Shadowing-Übung: AI Will End Philosophy, Physicist Claims - Englisch Sprechen Lernen mit Video
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A physicist has written a book explaining how artificial intelligence will make much of philosophy obsolete soon.
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A philosopher thinks otherwise, and I think, well, they're both wrong.
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Let me explain.
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The new book comes from Louis Fervort, who started out with a PhD in physics, but then did a second PhD in philosophy.
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So this isn't your stereotypical ignorant physicists with a YouTube channel.
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You have me for that.
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The book is titled Problem Solving in Philosophy, How to Do Philosophy in the Age of Ultra Intelligent AI.
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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.
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As he writes in the book, quote, philosophy is now mature enough to come to reasonably solid answers to key problems,
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And there's one overarching method to do so, in essence, the same method as the natural science is used to obtain answers,
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in particular theoretical physics.
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He argues that philosophers should quantify how good an explanation is by using
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that explanation which gives the largest number of coherent answers to the well -posed problems.
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He calls this the maximally coherent theory.
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The best theory is the one that explains the most cases, makes sense of the most counterexamples and contradicts the least other accepted knowledge.
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And AI can do it, so his argument, because all it really comes down to is counting the questions answered and contradictions.
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He's even done an experiment in which he used AI to allegedly solve a thorny problem of philosophy.
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That's how to define causality.
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The experiment works like this.
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Ask Chad GPT, at the time this was GPT -4, which notion of causality is the best.
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Chad GPT said, counterfactual causality, which Fairbord thinks is correct because it's the one he also likes best.
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Maybe doing philosophy like theoretical physics is not the flex he thinks it is.
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Other philosophy topics that Fairbord thinks AI or cetera is free will, which clearly doesn't exist, and induction,
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which he thinks is a pseudo -problem.
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Though I have to add that he also says that he doesn't think AI will solve all philosophy problems.
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In particular, he says big questions like the meaning of life or the existence of God are still up for grabs,
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presumably until chat GPT 7 .8 Max Pro Ultra agrees with him.
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The author published a paper with his main argument before the book, so we already have a comment from a philosopher titled,
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can we automate philosophy through AI?
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And we want to.
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The philosopher basically says that if you think philosophy is about generating theories and arguing for and against them,
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then yes, an AI can in principle do it.
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If you, on the other hand, think philosophy is about thinking through these problems yourself, then an AI can't do it for you.
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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.
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Loads of words to say the pathetically obvious.
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That said, I don't have much sympathy for the physicist's argument in this case either,
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because the question of how to quantify the best explanation for a philosophical theory is itself a philosophical problem.
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And the entire idea that you can science -ify philosophy is nonsense,
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because philosophy is exactly what we use to discuss the questions that science cannot answer, or not yet.
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There are, of course, questions that eventually move from philosophy to science.
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Consciousness is just doing this, and free will is likely going to come next.
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The problem with the author's argument is nicely illustrated in his take on the problem of induction.
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That's the question of why induction works.
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Why do the laws of nature continue to work?
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Why does the sun rise every morning?
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Why do atoms remain stable?
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Why does Sabina keep making stupid jokes?
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You might say, well, it's because we have seen in the past that that's the case.
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Yes, but that'd be proving induction by induction, which is a circular argument.
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Verwort basically says it's a meaningless question
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because induction should be treated as an axiom and as such it doesn't require a justification.
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But induction is an axiom in science.
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We need it for science to work.
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The question is why does it work?
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That's a question science can't answer which is exactly why it's a question for philosophers.
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If you say a non -scientific question isn't a question then yeah I guess you can close the philosophy departments
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but even Claude could tell you that this is a pseudo -argument.
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That said, I think both of these gentlemen missed the obvious point, which is that humans are by.. default lazy.
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Most philosophy papers are already collections of useless words
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that no one reads and of course increasingly more philosophers will let AI do this job.
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Indeed, I'm sure this is already happening and I hope
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that this will ultimately encourage philosophers to improve the quality of their discourse.
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I give the book a 6 out of 10 on the bullshit meter.
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Why is it so low after all I've said?
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It's because I think that the method that the author suggests to quantify how good different explanations are is worthwhile.
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I just don't think it's going to make philosophy redundant.
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And if AI really does make philosophy obsolete, philosophers will spend the next 50 years debating whether that actually happened.
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Wortschatz und Sprechhinweise zu dieser Lektion
Dieses Video enthält 85 Sätze und 1087 Wörter zum Nachsprechen. Der gesprochene Teil dauert 6:58. Der Sprecher spricht in natürlichem Tempo, etwa 156 Wörter pro Minute, ähnlich wie im Alltagsgespräch. Nur 80 % der Wörter gehören zu den 3.000 häufigsten im Englischen, der Wortschatz ist also anspruchsvoll.
