跟讀練習: "AI Existential Risk" Was Invented to Distract Us - 通過影片學習英語口語

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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?

146

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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本課的詞彙與口語要點

這節 B2 級別的口語課以影片“"AI Existential Risk" Was Invented to Distract Us”為素材。這段影片共有 162 個句子、2554 個單詞可供跟讀。講話部分時長為 13:21。說話人語速較快，每分鐘約 191 個詞，會出現較多連讀和弱讀。 84% 的單詞屬於英語最常用的 3,000 詞，其餘的詞建議在練習前先學一下。全部 162 個句子中有 31 個是問句，適合練習疑問語調和簡短回答。

影片中的重點詞彙

影片中最難的 15 個單詞，附發音和釋義：

單詞	發音	釋義
existential 形容詞	/ˌɛɡzɪˈstɛnʃl̩/	存在性, 有關存在的 /有關存在的
extinction 名詞	/ɪkˈstɪŋkʃən/	滅絕 /滅絕
depend 動詞	/dɪˈpɛnd/	信任, 信賴 /信賴
volition 名詞	/voʊˈlɪʃ(ə)n/	意志, 決斷 /決斷
hypothetical 形容詞	/ˌhaɪpəˈθɛtɪkəl/	假設的 /假設的, 假定的
tweet 名詞	/ˈtwiːt/	鳴叫 /鳴叫
chatbot 名詞	/ˈtʃætbɑt/	聊天機器人 /聊天機器人
swarm 名詞	/swɔɹm/	群
skeptical 形容詞	/ˈskɛptɪkəl/	持有懷疑的
millennium 名詞	/mɪˈlɛnɪəm/	千年, 千紀 /千紀
insecure 形容詞	/ɪnsəˈkjʊɹ/	不安全的
rumor 名詞	/ˈɹumɚ/	傳聞 /傳聞, 傳言 /傳言
insider 名詞	/ɪnˈsaɪdɚ/	內部的人 /內部的人
wipe 動詞	/waɪp/	擦, 擦拭
cigarette 名詞	/ˈsɪɡəɹɛt/	香煙 /香菸, 紙煙 /紙菸

影片中出現的短語動詞

單詞	發音	釋義
make up 動詞	/ˌmeɪk ˈʌp/	組成 /組成
come up with 動詞		想出, 提出
end up 動詞		到達
figure out 動詞		弄清楚
go up 動詞		上昇 /上升, 上去
slow down 動詞		減速 /減速, 放慢

值得反覆跟讀的句子

影片中簡短而完整的句子，可以直接用在日常對話裡：

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

影片中的語法

說話人最常用的結構，並附上影片中的原話：

結構	影片中的用法
現在完成進行時 have/has been + -ing — 以前開始、現在仍在繼續的動作	has been saying · it's been causing · have been trying
定語從句 who / which + 從句 — 補充說明人或事物	people who come · everyone who worked · guy who did
被動語態 be + 過去分詞 — 強調發生了什麼，而不是誰做的	being controlled · is specifically supplied · was trained
現在完成時 have/has + 過去分詞 — 過去發生但與現在仍有關聯的事	has led · have been · we've been

需要注意的發音

說話人用了 41 次縮略和弱讀形式，例如 they're, don't, didn't。請按聽到的簡短形式來說。

“th” 音: hypothetical /ˌhaɪpəˈθɛtɪkəl/, mathematics /mæθ(.ə)ˈmæt.ɪks/, mathematician /ˌmæθ.(ə.)məˈtɪʃ.ən/, thinker /ˈθɪŋ.kɚ/, truthful /ˈtɹuːθ.f(ə)l/
“sh” 和 “zh” 音: existential /ˌɛɡzɪˈstɛnʃl̩/, extinction /ɪkˈstɪŋkʃən/, volition /voʊˈlɪʃ(ə)n/, computation /ˌkɑmpjʊˈteɪʃn̩/, mathematician /ˌmæθ.(ə.)məˈtɪʃ.ən/
長單詞——注意重音位置: bioweapon /ˈbaɪ.oʊˌwɛ.pən/, hypothetical /ˌhaɪpəˈθɛtɪkəl/, mathematics /mæθ(.ə)ˈmæt.ɪks/, demonstrably /diˈmɑnstrəbli/, extrapolate /ɛkˈstɹæp.əˌleɪt/

中文母語者容易讀錯的音：

/v/ — 不要讀成 /w/，上齒輕觸下唇: volition /voʊˈlɪʃ(ə)n/, absolve /æbˈzɑlv/, unsolved /ʌnˈsɑlvd/, havoc /ˈhævək/, civilians /sɪˈvɪl.jənz/
詞尾子音 — 要讀清楚，後面不要加母音: depend /dɪˈpɛnd/, tweet /ˈtwiːt/, chatbot /ˈtʃætbɑt/, wipe /waɪp/, cigarette /ˈsɪɡəɹɛt/
/r/ 和 /l/ 的區別: answerable /ˈæn.səɹ.ə.bl/, demonstrably /diˈmɑnstrəbli/, extrapolate /ɛkˈstɹæp.əˌleɪt/, forestall /fɔː(ɹ)ˈstɔːl/, truthful /ˈtɹuːθ.f(ə)l/

如何用這段影片練習

先完整聽一遍影片，不要開口，記下不認識的單詞。
先用 0.75 倍速逐句跟讀，熟練之後再回到正常速度。
錄下自己的聲音並與原聲對比，特別注意 existential, extinction, depend 這類單詞。

什麼是跟讀法？

跟讀法 (Shadowing) 是一種有科學依據的語言學習技巧，最初開發用於專業口譯員的培訓，並由多語言者Alexander Arguelles博士普及。這個方法簡單而強大：您在聽英語母語原聲的同時立即大聲重複——就像是一個延遲1-2秒緊跟說話者的影子。與被動聽力或語法練習不同，跟讀法強迫您的大腦和口腔肌肉同時處理並模模擬實的講話模式。研究表明它能顯著提高發音準確性，語調，節奏，連讀，聽力理解和口語流利度——使其成為雅思口語備考和真實英語交流最有效的方法之一。

影子跟讀法: 閱讀完整分步指南 →

跟讀練習: "AI Existential Risk" Was Invented to Distract Us - 通過影片學習英語口語

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