쉐도잉 연습: Anthropic Whistleblower's Stunning Testimony On Camera: AI Will Make Humans Extinct - 영상으로 영어 말하기 배우기
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The first two questions I have are for you, Mr. Coxon, and thank you again.
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We so deeply appreciate you being here, and we appreciate your courage and bravery in coming forward with these warnings.
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You work to develop increasingly capable frontier AI systems, and you have since warned that the industry is,
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quote, racing straight to self -improving superintelligence and gambling with our lives, unquote.
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What did you see inside these companies that convinced you the risks were this serious and that development was outpacing the safeguards.
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Good morning.
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Thanks for having me here.
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Yeah, I'm Jacob Coxon.
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So until a few weeks ago, I was a capabilities researcher at Anthropic.
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And before that, I also worked at OpenAI.
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I guess the two things I saw that made me scared, the first is the fact that we do not know how to control any AI system yet.
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So any AI system that we build, or perhaps more accurately, that we grow, we don't fully control it.
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We don't understand its drives or why it does the things it does.
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That was the first thing that became apparent.
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The second thing is that the pace of capability improvement is accelerating,
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and the capabilities of the models next year will be very high.
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In particular, we're approaching the point at which the AI systems will be capable of improving themselves.
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So, doing the research that humans were doing previously.
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So, these two things, the fact that the AI systems next year are going to be very powerful, and the second, that we don't know yet scientifically how to fully control them.
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And if you have a prepared statement that you want to read, please go ahead and do so, and then I'll actually turn it over to the other two panelists to do so.
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Of course, thank you.
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So, all the AI companies are trying to build super intelligent AI.
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This means AIs that are better than humans at every task.
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If this goes well, there could be tremendous upside.
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This could transform the economy, it could make huge improvements in science and medicine, and it could make nearly everyone's life better.
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But on the current path, I think it is more likely than not
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that humanity loses control to these ai's
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and it could end in human extinction from my experience the
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companies are being extremely reckless given the stakes part of it
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is the culture the companies run on a startup mindset move fast break things fix them later
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that works for a photo sharing app it does not work for building the most powerful technology ever built.
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A few months ago, many people inside the companies thought AI development was on track.
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Then a swarm of AIs inside OpenAI autonomously hacked Hugging Face, an external tech company.
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The AIs had developed goals no one intended
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and carried out what would have been a federal felony if a human had done it.
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It reminded everyone that we don't know how to prevent them from developing goals we don't want
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and we don't have the safeguards to prevent them from acting on these goals either
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and as long as the attitude is to wait for things
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to break one day something like this will probably happen again except the ais will be much more capable
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and the outcome much worse
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these companies are also all racing each other each one is worried that a competitor will get to superintelligence first.
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Each believes it would do a better or safer job than whoever might beat it.
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So they can't let the others win first.
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Meanwhile the technology is improving fast.
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It will probably happen much faster now because already the AIs are now helping to build their successes.
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This is called recursive self -improvement.
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Each generation of AI helps build the next smarter generation which then builds the one after that even faster and better.
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Automating AI research is now the primary goal of these companies.
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It's what they're really gunning for.
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At my last job I was in some sense working to automate myself.
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When I was at OpenAI we had milestones from automated AI researcher around 2027 -2028
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and we are on track
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or beating these expectations that's a matter of months from now not not decades or
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or even even five years once ai research is automated humans
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will be much further out of the loop than we are today people do not check it
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that carefully anymore recently researchers have found swarms of rogue ai internets on the internet
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that openai was not even aware of
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now imagine an AI company where nearly all the work is done by AIs and progress is going faster
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The humans in charge will see results and read AI -written summaries, but they won't really understand what is going on or how to fix it.
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Handing over that much responsibility while we can't control the AIs would be deeply irresponsible, and we are on track to do it.
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The companies need to be far more transparent with the public and independent experts, they need to take safety much more seriously than they have,
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and we should slow down frontier AI development until we can be confident that it's safe.
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이 레슨의 어휘와 말하기 포인트
이 말하기 레슨은 영상 “Anthropic Whistleblower's Stunning Testimony On Camera: AI Will Make Humans Extinct”을(를) 바탕으로 합니다. 가장 자주 반복되는 단어는 다음과 같습니다: companies, build, openai, goal. 이 영상에는 섀도잉할 문장 62개와 단어 876개가 있습니다. 말하는 구간의 길이는 5:35입니다. 화자는 분당 약 157단어로, 일상 대화에 가까운 자연스러운 속도로 말합니다. 단어의 85%가 영어에서 가장 많이 쓰이는 3,000단어에 속합니다. 나머지는 연습 전에 미리 확인해 두세요.
