쉐도잉 연습: When AIs act emotional - 영상으로 영어 말하기 배우기
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When you're chatting with an AI model, it can sometimes seem like it has feelings.
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It might say sorry when it makes a mistake, or express satisfaction with a job well done.
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Why does it do that?
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Is it just mimicking what it thinks a human might say?
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Or is something deeper going on?
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Turns out it's hard to understand what's happening inside a language model.
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At Anthropic, we do something like AI neuroscience to try to figure this out.
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We look inside the model's brain, the giant neural network that powers it, and by seeing which neurons light up in different situations and how they're connected,
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we can start to understand how models think.
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We used this approach to understand whether models had ways of representing emotions, or the concepts of emotions.
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Basically, could we find neurons in the model for the concept of happiness, or anger, or fear?
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We started with an experiment.
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We had the model read lots of short stories.
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In each story, the main character experiences a particular emotion.
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In one, a woman tells her old school teacher how much they meant to her.
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That's love.
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In another, a man sells his grandmother's engagement ring at a pawn shop and feels guilt.
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We looked for what parts of the model's neural network were lighting up as it was reading these stories.
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And we started to see patterns.
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Stories about loss and grief lit up similar neurons.
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Stories about joy and excitement overlapped too.
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dozens of distinct neural patterns that mapped to different human emotions.
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It turns out we also saw these same patterns activate in test conversations we had with our AI assistant Claude.
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When we had a user mention they'd taken a dose of medicine that Claude knows to be unsafe,
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the "afraid" pattern lit up and Claude's response sounded alarmed.
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When a user expressed sadness, the "loving" This led us to wonder,
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could these same neural patterns actually be influencing Claude's behavior?
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This became clear when we put Claude in a high -pressure situation.
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We gave Claude a programming task, with requirements that were actually impossible.
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But we didn't tell it that.
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Claude kept trying and failing, and with each attempt, the neurons corresponding to desperation lit up stronger and stronger.
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After failing enough times, Claude took a different approach.
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It found a shortcut that allowed it to pass the test, but didn't actually solve the problem.
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It cheated.
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Could it be that this cheating was actually driven, at least in part, by desperation?
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We came up with a way to check.
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We decided to artificially turn down the desperation neurons to see what would happen.
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And the model cheated less.
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And when we dialed up the activity of desperation neurons or dialed down the activity of calm neurons, the model cheated even more.
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This showed us that the activation of these patterns could actually drive Claude's behavior.
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This research does not show that the model is feeling emotions or having conscious experiences.
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These experiments don't try to answer that question.
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To understand what's happening here, it's important to know how AI assistants like Claude work on the inside.
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Under the hood, there's a language model that's been trained to predict tons of text, and its job is to write what comes next.
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And when you talk to the model, what it's doing is writing a story about a character, the AI assistant named Claude.
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as the characters they write.
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But the thing is, you, the user, are actually talking to Claude the character.
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And what our experiments suggest is that this Claude character has what we're calling functional emotions, regardless of whether they're anything like human feelings.
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So if the model represents Claude as being angry, or desperate, or loving, or calm, that's going to affect how Claude talks to you,
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how it writes code, and how it makes important decisions.
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to really understand AI models, we have to think carefully about the psychology of the characters they play.
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The same way you'd want a person in a high -stakes job to stay composed under pressure, to be resilient and to be fair,
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we may need to shape similar qualities in Claude and other AI characters.
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It's an unusual challenge, something like a mix of engineering, philosophy and even parenting.
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But to build AI systems we can trust, we need .
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이 레슨에 대해
"When AIs act emotional"으로 쉐도잉 기법을 사용해 영어를 연습합니다.
매일 15~30분 꾸준히 연습하면 IELTS 스피킹에 대한 자신감이 길러집니다.
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.