跟讀練習: AI Will End Philosophy, Physicist Claims - 通過影片學習英語口語

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A physicist has written a book explaining how artificial intelligence will make much of philosophy obsolete soon.

A philosopher thinks otherwise, and I think, well, they're both wrong.

Let me explain.

The new book comes from Louis Fervort, who started out with a PhD in physics, but then did a second PhD in philosophy.

So this isn't your stereotypical ignorant physicists with a YouTube channel.

You have me for that.

The book is titled Problem Solving in Philosophy, How to Do Philosophy in the Age of Ultra Intelligent AI.

To make a long story short, the author argues that philosophy should be done like in natural science in general, and like theoretical physics in particular.

As he writes in the book, quote, philosophy is now mature enough to come to reasonably solid answers to key problems,

And there's one overarching method to do so, in essence, the same method as the natural science is used to obtain answers,

in particular theoretical physics.

He argues that philosophers should quantify how good an explanation is by using

that explanation which gives the largest number of coherent answers to the well -posed problems.

He calls this the maximally coherent theory.

The best theory is the one that explains the most cases, makes sense of the most counterexamples and contradicts the least other accepted knowledge.

And AI can do it, so his argument, because all it really comes down to is counting the questions answered and contradictions.

He's even done an experiment in which he used AI to allegedly solve a thorny problem of philosophy.

That's how to define causality.

The experiment works like this.

Ask Chad GPT, at the time this was GPT -4, which notion of causality is the best.

Chad GPT said, counterfactual causality, which Fairbord thinks is correct because it's the one he also likes best.

Maybe doing philosophy like theoretical physics is not the flex he thinks it is.

Other philosophy topics that Fairbord thinks AI or cetera is free will, which clearly doesn't exist, and induction,

which he thinks is a pseudo -problem.

Though I have to add that he also says that he doesn't think AI will solve all philosophy problems.

In particular, he says big questions like the meaning of life or the existence of God are still up for grabs,

presumably until chat GPT 7 .8 Max Pro Ultra agrees with him.

The author published a paper with his main argument before the book, so we already have a comment from a philosopher titled,

can we automate philosophy through AI?

And we want to.

The philosopher basically says that if you think philosophy is about generating theories and arguing for and against them,

then yes, an AI can in principle do it.

If you, on the other hand, think philosophy is about thinking through these problems yourself, then an AI can't do it for you.

The remarkable thing about this argument is that he managed to blow it up to 15 pages, which is basically my problem with all philosophy literature.

Loads of words to say the pathetically obvious.

That said, I don't have much sympathy for the physicist's argument in this case either,

because the question of how to quantify the best explanation for a philosophical theory is itself a philosophical problem.

And the entire idea that you can science -ify philosophy is nonsense,

because philosophy is exactly what we use to discuss the questions that science cannot answer, or not yet.

There are, of course, questions that eventually move from philosophy to science.

Consciousness is just doing this, and free will is likely going to come next.

The problem with the author's argument is nicely illustrated in his take on the problem of induction.

That's the question of why induction works.

Why do the laws of nature continue to work?

Why does the sun rise every morning?

Why do atoms remain stable?

Why does Sabina keep making stupid jokes?

You might say, well, it's because we have seen in the past that that's the case.

Yes, but that'd be proving induction by induction, which is a circular argument.

Verwort basically says it's a meaningless question

because induction should be treated as an axiom and as such it doesn't require a justification.

But induction is an axiom in science.

We need it for science to work.

The question is why does it work?

That's a question science can't answer which is exactly why it's a question for philosophers.

If you say a non -scientific question isn't a question then yeah I guess you can close the philosophy departments

but even Claude could tell you that this is a pseudo -argument.

That said, I think both of these gentlemen missed the obvious point, which is that humans are by.. default lazy.

Most philosophy papers are already collections of useless words

that no one reads and of course increasingly more philosophers will let AI do this job.

