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The new age of algorithms

Sunday, August 11, 2013 18:04

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They work a few hundred yards from one of the Library of Congress’s most prized possessions: a vellum copy of the Bible printed in 1455 by Johann Gutenberg, inventor of movable type. But almost six centuries later, Jane Mandelbaum and Thomas Youkel have a task that would confound Gutenberg.

The researchers are leading a team that is archiving almost every tweet sent out since Twitter began in 2006. A half-billion tweets stream into library computers each day.

Their question: How can they store the tweets so they become a meaningful tool for researchers – a sort of digital transcript providing insights into the daily flow of history?

Thousands of miles away, Arnold Lund has a different task. Mr. Lund manages a lab for General Electric, a company that still displays the desk of its founder, Thomas Edison, at its research headquarters in Niskayuna, N.Y. But even Edison might need training before he’d grasp all the dimensions of one of Lund’s projects. Lund’s question:

How can power companies harness the power of data to predict which trees will fall on power lines during a storm – thus allowing them to prevent blackouts before they happen?

The work of Richard Rothman, a professor at Johns Hopkins University in Baltimore, is more fundamental: to save lives. The Centers for Disease Control and Prevention (CDC) in Atlanta predicts flu outbreaks, once it examines reports from hospitals. That takes weeks. In 2009, a study seemed to suggest researchers could predict outbreaks much faster by analyzing millions of Google searches.

Spikes in queries like “My kid is sick” signaled a flu outbreak before the CDC knew there would be one. That posed a new question for Dr. Rothman and his colleague Andrea Dugas:

Could Google help predict influenza outbreaks in time to allow hospitals like the one at Johns Hopkins to get ready?

They ask different questions. But all five of these researchers form part of the new world of Big Data – a phenomenon that may, for better or worse, revolutionize every facet of life, culture, and, well, even the planet. From curbing urban crime to calculating the effectiveness of a tennis player’s backhand, people are now gathering and analyzing vast amounts of data to predict human behaviors, solve problems, identify shopping habits, thwart terrorists – everything but foretell which Hollywood scripts might make blockbusters. Actually, there’s a company poring through numbers to do that, too.

Just four years ago, someone wanted to do a Wikipedia entry on Big Data. Wikipedia said no; there was nothing special about the term – it just combined two common words. Today, Big Data seems everywhere, ushering in what advocates consider some of the biggest changes since Euclid.

Want to get elected to public office? Put a bunch of computer geeks in a room and have them comb through databases to glean who might vote for you – then target them with micro-tailored messages, as President Obama famously did in 2012.

Want to solve poverty in Africa? Analyze text messages and social media networks to detect early signs of joblessness, epidemics, and other problems, as the United Nations is trying to do.

Eager to find the right mate? Use algorithms to analyze an infinite number of personality traits to determine who’s the best match for you, as many online dating sites now do.

What exactly is Big Data? What makes it new? Different? What’s the downside?

Such questions have evoked intense interest, especially since June 5. On that day, former National Security Agency analyst Edward Snowden revealed that, like Ms. Mandelbaum or Rothman, the NSA had also asked a question:

Can we find terrorists using Big Data – like the phone records of hundreds of millions of ordinary Americans? Could we get those records from, say, Verizon?

Mr. Snowden’s disclosures revealed that PRISM, the program the NSA devised, secretly monitors calls, Web searches, and e-mails, in the United States and other countries.

The dark side of Big Data involves much more than Snowden’s disclosure, or what the US does. And what made Big Data possible did not happen overnight. The term has been around for at least 15 years, though it’s only recently become popular.

“It will be quite transformational,” says Thomas Davenport, an information technology expert at Babson College in Wellesley, Mass., who co-wrote the widely used book “Competing on Analytics: The New Science of Winning.”

What exactly will it transform? To find out, let’s go back to the beginning.

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