Shadowing Practice: AI Will End Philosophy, Physicist Claims - Learn English Speaking with 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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Vocabulario y notas de pronunciación para esta lección
Este vídeo tiene 85 frases y 1087 palabras para practicar shadowing. La parte hablada dura 6:58. El hablante habla a un ritmo natural de unas 156 palabras por minuto, cercano a una conversación cotidiana. Solo el 80 % de las palabras está entre las 3.000 más comunes del inglés, por lo que el vocabulario es exigente.
Vocabulario clave de este vídeo
15 palabras del vídeo que vale la pena aprender, con su pronunciación y significado:
| Palabra | Pronunciación | Significado |
|---|---|---|
| philosopher sustantivo | /fəˈlɑsəfɚ/ | filósofo, filósofa |
| induction sustantivo | /ɪnˈdʌkʃən/ | inducción |
| explanation sustantivo | /ˌɛkspləˈneɪʃən/ | explicación |
| physics sustantivo | /ˈfɪz.ɪks/ | física |
| argue verbo | /ˈɑɹ.ɡju/ | argüir, argumentar |
| theoretical adjetivo | /ˌθi.əˈɹɛt.ɪ.kəl/ | teórico |
| solve verbo | /sɒlv/ | resolver, solucionar |
| experiment sustantivo | /ɪkˈspɛɹ.ə.mənt/ | experimento |
| philosophical adjetivo | /ˌfɪl.əˈsɑ.fɪ.kl̩/ | filosófico, filosofal |
| obsolete adjetivo | /ˈɑbsəlit/ | obsoleto, desusado |
| coherent adjetivo | /koʊˈhɛɹ.ənt/ | coherente |
| topic sustantivo | /ˈtɑpɪk/ | tema, tópico |
| stable sustantivo | /ˈsteɪ.bəl/ | establo, cuadra |
| encourage verbo | /ɪnˈkʌɹ.ɪd͡ʒ/ | alentar, arengar |
| select verbo | /sɪˈlɛkt/ | seleccionar, cribar |
Phrasal verbs que vas a escuchar
| Palabra | Significado |
|---|---|
| come up verbo | salir a relucir |
| think through verbo | cavilar |
Gramática en este vídeo
Las estructuras que más usa el hablante, con las palabras exactas del vídeo:
| Estructura | En el vídeo |
|---|---|
| Oraciones de relativo who / which + oración — información extra sobre una persona o cosa | pages, which is · induction, which is · answer which is |
| Present perfect have/has + participio pasado — una acción pasada que sigue importando ahora | has written · have seen · I've said |
| Voz pasiva be + participio pasado — importa lo que ocurre, no quién lo hace | is titled · should be done · should be treated |
Pronunciación a tener en cuenta
El hablante usa 17 contracciones y formas reducidas, como doesn't, don't, can't. Dilas en su forma corta, tal como las oyes.
- Los sonidos de “th”: theoretical /ˌθi.əˈɹɛt.ɪ.kəl/, sympathy /ˈsɪm.pəθ.i/, worthwhile /ˌwɜː(ɹ)θˈwaɪl/, pathetically /pəˈθɛtɪkli/, thorny /ˈθɔɹni/
- Los sonidos de “sh” y “zh”: induction /ɪnˈdʌkʃən/, explanation /ˌɛkspləˈneɪʃən/, artificial /ˌɑː.tɪˈfɪʃ.əl/, collections /kəˈlɛkʃənz/, notion /ˈnoʊʃən/
- Palabras largas — cuida el acento: philosopher /fəˈlɑsəfɚ/, explanation /ˌɛkspləˈneɪʃən/, theoretical /ˌθi.əˈɹɛt.ɪ.kəl/, experiment /ɪkˈspɛɹ.ə.mənt/, philosophical /ˌfɪl.əˈsɑ.fɪ.kl̩/
Cómo practicar con este vídeo
- Escucha el vídeo entero una vez sin hablar y anota las palabras que no conoces.
- Empieza a velocidad 0,75×, haz shadowing frase por frase y vuelve a la velocidad normal cuando te resulte fácil.
- Grábate y compara con el original, prestando atención a palabras como philosopher, induction, explanation.
¿Qué es la Técnica de Shadowing?
Shadowing es una técnica de aprendizaje de idiomas respaldada por la ciencia, desarrollada originalmente para la formación de intérpretes profesionales y popularizada por el políglota Dr. Alexander Arguelles. El método es simple pero poderoso: escuchas audio en inglés nativo y lo repites en voz alta de inmediato, como una sombra que sigue al hablante con solo 1-2 segundos de retraso. A diferencia de la escucha pasiva o los ejercicios de gramática, el shadowing obliga a tu cerebro y músculos de la boca a procesar y reproducir simultáneamente patrones de habla reales. Las investigaciones muestran que mejora significativamente la precisión de la pronunciación, la entonación, el ritmo, el habla conectada, la comprensión auditiva y la fluidez al hablar, convirtiéndola en una de las metodologías más efectivas para la preparación del IELTS Speaking y la comunicación en inglés en el mundo real.