Indeed, I'm sure this is already happening and I hope

that this will ultimately encourage philosophers to improve the quality of their discourse.

I give the book a 6 out of 10 on the bullshit meter.

Why is it so low after all I've said?

It's because I think that the method that the author suggests to quantify how good different explanations are is worthwhile.

I just don't think it's going to make philosophy redundant.

And if AI really does make philosophy obsolete, philosophers will spend the next 50 years debating whether that actually happened.

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Thanks for watching.

See you tomorrow.

You

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本課的詞彙與口語要點

這段影片共有 85 個句子、1087 個單詞可供跟讀。講話部分時長為 6:58。說話人語速自然，每分鐘約 156 個詞，接近日常對話。只有 80% 的單詞屬於英語最常用的 3,000 詞，詞彙難度較高。

影片中的重點詞彙

影片中 15 個值得學習的單詞，附發音和釋義：

單詞	發音	釋義
philosopher 名詞	/fəˈlɑsəfɚ/	哲學家 /哲學家
explanation 名詞	/ˌɛkspləˈneɪʃən/	解釋 /解釋, 說明 /說明
physics 名詞	/ˈfɪz.ɪks/	物理學 /物理學
argue 動詞	/ˈɑɹ.ɡju/	辯論 /辯論, 爭辯 /爭辯
theoretical 形容詞	/ˌθi.əˈɹɛt.ɪ.kəl/	理論 /理論
solve 動詞	/sɒlv/	解決 /解決
experiment 名詞	/ɪkˈspɛɹ.ə.mənt/	實驗 /實驗
obsolete 形容詞	/ˈɑbsəlit/	淘汰, 過時 /過時
coherent 形容詞	/koʊˈhɛɹ.ənt/	凝聚的
topic 名詞	/ˈtɑpɪk/	主題 /主題, 話題 /話題
stable 名詞	/ˈsteɪ.bəl/	馬廄, 馬棚 /馬棚
encourage 動詞	/ɪnˈkʌɹ.ɪd͡ʒ/	鼓勵 /鼓勵, 激勵 /激勵
select 動詞	/sɪˈlɛkt/	選 /選, 挑選 /挑選
guarantee 名詞	/ˌɡæɹ.ənˈtiː/	保證 /保證
obtain 動詞	/əbˈteɪn/	獲得 /獲得

影片中出現的短語動詞

單詞	釋義
come up 動詞	上來 /上來

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
定語從句 who / which + 從句 — 補充說明人或事物	pages, which is · induction, which is · answer which is
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 written · have seen · I've said
被動語態 be + 過去分詞 — 強調發生了什麼，而不是誰做的	is titled · should be done · should be treated

需要注意的發音

說話人用了 17 次縮略和弱讀形式，例如 doesn't, don't, can't。請按聽到的簡短形式來說。

“th” 音: theoretical /ˌθi.əˈɹɛt.ɪ.kəl/, sympathy /ˈsɪm.pəθ.i/, worthwhile /ˌwɜː(ɹ)θˈwaɪl/, pathetically /pəˈθɛtɪkli/, thorny /ˈθɔɹni/
“sh” 和 “zh” 音: induction /ɪnˈdʌkʃən/, explanation /ˌɛkspləˈneɪʃən/, artificial /ˌɑː.tɪˈfɪʃ.əl/, collections /kəˈlɛkʃənz/, notion /ˈnoʊʃən/
長單詞——注意重音位置: philosopher /fəˈlɑsəfɚ/, explanation /ˌɛkspləˈneɪʃən/, theoretical /ˌθi.əˈɹɛt.ɪ.kəl/, experiment /ɪkˈspɛɹ.ə.mənt/, philosophical /ˌfɪl.əˈsɑ.fɪ.kl̩/

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 philosopher, explanation, physics 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。

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跟讀練習: AI Will End Philosophy, Physicist Claims - 通過影片學習英語口語

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