字幕表 動画を再生する 字幕スクリプトをプリント 翻訳字幕をプリント 英語字幕をプリント Technology has brought us so much 翻訳: Moe Shoji 校正: Naoko Fujii The moon landing, the internet, the ability to sequence the human genome 科学技術は多くをもたらしてくれました but it also taps into a lot of humans’ fear 月面着陸 インターネット and about thirty years ago, the cultural critic Neil Postman wrote a book call the amusing ourselves to death ヒトゲノム配列の解析などです Which lay this out really brilliantly ですが 私たちの奥深くにある 恐怖の多くにも それは入り込んでいます And here’s what he said comparing the dystopian visions of George Orwell and Aldous Huxley およそ30年ほど前 He said ‘Orwell fear that we will become a captive culture; Huxley fear that we would become a trivial culture.’ 文化批評家のニール・ポストマンは Orwell fear the truth would be conceal from us and Huxley fear we would be drown in the sea of irrelevance. "Amusing Ourselves to Death" という著作で In a nut shell, it’s a choice between big brother watching you and you watching big brother. このことを的確に述べました But it doesn’t have to be this way, we are not passive consumer of data and technology. 彼はこの著作において We shape the role it place in our life and the way we made meaning from it. ジョージ・オーウェルとオルダス・ハクスリーの But to do that, we have to pay as much attention to how we think as how we code ディストピア (反ユートピア) 思想を比べて こう書きました We have to ask question and hard question to move pass counting things to understanding them 「オーウェルは私たちが We’re constantly bombarded with stories about how much data there is in the world 囚われの身になる文化を恐れた But when it comes to big data, and the challenge is interpreting it ハクスリーは私たちが 取るに足らないことに耽溺する文化を恐れた Size isn’t everything. オーウェルは真実が There’s also the speed of which it moves 私たちから隠蔽されることを恐れ And the many variety of data types ハクスリーは私たちが無関心の海で And here are just the few examples, Images 溺れ死ぬことを恐れた」 Texts 要するに Video 「ビッグ・ブラザー」 に監視されるか Audio 「ビッグ・ブラザー」を監視するかの どちらかということです And what unites these despair it types of data (笑) Is that they are created by people でも そうでなくともよいのです And they require context 私たちはデータや技術を 受け身で消費するだけではありません Now, there’s a group of data scientists at the university of Illinos at Chicago 生活において データや技術が果たす役割や And they are called the Health Media collaboratory. その意味を見出す方法を 私たちが形作るのです And they have been working with the center for disease control しかし そのためには To better understand, how people talk about quitting smoking コード化の方法と同じくらいに How they talk about electronic cigarets. 考え方にも注意を向けねばなりません And what they can do collectively to help them quit. 物を数えるだけでなく さらにそれを理解するために The interesting thing is if you wanna understand how people talk about smoking 難解な問いを First you have to understand what they mean, when they say smoking 投げかけねばなりません And on Tweeter, they are four main categories. 私たちは世界に どれ位のデータがあるか First one, smoking cigarets. 常に聞かされていますが Number two, smoking marijuana. ビッグデータや Number three, smoking ribs. それを読み解く難解さとなると And number four, smoking hot women 量だけがすべてではありません So…then you have to think about what have the people talk about electronic cigarets? データが動く速さも問題になりますし And there are so many different ways that people do this データには様々な種類があります You can see from the slide. ごくわずかな例を挙げると It’s a complex kind of queery. 画像 And what that reminds us is that 文章 Languages created by people. 映像 And people are messy and were complex and we use metaphors and slang and jargon 音声などです And we do this twenty-four seven and many many languages. これら別々の種類のデータに 共通しているのは And then as soon as we figure it out, we change it up. これらは人の手で作られ So…did this ads that cdcs put on these television ads that feature a woman with a hole in her throat 文脈を必要としているということです And that were very graphic and very disturbing さて イリノイ大学シカゴ校出身の Did they actually have an impact on whether people quit? データ科学者のグループがあります And helpfully, the collaboratory respect the limits of their data このグループは ヘルス・メディア・コラボラトリーと呼ばれ But they were able to conclude that those advertisements and you may have seen them 米国疾病管理センターと一緒に仕事をし They have the affect of jotting people into a thought process. 人々が That may have an impact on future behavior. 禁煙についての言い表し方や And…what I admire, and appreciate about this project design from the fact, including the fact 電子タバコについての言い表し方 That’s base on real human need is that 禁煙を促すために協力しあえることを It’s a fantastic example of courage and the face of the sea of relevance. より良く理解するよう努めました And so…it’s not just big data that causes challenge and interpretation. 