シャドーイング練習: Why Are People Starting to Sound Like ChatGPT? | Adam Aleksic | TED - YouTubeで英語スピーキングを学ぶ
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How sure are you that you can tell what's real online?
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How sure are you that you can tell what's real online?
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(Laughter) You might think it's easy to spot an obviously AI-generated image, and you're probably aware that algorithms are biased in some way.
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But all the evidence is suggesting that we're pretty bad at understanding that on a subconscious level.
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Take, for example, the growing perception gap in America.
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We keep over- and overestimating how extreme other people's political beliefs are, and this is only getting worse with social media, because algorithms show us the most extreme picture of reality.
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As an etymologist and content creator, I always see controversial messages go more viral because they generate more engagement than a neutral perspective.
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But that means we all end up seeing this more extreme version of reality, and we're clearly starting to confuse that with actual reality.
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The same thing is currently happening with AI chatbots, because you probably assume that ChatGPT is speaking English to you, except it's not speaking English, in the same way that the algorithm's not showing you reality.
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There are always distortions, depending on what goes into the model and how it's trained.
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Like we know that ChatGPT says “delve” at way higher rates than usual, possibly because OpenAI outsourced its training process to workers in Nigeria who do, actually, say, "delve" more frequently.
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Over time, though, that little linguistic overrepresentation got reinforced into the model even more than in the workers' own dialects.
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Now that's affecting everybody's language.
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Multiple studies have found that, since ChatGPT came out, people everywhere have been saying the word "delve" more in spontaneous spoken conversation.
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Essentially, we're subconsciously confusing the AI version of language with actual language.
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But that means that the real thing is, ironically, getting closer to the machine version of the thing.
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We're in a positive feedback loop with the AI representing reality, us thinking that's the real reality, and regurgitating it so the AI can be fed more of our data.
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You can also see this with the algorithm through words like "hyperpop," [not a] part of our cultural lexicon until Spotify noticed an emerging cluster of similar users in their algorithm.
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[When] they identified it and introduced a hyperpop playlist, however, the aesthetic was given a direction.
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Now people began to debate what did and did not qualify as hyperpop.
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The label and the playlist made the phenomenon more real by giving them something to identify with or against.
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And as more people identified with hyperpop, more musicians also started making hyperpop music.
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All the while, the cluster of similar listeners in the algorithm grew larger, and Spotify kept pushing it more, because these platforms want to amplify cultural trends to keep you on the app.
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But that means we also lose the distinction between a real trend and an artificially inflated trend.
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And yet, this is how all fads now enter the mainstream.
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We start with a latent cultural desire.
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Maybe some people are interested in matcha, Labubu or Dubai chocolate.
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The algorithm identifies this desire and pushes it to similar users, making the phenomenon more of a thing.
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But again, just like how ChatGPT misrepresented the word "delve," the algorithm is probably misrepresenting reality.
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Now more businesses are making Labubu content because they think that's the desire.
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More influencers are also making Labubu trends because we have to tap into trends to go viral.
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And yet, the algorithm is only showing you the visually provocative items that work in the video format.
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TikTok has a limited idea of who you are as a user, and there's no way that matches up with your complex desires as a human being.
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So we have a biased input.
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And that's assuming that social media is trying to faithfully represent reality, which it isn't.
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It's only trying to do what's going to make money for them.
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It's in Spotify's interest to have you listening to hyperpop, and it’s in TikTok’s to have you looking at Labubus because that's commodifiable.
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So again, we have this difference between reality and representation, where they're actually constantly influencing one another.
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But it's incredibly dangerous to ignore that distinction, because this goes beyond our language and consumptive behaviors.
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This affects the world we see as possible.
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Evidence suggests that ChatGPT is more conservative when speaking the Farsi language, likely because of the limited training texts in Iran reflect the more conservative political climate in the region.
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Does that mean that Iranian ChatGPT users will think more conservative thoughts?
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Elon Musk regularly makes changes to his chatbot Grok when he doesn't like how it's responding, and then uses his platform X to artificially amplify his tweets.
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Does that mean that the millions of Grok and X users are subconsciously being trained to align with Musk's ideology?
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We need to constantly remember that these aren't neutral tools.
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Everything that ends up in your social media feed or in your chatbot responses is actually filtered through many layers of what's good for the platform, what makes money and what conforms to the platform’s incorrect idea about who you are.
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When we ignore this, we view reality through a constant survivorship bias, which affects our understanding of the world.
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After all, if you're talking more like ChatGPT, you're probably thinking more like ChatGPT as well, or TikTok or Spotify.
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But you can fight this if you constantly ask yourself: Why?
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Why am I seeing this?
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Why am I saying this?
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Why am I thinking this?
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And why is the platform rewarding this?
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If you don't ask yourself these questions, their version of reality is going to become your version of reality.
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So stay real.
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(Cheers and applause)
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この動画で話す練習をする理由
この動画は、今日のデジタル社会におけるコミュニケーションの変化を探求しており、特にAIとその影響について深く掘り下げています。話す練習をすることで、実際の会話の中での言葉の使い方や、話し手の意図を理解しやすくなります。AIの影響を受けた言語使用は、私たちの表現力にも大きく影響を与えています。YouTubeで英語学習を進める中で、この動画を使って練習することで、最新のトピックに基づく実践的な表現力を身につけることができます。
文法と表現の文脈
- 「might think」: 可能性を示す表現で、相手の意見に柔軟性を持たせる際に便利です。会話の中で使うと、相手に配慮した印象を与えます。
- 「is suggesting」: 現在進行形を用いて、事実が進行中であることを示します。これにより、話題性のあるテーマを強調することができます。
- 「that means」: これは因果関係を示す際の便利なフレーズです。自分の意見や結論を強調する助けになります。
- 「you probably assume」: 曖昧な仮定を示すことで、聞き手との共通理解を生み出します。会話での雰囲気を柔らかくする要素ともなります。
- 「it’s in (someone's) interest」: 利害関係を示す表現で、ビジネスや社会的な文脈でよく使われます。IELTS スピーキング対策としても有効です。
発音の落とし穴
この動画では、特に注意が必要な単語やフレーズがいくつかあります。たとえば、「algorithm」は発音が難しいため、多くの英語学習者が間違いやすい単語です。また、「delve」はその使用頻度が高まっているため、発音の練習も必要です。これらの単語を正確に発音することは、shadow speakやshadowing siteを活用する上で重要です。正しい発音をすることで、聞き手により明確に意図を伝えることができます。
シャドーイングとは？英語上達に効果的な理由
シャドーイング（Shadowing）は、もともとプロの通訳者養成プログラムで開発された言語学習法で、多言語習得者として知られるDr. Alexander Arguelles によって広く普及されました。方法はシンプルですが非常に効果的：ネイティブスピーカーの英語を聞きながら、1〜2秒の遅延で声に出してすぐに繰り返す——まるで「影（shadow）」のように話者を追いかけます。文法ドリルや受動的なリスニングと異なり、シャドーイングは脳と口の筋肉が同時にリアルタイムで英語を処理・再現することを強制します。研究により、発音精度、抑揚、リズム、連音、リスニング力、そして会話の流暢さが大幅に向上することが確認されています。IELTSスピーキング対策や自然な英語コミュニケーションを目指す方に特におすすめです。