Практика Shadowing: When AIs act emotional - Изучайте разговорный английский по видео
Создание урока...
1
When you're chatting with an AI model, it can sometimes seem like it has feelings.
2
It might say sorry when it makes a mistake, or express satisfaction with a job well done.
3
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 .
📺 Тот же канал
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Лексика и советы по произношению к этому уроку
Этот урок разговорной практики уровня C1 построен на видео «When AIs act emotional». Чаще всего повторяются слова: Claude, model, neurons, character, emotion. В этом видео 55 предложений и 728 слов для шедоуинга. Речь длится 4:49. Говорящий говорит в естественном темпе, около 151 слов в минуту, близком к повседневной речи. Только 80% слов входят в 3000 самых частых слов английского языка, поэтому лексика сложная.
Ключевая лексика этого видео
Самые сложные слова из видео (15), с произношением и значением:
| Слово | Произношение | Значение |
|---|---|---|
| neuron существительное | /ˈn(j)ʊɹɑn/ | нейро́н, не́рвная кле́тка |
| desperation существительное | /ˌdɛspəˈɹeɪʃən/ | отча́яние |
| cheat глагол | /ˈt͡ʃiːt/ | моше́нничать, смоше́нничать |
| dial существительное | /ˈdaɪ.əl/ | цифербла́т |
| artificially наречие | иску́сственно | |
| compose глагол | /kəmˈpəʊz/ | составля́ть, соста́вить |
| neuroscience существительное | нейробиоло́гия, нейронау́ка | |
| resilient прилагательное | /ɹɪˈzɪl.jənt/ | ги́бкий, эласти́чный |
| shortcut существительное | /ˈʃɔːtkʌt/ | кратча́йший пу́ть, срез |
| correspond глагол | /ˌkoɹəˈspɑnd/ | соотве́тствовать, согласо́вываться |
| pawn существительное | /ˈpɔːn/ | пе́шка |
| unsafe прилагательное | /ʌnˈseɪf/ | опасный |
| overlap глагол | /ˌəʊvəˈlæp/ | накрыва́ть, перекрыва́ть |
| activate глагол | /ˈæktɪˌveɪt/ | активизи́ровать, активи́ровать |
| activation существительное | /ˌæktəˈveɪʃən/ | актива́ция, активиза́ция |
Фразовые глаголы, которые вы услышите
| Слово | Значение |
|---|---|
| turn out глагол | ока́зываться, оказа́ться |
| come up with глагол | придумывать, приходить в голову |
| light up глагол | свети́ть, освети́ть |
| turn down глагол | отверга́ть, отве́ргнуть |
Произношение, на которое стоит обратить внимание
Говорящий использует 9 сокращённых и редуцированных форм, например didn't, they're, don't. Произносите их коротко, так, как слышите.
- Звуки «sh» и «zh»: desperation /ˌdɛspəˈɹeɪʃən/, shortcut /ˈʃɔːtkʌt/, activation /ˌæktəˈveɪʃən/
- Длинные слова — следите за ударением: desperation /ˌdɛspəˈɹeɪʃən/, activation /ˌæktəˈveɪʃən/
Звуки, трудные для русскоязычных:
- Звонкие согласные в конце слова — не оглушайте их: compose /kəmˈpəʊz/, correspond /ˌkoɹəˈspɑnd/
Как заниматься с этим видео
- Прослушайте всё видео один раз молча и выпишите незнакомые слова.
- Начните со скорости 0,75×, повторяйте предложение за предложением и вернитесь к обычной скорости, когда станет легко.
- Запишите себя и сравните с оригиналом, обращая внимание на такие слова, как neuron, desperation, cheat.
Что такое техника Shadowing?
Shadowing — это научно обоснованная техника изучения языка, изначально разработанная для подготовки профессиональных переводчиков и популяризированная полиглотом доктором Александром Аргуэльесом. Метод прост, но эффективен: вы слушаете аудио на английском от носителей языка и немедленно повторяете вслух — как тень, следующая за говорящим с задержкой в 1–2 секунды. В отличие от пассивного прослушивания или грамматических упражнений, Shadowing заставляет мозг и мышцы рта одновременно обрабатывать и воспроизводить реальные речевые паттерны. Исследования показывают, что это значительно улучшает точность произношения, интонацию, ритм, связную речь, понимание на слух и беглость речи — что делает его одним из самых эффективных методов для подготовки к IELTS Speaking и реального общения на английском.