興味深いことに 人がどのように Because let’s face it. We human-beings have a very rich stream of taking any among of data 喫煙について話しているかを 理解するにはまず No matter how small and screwing it up. 「smoking (吸う)」という語で So…many years ago you may remember どんな意味が表されているかを 理解せねばなりません That formal president Ronald Reagan was very criticize for making a statement the facts are stupid things ツイッター上には 4つの主なカテゴリーがあります And it was a slip of the tongue. Let’s be fair. 1つ目 タバコを「吸う」 He actually meant to quote John Adams’ defense British soldiers in the Boston Massacre trial 2つ目 マリファナを「吸入する」 That facts are stubborn things. 3つ目 リブ肉を「いぶす」 But I actually think there’s a bit of accidental wisdom in what he said. 4つ目 「煙が出るほどホットな」イケてる女 Because facts are stubborning things. (笑) But sometimes they are stupid too. 電子タバコについて どのように話されているかは When I tell you a personal story about why this matters a lot to me その上で考えてみなければなりません I need to take a breath. これには 非常に様々な例が見られます My son Isaac when he was two, he is diagnose with autism. スライドからもおわかりのように And he was happy, hilarious, loving and affectionate little guy. これは複雑な問いなのです but the metrics on his developmental evaluations, which looked at things like the number of words — at that point, none このことで思い出すのは Communicate with gestures and minimum eye contact put his developmental level at that of a nine months old baby. 言語は人々によって作られたものであり And the diagnosis fact is actually correct but it didn’t tell the whole story. 人間は厄介かつ複雑なもので And about a year and a half later, he was almost four. 比喩やスラングや隠語を 使うものだということ I found him in front of the computer one day. そしてそれを人間は毎日24時間 多くの言語で行い続けており Running a google search on woman 理解するやいなや その言葉自体を変えてしまうことです Spell w-i-m-e-m では 米国疾病管理センターが出した And I did what any you know…upset parents will do 喉に穴が開いた女性を 映し出すこのテレビ広告は just immediate started hitting the back bottom to see what else he has been searching for 非常に描写が露骨で And they were in order men, school, bus and computer (cpyutr) 気持ちの良いものではありませんが And I was stunned. この広告は実際に禁煙するように Because we didn’t know that he could spell much less read 人々を促したのでしょうか? So I ask him. Isaac, how do you do this? ヘルス・メディア・コラボラトリーは データの限界を認めてはいますが And he looked at me very seriously and said ‘type in the box’ その結論によると He was teaching himself to communicate. あなた方も見たことがあるかもしれない これらの広告によって But we were looking at the wrong place. 将来の行動が And this is what happens when assessment and analytics over value one matrix in this case verbal communication 影響されるかもしれないような And undervalue others’ such as creating problem solving. 思考プロセスに 人々を導いたのだそうです Communication was hard for Isaac. 私がこのプロジェクトについて 感心し 評価するのは And so he found a work around to find out what he needed to know. 人間の現実的な必要性に 基づいている などの事実面はさておき And when you think about it, it makes a lot of sense. 人間の現実的な必要性に 基づいている などの事実面はさておき Because forming a question is really complex process. これが無関心の海に真っ向から 立ち向かう勇気を示す But he can get himself a lot of way there. By putting a word in the search box. 素晴らしい例であるということです And so this little moment had a really profound impact on me. 一方 理解が難しいのは ビッグデータだけではないのです In our family. Because it helps us change our reference for what’s going on for him. なぜなら 考えてもみてください And worry of a little bit less and appreciate his resource more. 私たち人間は データの大小にかかわらず Facts are stupid things. それを台無しにしてしまった 豊かな歴史を And they’re vulnerable to misuse willful or otherwise. 有しているではありませんか I have a friend - Emily Willingham who’s a scientist. 何年も前に ロナルド・レーガン元大統領が And she wrote a piece for forbes not long ago. このように述べて厳しく批判されたことを Entitled the ten weirdest things ever linked to autism. 皆さんも覚えているかもしれません It’s quite a list. 「事実とは馬鹿げたものである」と The internet link for everything, right? これは言い間違いでした 公平を期すなら ですが And of course mother. Because an actually way, there’s more others the whole bunch in the mother category here. 彼はジョン・アダムズが And you can see, it’s a pretty rich and interesting list. ボストン虐殺事件裁判において イギリス人兵士の弁護で述べた I’m a big fan of you know…being pregnant in a free way, personally. 「事実とは確固たるものである」を 引用したつもりだったのです The final one is interesting because the term of ‘refrigerator’ mother was actually the original hypothesis for the cause of autism. しかし このレーガンの言い間違いは And that meant somebody was cold and unloving. 