A member of staff poses for a photograph in a projection of live data feeds taken from Twitter, Instagram and Transport for London, as he stands in the 'London Situation Room,' a n artwork created in collaboration with Future Cities Catapult & Tekja, during a photocall to promote the Big Bang Data exhibition at Somerset House in London on December 2, 2015. Justin Tallis/Stringer

Как управлять большими рисками «больших данных»

НЬЮ-ЙОРК – В течение последних 15 лет мы стали свидетелями взрывного роста объёмов электронных данных (доступных из интернета, социальных сетей, научного оборудования, смартфонов, камер наблюдения и многих других источников), а также быстрого развития компьютерных технологий, применяемых для их обработки. Эти так называемые «Большие данные» (Big Data), несомненно, помогут добиться важных научных, технических и медицинских успехов. Однако «большие данные» создают ещё и серьёзные риски, если они используются неправильно или со злым умыслом.

В таких значительных инновациях, как например, поисковые системы в интернете, машинный перевод, маркировка изображений, уже активно применяются технологии машинного обучения для обработки огромных массивов данных. А в ближайшем будущем «большие данные» позволят значительно улучшить качество принимаемых государственных решений, программ социальной помощи, научных знаний.

Однако наличие больших объёмов данных не может заменить собой наличие данных высокого качества. Например, как отмечается в недавней статье в журнале Nature, организаторы предвыборных опросов в США испытывают серьёзные трудности с получением репрезентативной выборки населения, поскольку закон разрешает им звонить только на телефоны фиксированной, проводной связи, а между тем, американцы всё больше пользуются сотовой связью. И хотя в социальных сетях можно найти бессчётное множество политических комментариев, их тоже нельзя считать надёжным отражением мнений избирателей. Более того, значительная часть твитов и публикаций в Facebook на тему политики сгенерирована компьютерами.

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