Shadowing Practice: Claude Just Revealed AI's Biggest Problem - Learn English Speaking with Video
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For thousands of years, humans have built tools to make hard things easier.
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A hammer does not make you worse at building.
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But is AI different?
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Because AI helps your brain, not your hands.
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And that raises an uncomfortable question.
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What happens to the skills we outsource?
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Is AI brain rot real?
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What should we do?
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Well, I see a big difference in the media headlines and actual real-world studies.
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So, let's see an actual experiment with a group of 52 junior software engineers split into two groups,
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one that used AI for coding and one that didn't.
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I have two questions here and the results on both kind of surprised me.
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1. Did AI make them faster?
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Well, the AI group finished their tasks a good two minutes, or about 8% faster.
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So, they had time to watch a 2 minute papers episode.
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Which is never 2 minutes.
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But then, wait a second, the result is not statistically significant.
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I'll downgrade this a bit, so did AI make people code faster?
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Maybe.
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Now, second question, did the AI make them dumber?
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Now, hold on to your papers, fellow scholars, because the answer is, kinda yes.
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After having them take a quiz, we get 50% for the AI people, and 67% for the no AI people.
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Whew, that is almost a too great difference.
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Huge difference!
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And this is statistically significant.
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So this one would be much harder to dismiss as noise.
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I gotta say, this is a fairly large effect for such a smaller study.
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So where is the largest gap?
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The AI group really underperforms, when exactly?
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Well, in debugging.
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Yes, you get an AI to write a piece of code, and at some point, there will be a problem.
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And if you rely on the AI too much, sooner or later, you will lose the capability to fix something that goes wrong.
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I would be careful with that.
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And I find this study informative because it tells you how much worse it is and in what areas.
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So, what should you do going forward?
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Well, in my opinion, three things.
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Dear Fellow Scholars, this is Two Minute Papers with Dr. Károly Zsolnai-Fehér.
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1. If you use AI, use it mainly for automating and speeding up things you already understand.
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It is excellent for that.
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2. For things you don't know yet.
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Ask questions.
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Keep your mind sharp.
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That is the way of the scholar.
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3. When something breaks, don't just ask the AI to fix it.
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No, first try it yourself.
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Then, have it explain to you what you missed.
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You will learn so much more.
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We are scholars here, so let's be measured.
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This is not an ultimate study.
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No, this is not the final word on this question.
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This is 52 mostly junior developers, one Python library, one short task, and one quiz.
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Oh, and it has a chat-style assistant, not a full agentic coding system.
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Which would probably make this kind of difference even larger.
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So, plenty of limitations apply, but as a pointer, I feel it is quite valuable.
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TLDR, if you use AI as a tutor, it will sharpen your mind.
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I use Lambda to reproduce AI research papers, often in minutes.
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It's also great to train your own models or fine-tune an existing one.
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Run inference or text to image or video, easy peasy.
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Running a DeepSeek chatbot or agent, super fast, super reliable.
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Lambda gives you powerful Nvidia GPUs to run your own experiments.
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I test ideas from the papers I cover, and moments later, results!
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Love it!
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Seriously, try it out now at lambda.ai.papers.
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Vocabulary and speaking notes for this lesson
This B2 speaking lesson is built on the video “Claude Just Revealed AI's Biggest Problem”. The speaker keeps coming back to these words: papers, scholar, difference, lambda, faster. This video has 63 sentences and 602 words to shadow. The speech runs for 3:54. The speaker talks at a natural 154 words per minute, close to everyday conversation. 82% of the words are among the 3,000 most common in English; the rest is worth studying before you start. 10 of its 63 sentences are questions, so it is good practice for question intonation and short answers.
Key vocabulary in this video
The 15 most advanced words in the video, with pronunciation and meaning:
| Word | Pronunciation | Meaning |
|---|---|---|
| scholar noun | /ˈskɑlɚ/ | A student; one who studies at school or college, typically having a scholarship. |
| lambda noun | /ˈlæm.də/ | The eleventh letter of the Classical and Modern Greek alphabet, the twelfth of the Old Greek alphabet. |
| statistically adverb | /stəˈtɪs.tɪ.kə.li/ | In a statistical way. |
| quiz noun | /kwɪz/ | A competition in the answering of questions. |
| agentic adjective | /eɪˈd͡ʒɛn.tɪk/ | That behaves like an agent: able to express or expressing agency or control on one's own behalf or on the behalf of another. |
| automate verb | /ˈɔ.təˌmeɪt/ | To replace or enhance human labor with machines. |
| chatbot noun | /ˈtʃætbɑt/ | A computer program that holds conversations through a chat room. |
| downgrade verb | /ˌdaʊnˈɡɹeɪd/ | To place lower in position. |
| inference noun | /ˈɪn.fə.ɹəns/ | The act or process of inferring by deduction or induction. |
| outsource verb | /ˈaʊtˌsɔːs/ | To transfer the management or day-to-day execution of a business function to a third-party service provider. |
| sharpen verb | /ˈʃɑɹpən/ | To make sharp. |
| underperform verb | To underachieve; to fail to reach standards or expectations, especially with respect to a financial investment. | |
| informative adjective | /ɪnˈfɔːmətɪv/ | Providing information; especially, providing useful or interesting information. |
| pointer noun | /ˈpɔɪn.təɹ/ | One who points. |
| reproduce verb | /ˌɹi.pɹəˈdus/ | To produce an image or copy of. |
Phrasal verbs you will hear
| Word | Pronunciation | Meaning |
|---|---|---|
| going forward adverb | In the immediate future and beyond. | |
| speed up verb | /spiːdˈʌp/ | To accelerate; to increase speed. |
Sentences worth repeating
Short, complete lines from the video that you can reuse in everyday conversation:
- What happens to the skills we outsource?
- What should we do?
- For things you don't know yet.
- We are scholars here, so let's be measured.
Pronunciation to watch
The speaker uses 6 contractions and reduced forms, such as don't, didn't, gotta. Say them the short way, as you hear them.
- The “sh” and “zh” sounds: sharpen /ˈʃɑɹpən/, limitation /lɪmɪˈteɪʃən/
- Long words — get the stress right: statistically /stəˈtɪs.tɪ.kə.li/, informative /ɪnˈfɔːmətɪv/, limitation /lɪmɪˈteɪʃən/, capability /ˌkeɪ.pəˈbɪl.ɪ.ti/, uncomfortable /ʌnˈkʌm.fɚ.tə.bl̩/
How to practise with this video
- Listen to the whole video once without speaking and note the words you do not know.
- Start at 0.75× speed, shadow it sentence by sentence, then go back to normal speed once it feels easy.
- Record yourself and compare with the original, paying attention to words like scholar, lambda, statistically.
What is the Shadowing Technique?
Shadowing is a science-backed language learning technique originally developed for professional interpreter training and popularized by polyglot Dr. Alexander Arguelles. The method is simple but powerful: you listen to native English audio and immediately repeat it out loud — like a shadow following the speaker with just a 1–2 second delay. Unlike passive listening or grammar drills, shadowing forces your brain and mouth muscles to simultaneously process and reproduce real speech patterns. Research shows it significantly improves pronunciation accuracy, intonation, rhythm, connected speech, listening comprehension, and speaking fluency — making it one of the most effective methods for IELTS Speaking preparation and real-world English communication.