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自分が読んで興味深く感じた英文記事を中心に取り上げる予定です

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Man and machine should go hand-in-hand

 
東日本大震災関連のニュースはiPad版ニューヨークタイムズの一面にはなく、一面記事で目に付いたのが以下の記事。ビッグデータ関連の記事は関心が高いということでしょうか。

Algorithms Get a Human Hand in Steering Web
By STEVE LOHR
Published: March 10, 2013

Trading stocks, targeting ads, steering political campaigns, arranging dates, besting people on “Jeopardy” and even choosing bra sizes: computer algorithms are doing all this work and more.

But increasingly, behind the curtain there is a decidedly retro helper — a human being.

Although algorithms are growing ever more powerful, fast and precise, the computers themselves are literal-minded, and context and nuance often elude them. Capable as these machines are, they are not always up to deciphering the ambiguity of human language and the mystery of reasoning. Yet these days they are being asked to be more humanlike in what they figure out.

常々このブログでは文脈やニュアンスの大切さを語らせていただいていますが、データ分析においても重要になってきているようです。Although algorithms are growing ever more powerful, fast and precise, the computers themselves are literal-minded, and context and nuance often elude them.(アルゴリズムはますます強力、迅速、正確になってきているが、コンピューター自身は文字通りのことしか考えられないため、文脈やニュアンスを捉え損なうことが多い)とありますが、このようなコンピュータ的な言語観で外国語学習に取り組む人が多いんですよね。

この記事はデータ分析について人間が補正している具体例をいくつか紹介してくれています。英語学習でもコーパス、コーパスと言いますが人間の補正は不可欠のはずです。

Twitter uses a far-flung army of contract workers, whom it calls judges, to interpret the meaning and context of search terms that suddenly spike in frequency on the service.

For example, when Mitt Romney talked of cutting government money for public broadcasting in a presidential debate last fall and mentioned Big Bird, messages with that phrase surged. Human judges recognized instantly that “Big Bird,” in that context and at that moment, was mainly a political comment, not a reference to “Sesame Street,” and that politics-related messages should pop up when someone searched for “Big Bird.” People can understand such references more accurately and quickly than software can, and their judgments are fed immediately into Twitter’s search algorithm.

“Humans are core to this system,” two Twitter engineers wrote in a blog post in January.

大統領選討論会でロムニー候補がBig Birdについてコメントした折りに、ツイッターでも反応が多かったそうです。People can understand such references more accurately and quickly than software canとあるようにこの場合Big Birdという言葉を含めてツイートしているのは政治関連だと人間だったらすぐに判断できますよね。コンピューターは意味や文脈を読み取るのは苦手ですから、人間が補正してあげないといけないみたいですね。

次に最近グーグル検索すると右手にwikipediaからの引用が表示されるようになりましたよね。この機能も人の手が加えられたデータベースの情報だそうです。

Even at Google, where algorithms and engineers reign supreme in the company’s business and culture, the human contribution to search results is increasing. Google uses human helpers in two ways. Several months ago, it began presenting summaries of information on the right side of a search page when a user typed in the name of a well-known person or place, like “Barack Obama” or “New York City.” These summaries draw from databases of knowledge like Wikipedia, the C.I.A. World Factbook and Freebase, whose parent company, Metaweb, Google acquired in 2010. These databases are edited by humans.

When Google’s algorithm detects a search term for which this distilled information is available, the search engine is trained to go fetch it rather than merely present links to Web pages.

“There has been a shift in our thinking,” said Scott Huffman, an engineering director in charge of search quality at Google. “A part of our resources are now more human curated.”

よりよい情報を表示するためには、グーグルでさえ人の判断が必要になってきたということですね。

The algorithms are getting better. But they cannot do it alone.

“You need judgment, and to be able to intuitively recognize the smaller sets of data that are most important,” Mr. Taylor said. “To do that, you need some level of human involvement.”

すぐに機械が、ロボットが人間に置き換わるようになるという話になりがちですが、やはり大切なのは、機械ができること、人間ができることの線引を引き直していくことなのかもしれません。
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