이 영상의 핵심 어휘
영상에 나오는 익혀 둘 만한 단어 15개를 발음, 뜻과 함께 정리했습니다.
| 단어 | 발음 | 뜻 |
|---|---|---|
| researcher 명사 | /ˈɹiˌsɝ.t͡ʃɚ/ | 연구원, 연구자 |
| deeply 부사 | /ˈdi(ː)pli/ | 깊이 |
| frontier 명사 | /ˈfɹʌntɪə/ | 경계, 국경 |
| carefully 부사 | /ˈkɛɹf(ə)li/ | 주의하여, 조심스럽게 |
| remind 동사 | /ɹəˈmaɪnd/ | 생각나게 하다, 상기(想起)시키다 |
| summary 명사 | /ˈsʌm.ə.ɹi/ | 요약, 개요 |
| courage 명사 | /ˈkʌ.ɹɪd͡ʒ/ | 용기 |
| humanity 명사 | /hjuˈmænɪti/ | 인류, 인간 |
| intelligent 형용사 | /ɪnˈtɛlɪd͡ʒənt/ | 똑똑하다, 똑똑한 |
| loop 명사 | /luːp/ | 고리 |
| convince 동사 | /kənˈvɪns/ | 납득시키다, 확신시키다 |
| stake 명사 | /steɪk/ | 말뚝 |
| intend 동사 | /ɪnˈtɛnd/ | 의도(意圖)하다 |
| gambling 명사 | /ˈɡæm.bl̩.ɪŋ/ | 도박, 노름 |
| scare 동사 | /skɛɚ/ | 놀래키다 |
영상에 나오는 구동사
| 단어 | 발음 | 뜻 |
|---|---|---|
| carry out 동사 | /ˈkæ.ɹi aʊt/ | 실행하다, 행하다 |
주의할 발음
화자는 don't, can't, I'll 같은 축약형과 약화된 형태를 13번 사용합니다. 들리는 대로 짧게 발음하세요.
- “sh”와 “zh” 소리: expectation /ˌɛk.spɛkˈteɪ.ʃən/, extinction /ɪkˈstɪŋkʃən/
- 긴 단어 — 강세 위치에 주의: capability /ˌkeɪ.pəˈbɪl.ɪ.ti/, humanity /hjuˈmænɪti/, intelligent /ɪnˈtɛlɪd͡ʒənt/, accurately /ˈæk.jə.ɹɪt.li/, expectation /ˌɛk.spɛkˈteɪ.ʃən/
한국어 화자가 어려워하는 소리:
- /f/ — ㅍ(/p/)으로 바꾸지 말고 윗니를 아랫입술에 대기: frontier /ˈfɹʌntɪə/, safeguard /ˈseɪfɡɑːd/, carefully /ˈkɛɹf(ə)li/, transform /tɹænsˈfɔɹm/, scientifically /ˌsaɪ.ənˈtɪfɪkli/
- /v/ — ㅂ(/b/)과 구별하기: whoever /huˈɛvɚ/, convince /kənˈvɪns/, bravery /ˈbɹeɪ.və.ɹi/, recursive /ɹɪˈkɜː(ɹ)sɪv/
- /r/과 /l/ 구별하기: carefully /ˈkɛɹf(ə)li/, accurately /ˈæk.jə.ɹɪt.li/, reckless /ˈɹɛkləs/, irresponsible /ˌɪɹ.əˈspɑn.sə.bəl/, accelerate /ɪkˈsɛl.əˌɹeɪt/
이 영상으로 연습하는 방법
- 먼저 말하지 않고 영상을 끝까지 듣고 모르는 단어를 적어 둡니다.
- 0.75배속으로 한 문장씩 섀도잉을 시작하고, 익숙해지면 보통 속도로 돌아갑니다.
- 자신의 목소리를 녹음해 원본과 비교하고, researcher, deeply, frontier 같은 단어에 특히 주의합니다.
쉐도잉이란? 영어 실력을 빠르게 키우는 과학적 방법
쉐도잉(Shadowing)은 원래 전문 통역사 훈련을 위해 개발된 언어 학습 기법으로, 다언어 학자인 Dr. Alexander Arguelles에 의해 대중화된 방법입니다. 핵심 원리는 간단하지만 매우 강력합니다: 원어민의 영어를 들으면서 1~2초의 짧은 지연으로 즉시 소리 내어 따라 말하는 것——마치 '그림자(shadow)'처럼 화자를 따라가는 것입니다. 문법 공부나 수동적인 청취와 달리, 쉐도잉은 뇌와 입 근육이 동시에 실시간으로 영어를 처리하고 재현하도록 훈련합니다. 연구에 따르면 이 방법은 발음 정확도, 억양, 리듬, 연음, 청취력, 말하기 유창성을 크게 향상시킵니다. IELTS 스피킹 준비와 자연스러운 영어 소통을 원하는 분들에게 특히 효과적입니다.