Big Data Doesn’t Interpret Itself

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Big Data Doesn’t Interpret Itself
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The history of astronomy teaches the limits of a “big data” approach to problem-solving, writes Frank Wilczek

The history of astronomy shows that observations can only explain so much without the interpretive frame of theories and modelsBig data and machine learning are powering new approaches to many scientific questions. But the history of astronomy offers an interesting perspective on how data informs science—and perhaps a cautionary tale.

Early Babylonian astronomers took what today we’d call a pure “big data” or “pattern recognition” approach. They accumulated observations of solar, lunar and planetary motion and eclipses for many centuries and identified various cycles that had repeated many times. Simply by assuming that those cycles would continue,...

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