偶然ながらも 一理あると私は思います And at this point, you might be thinking…okay…Susan we get it. なぜなら 事実は確固たるものですが You can take data. You can make it mean anything and this is true. 時に 馬鹿げてもいるからです It’s absolutely true. これが 私にとってなぜ重要なのか But the challenge is that 個人的なお話をしたいと思います We have this opportunity to try make meaning out of ourselves. ひと息つかせてください Because frankly, data doesn’t create meaning, we do. 息子のアイザックは 2歳の時に So as business people, as consumers, as patients, as citizens 自閉症の診断を受けました We have our responsibility, I think. 彼はにこにこして 愉快で To spend more time focus on our critical thinking skills. 愛情深く 優しい男の子でしたが Why? 彼の発育評価についての測定基準が Because at this point in our history as we heard, many times over we can process Exabyte in lightening speed. 着目したのは 話せる言葉の数や― And we have potential to make bad decisions far more quickly, efficiently and far greater impact than we did in the past. これは当時 ゼロでした― Great, right? 意思疎通を図る身振り アイコンタクトなどであったため And so what we need to do instead is spend a little bit more time on things like the humanities. 彼の発育レベルは And sociology, and the social sciences, rhetoric, philosophy, ethics. 9か月の赤ちゃん程度でした Because it gives us context that is so important for big data. この診断は事実からすれば 正しいものでしたが Because they help us become better critical thinkers. 全体像を語ってはいませんでした Because after all, if I can spot a problem in an argument, it doesn’t much matter whether it’s express in words or numbers およそ1年半後 And this means, teaching ourselves. アイザックがもうすぐ4歳になる頃 To find those conformation by thesis and false correlations. 私は ある日 彼がコンピュータの前で And being able to spot a naked emotional appeal from thirty yards. グーグル画像検索で 女性を検索しているのを見つけました Because something that happens after something doesn’t mean it happen because of it necessarily. 「w-i-m-e-n」というつづりで です And if you let me geek out on your first second, the Romans call this ‘post hoc ergo propterhoc’ 過干渉な親がそうするように 私も After which therefore because of which. 「前のページに戻る」ボタンをクリックし And it means questioning disciplines like demographics 他に何を検索していたのか知ろうとしました Why? Because they're based on assumptions about who we all are based on our gender 他の検索は 順番に「男性」 and our age and where we live as opposed to data on what we actually think and do 「学校」 「バス」 そして「コンピュータ」でした And since we have this data 私は呆気にとられました we need to treat it with appropriate privacy controls and consumer opt-in アイザックがスペルを知っているとも and beyond that, we need to be clear about our hypotheses, ましてや読めるとも知らなかったのです the methodologies that we use, and our confidence in the result そこで息子に訊きました 「どうやったの?」 As my high school algebra teacher used to say アイザックは私を真剣に見て 言いました show your math, because if I don't know what steps you took 「ボックスに文字をタイプしたんだ」 I don't know what steps you didn't take 彼は自分で意思疎通の仕方を 学んでいたのに and if I don't know what questions you asked, I don't know what questions you didn't ask 私たちは誤った部分に 目を向けていたのです And it means asking ourselves, really, the hardest question of all そして こういったことが起こるのは Did the data really show us this, or does the result make us feel more successful and more comfortable? 査定や分析が ある測定基準― So the Health Media Collaboratory, at the end of their project ここでは 言語による意思疎通― を過大評価して they were able to find that 87 percent of tweets about those very graphic and disturbing anti-smoking ads expressed fear 創造的問題解決能力のような 他の基準を過小評価する場合です but did they conclude that they actually made people stop smoking? アイザックにとって 他者との意思疎通は難しいので No. It's science, not magic. 彼は自分に必要なことを知るための So if we are to unlock the power of data 別の方法を見つけたのです We don't have to go blindly into Orwell's vision of a totalitarian future 考えてみれば 合点がいきますね or Huxley's vision of a trivial one, or some horrible cocktail of both. 質問文を構成するのは What we have to do is treat critical thinking with respect and be inspired by examples like the Health Media Collaboratory 実に複雑なプロセスですが and as they say in the superhero movies, let's use our powers for good. アイザックは検索ボックスに 単語を入れるだけで Thank you. 自力で答えにたどり着けるのです
B1 中級 日本語 米 TED データ アイザック 禁煙 ヘルス 事実 TED】Susan Etlinger.このすべてのビッグデータを使って何をするのか?(Susan Etlinger: What we do with all this big data?) (【TED】Susan Etlinger: What do we do with all this big data? (Susan Etlinger: What do we do with all this big data?)) 13518 928 Go Tutor に公開 2021 年 01 月 14 日 シェア シェア 保存 報告 動画の中の単語