLM

that was trained on a database of specifically years of real-life hackers who were completing real-life hacking challenges.

The database was composed of their code and also the conversations between the hackers

and you know what those hackers did in that code and in those conversations?

They hacked into their competitors to see if they had the answers and they conspired about doing so on insecure message boards.

You know why they did that?

Because they were trying to complete hacking challenges.

So it's not surprising that an AI trained almost exclusively on that data set ended up hacking in that particular way.

In fact, that was entirely predictable.

It should have been predicted by the people at OpenAI.

Why the fuck were they acting surprised?

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.

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

that the AI did something on its own

when really they were the ones who did it They were the droids they're looking for.

You are Pagliacci motherfuckers.

The risk, the danger is never their actions The risk is always the thing the AI did

and if you inflate

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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이 레슨의 어휘와 말하기 포인트

이 B2 수준 말하기 레슨은 영상 “"AI Existential Risk" Was Invented to Distract Us”을(를) 바탕으로 합니다. 이 영상에는 섀도잉할 문장 162개와 단어 2554개가 있습니다. 말하는 구간의 길이는 13:21입니다. 화자는 분당 약 191단어로 빠르게 말하므로 연음과 약하게 발음되는 소리가 많습니다. 단어의 84%가 영어에서 가장 많이 쓰이는 3,000단어에 속합니다. 나머지는 연습 전에 미리 확인해 두세요. 전체 162문장 중 31문장이 질문이어서 의문문 억양과 짧은 대답을 연습하기에 좋습니다.

이 영상의 핵심 어휘

영상에서 가장 어려운 단어 15개를 발음, 뜻과 함께 정리했습니다.

단어	발음	뜻
existential 형용사	/ˌɛɡzɪˈstɛnʃl̩/	실존적
extinction 명사	/ɪkˈstɪŋkʃən/	멸종
depend 동사	/dɪˈpɛnd/	의존하다, ...에 달려 있다
volition 명사	/voʊˈlɪʃ(ə)n/	의지력
hypothetical 형용사	/ˌhaɪpəˈθɛtɪkəl/	가설적
tweet 명사	/ˈtwiːt/	트윗, 트위트
chatbot 명사	/ˈtʃætbɑt/	챗봇
swarm 명사	/swɔɹm/	떼, 무리
millennium 명사	/mɪˈlɛnɪəm/	천년, 천년기
rumor 명사	/ˈɹumɚ/	소문, 풍문
insider 명사	/ɪnˈsaɪdɚ/	내부자, 인사이더
wipe 동사	/waɪp/	닦다
cigarette 명사	/ˈsɪɡəɹɛt/	담배, 궐련
mathematics 명사	/mæθ(.ə)ˈmæt.ɪks/	수학
acknowledge 동사	/əkˈnɑ.lɪd͡ʒ/	승인하다, 인정하다

영상에 나오는 구동사

단어	뜻
wipe out 동사	무찌르다
go up 동사	올라가다

따라 말해 볼 만한 문장

영상에 나오는 짧고 완결된 문장으로, 일상 대화에서 그대로 쓸 수 있습니다:

We could also ask, what work is the belief doing for them?
Adam, didn't you hear?
You know why they did that?

이 영상의 문법

화자가 가장 많이 쓰는 문형을 영상 속 실제 표현과 함께 정리했습니다.

문형	영상 속 표현
현재완료진행 have/has been + -ing — 전에 시작해 지금도 계속되는 동작	has been saying · it's been causing · have been trying
관계절 who / which + 절 — 사람이나 사물에 대한 추가 정보	people who come · everyone who worked · guy who did
수동태 be + 과거분사 — 누가 하는지보다 무슨 일이 일어나는지에 초점	being controlled · is specifically supplied · was trained
현재완료 have/has + 과거분사 — 과거의 일이 지금도 관련이 있을 때	has led · have been · we've been

주의할 발음

화자는 they're, don't, didn't 같은 축약형과 약화된 형태를 41번 사용합니다. 들리는 대로 짧게 발음하세요.

“th” 소리: hypothetical /ˌhaɪpəˈθɛtɪkəl/, mathematics /mæθ(.ə)ˈmæt.ɪks/, mathematician /ˌmæθ.(ə.)məˈtɪʃ.ən/, thinker /ˈθɪŋ.kɚ/, truthful /ˈtɹuːθ.f(ə)l/
“sh”와 “zh” 소리: existential /ˌɛɡzɪˈstɛnʃl̩/, extinction /ɪkˈstɪŋkʃən/, volition /voʊˈlɪʃ(ə)n/, computation /ˌkɑmpjʊˈteɪʃn̩/, mathematician /ˌmæθ.(ə.)məˈtɪʃ.ən/
긴 단어 — 강세 위치에 주의: bioweapon /ˈbaɪ.oʊˌwɛ.pən/, hypothetical /ˌhaɪpəˈθɛtɪkəl/, mathematics /mæθ(.ə)ˈmæt.ɪks/, demonstrably /diˈmɑnstrəbli/, extrapolate /ɛkˈstɹæp.əˌleɪt/

한국어 화자가 어려워하는 소리:

/f/ — ㅍ(/p/)으로 바꾸지 말고 윗니를 아랫입술에 대기: forestall /fɔː(ɹ)ˈstɔːl/, inflate /ɪnˈfleɪt/, refute /ɹɪˈfjuːt/, truthful /ˈtɹuːθ.f(ə)l/, justify /ˈd͡ʒʌstɪfaɪ/
/v/ — ㅂ(/b/)과 구별하기: volition /voʊˈlɪʃ(ə)n/, absolve /æbˈzɑlv/, unsolved /ʌnˈsɑlvd/, havoc /ˈhævək/, civilians /sɪˈvɪl.jənz/
/z/ — ㅈ이 아니라 성대를 울리는 /s/: existential /ˌɛɡzɪˈstɛnʃl̩/, absolve /æbˈzɑlv/, compose /kəmˈpəʊz/, skepticism /ˈskɛp.tɪˌsɪ.zəm/, disclose /dɪsˈkləʊz/

이 영상으로 연습하는 방법

먼저 말하지 않고 영상을 끝까지 듣고 모르는 단어를 적어 둡니다.
0.75배속으로 한 문장씩 섀도잉을 시작하고, 익숙해지면 보통 속도로 돌아갑니다.
자신의 목소리를 녹음해 원본과 비교하고, existential, extinction, depend 같은 단어에 특히 주의합니다.

쉐도잉이란? 영어 실력을 빠르게 키우는 과학적 방법

쉐도잉(Shadowing)은 원래 전문 통역사 훈련을 위해 개발된 언어 학습 기법으로, 다언어 학자인 Dr. Alexander Arguelles에 의해 대중화된 방법입니다. 핵심 원리는 간단하지만 매우 강력합니다: 원어민의 영어를 들으면서 1~2초의 짧은 지연으로 즉시 소리 내어 따라 말하는 것——마치 '그림자(shadow)'처럼 화자를 따라가는 것입니다. 문법 공부나 수동적인 청취와 달리, 쉐도잉은 뇌와 입 근육이 동시에 실시간으로 영어를 처리하고 재현하도록 훈련합니다. 연구에 따르면 이 방법은 발음 정확도, 억양, 리듬, 연음, 청취력, 말하기 유창성을 크게 향상시킵니다. IELTS 스피킹 준비와 자연스러운 영어 소통을 원하는 분들에게 특히 효과적입니다.

섀도잉 방법: 단계별 전체 가이드 읽기 →

쉐도잉 연습: "AI Existential Risk" Was Invented to Distract Us - 영상으로 영어 말하기 배우기

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