Wichtiger Wortschatz in diesem Video
15 lernenswerte Wörter aus dem Video, mit Aussprache und Bedeutung:
| Wort | Aussprache | Bedeutung |
|---|---|---|
| philosopher Substantiv | /fəˈlɑsəfɚ/ | Philosoph, Philosophin |
| induction Substantiv | /ɪnˈdʌkʃən/ | Einführung |
| explanation Substantiv | /ˌɛkspləˈneɪʃən/ | Erläuterung, Erklärung |
| physics Substantiv | /ˈfɪz.ɪks/ | Physik |
| argue Verb | /ˈɑɹ.ɡju/ | diskutieren, erörtern |
| theoretical Adjektiv | /ˌθi.əˈɹɛt.ɪ.kəl/ | theoretisch |
| solve Verb | /sɒlv/ | lösen |
| experiment Substantiv | /ɪkˈspɛɹ.ə.mənt/ | Experiment, Versuch |
| philosophical Adjektiv | /ˌfɪl.əˈsɑ.fɪ.kl̩/ | philosophisch |
| obsolete Adjektiv | /ˈɑbsəlit/ | veraltet, obsolet |
| coherent Adjektiv | /koʊˈhɛɹ.ənt/ | kohärent, zusammenhängend |
| topic Substantiv | /ˈtɑpɪk/ | Thema |
| stable Substantiv | /ˈsteɪ.bəl/ | Stall, Pferdestall |
| encourage Verb | /ɪnˈkʌɹ.ɪd͡ʒ/ | ermutigen, ermuntern |
| select Verb | /sɪˈlɛkt/ | auswählen |
Phrasal Verbs, die du hören wirst
| Wort | Bedeutung |
|---|---|
| come up Verb | erscheinen |
| think through Verb | durchdenken |
Grammatik in diesem Video
Die Strukturen, die der Sprecher am häufigsten verwendet, mit den genauen Worten aus dem Video:
| Struktur | Im Video |
|---|---|
| Relativsätze who / which + Satz – eine Zusatzinformation über eine Person oder Sache | pages, which is · induction, which is · answer which is |
| Present Perfect have/has + Partizip Perfekt – eine vergangene Handlung, die jetzt noch wichtig ist | has written · have seen · I've said |
| Passiv be + Partizip Perfekt – wichtig ist, was geschieht, nicht wer es tut | is titled · should be done · should be treated |
Aussprache, auf die du achten solltest
Der Sprecher verwendet 17 Kurzformen und abgeschwächte Formen, zum Beispiel doesn't, don't, can't. Sprich sie in der kurzen Form, so wie du sie hörst.
- Die „th“-Laute: theoretical /ˌθi.əˈɹɛt.ɪ.kəl/, sympathy /ˈsɪm.pəθ.i/, worthwhile /ˌwɜː(ɹ)θˈwaɪl/, pathetically /pəˈθɛtɪkli/, thorny /ˈθɔɹni/
- Die Laute „sh“ und „zh“: induction /ɪnˈdʌkʃən/, explanation /ˌɛkspləˈneɪʃən/, artificial /ˌɑː.tɪˈfɪʃ.əl/, collections /kəˈlɛkʃənz/, notion /ˈnoʊʃən/
- Lange Wörter – auf die Betonung achten: philosopher /fəˈlɑsəfɚ/, explanation /ˌɛkspləˈneɪʃən/, theoretical /ˌθi.əˈɹɛt.ɪ.kəl/, experiment /ɪkˈspɛɹ.ə.mənt/, philosophical /ˌfɪl.əˈsɑ.fɪ.kl̩/
So übst du mit diesem Video
- Höre dir das ganze Video einmal an, ohne zu sprechen, und notiere die Wörter, die du nicht kennst.
- Beginne mit 0,75-facher Geschwindigkeit, sprich Satz für Satz nach und wechsle zur normalen Geschwindigkeit, sobald es leichtfällt.
- Nimm dich auf und vergleiche mit dem Original; achte dabei auf Wörter wie philosopher, induction, explanation.
Was ist die Shadowing-Technik?
Shadowing ist eine wissenschaftlich fundierte Sprachlerntechnik, die ursprünglich für die professionelle Dolmetscherausbildung entwickelt und durch den Polyglotten Dr. Alexander Arguelles populär gemacht wurde. Die Methode ist einfach aber wirkungsvoll: Du hörst englisches Audio von Muttersprachlern und wiederholst es sofort laut — wie ein Schatten, der dem Sprecher mit nur 1–2 Sekunden Verzögerung folgt. Anders als passives Hören oder Grammatikübungen zwingt Shadowing dein Gehirn und deine Mundmuskulatur, gleichzeitig echte Sprachmuster zu verarbeiten und zu reproduzieren. Studien zeigen, dass es Aussprachegenauigkeit, Intonation, Rhythmus, verbundene Sprache, Hörverständnis und Sprechflüssigkeit signifikant verbessert — was es zu einer der effektivsten Methoden für die IELTS Speaking-Vorbereitung und reale englische Kommunikation macht.