What we do, what they know
Even primitive humans left data trails in the form of footsteps, campfires, and arrowheads. But in the digital age, we are constantly generating data. Search engines and advertisers tap it. So does the National Security Agency. Convenience and security are the upside. Loss of privacy is the downside.
The footprints and arrowheads left by Stone Age ancestors are data from which archaeologists piece together the prehistoric world. That was little data. Digital Age humans generate big data.Skip to next paragraph
Editor-at-Large, The Christian Science Monitor
John Yemma is editor-at-large of The Christian Science Monitor, having served as the Monitor's editor from 2008 to 2014. The Monitor publishes international news and analysis at CSMonitor.com, in the Monitor Weekly newsmagazine, and in an email-delivered Daily News Briefing. John can be reached at email@example.com.
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IBM estimates that 90 percent of the data in the world has been created in the past two years alone. The data flows from tweets, GPS signals, online searches, security cameras, and on and on. When all that data is vacuumed up and analyzed, it can produce insights into everything from retail marketing to crime fighting, electricity management to public health. In a Monitor cover story, Robert Lehrman delves into the benefits and costs of Big Data.
Along with the efficiencies and clever new applications that Big Data has yielded come big concerns about privacy. As science historian George Dyson noted in a recent article published in Edge.org, “If Google has taught us anything, it is that if you simply capture enough links, over time, you can establish meaning, follow ideas, and reconstruct someone’s thoughts. It is only a short step from suggesting what a target may be thinking now, to suggesting what that target may be thinking next.”
Even if you scrub all the cookies from your browser, ditch your cellphone, steer clear of social media, microwave your modem, and relocate to Walden Pond – just by being an earthling you’ll still leave a data trail. You’ll need to shop for food – or at least for seed to grow your own. Security cameras will see you, and the cash register will record your purchase. Selling any of that produce to buy shoes? Unless you’re a scofflaw, you have to pay taxes (more data). And you’re not going to stop phoning Mom and Dad, are you? Even a pay phone generates a call record.
Few people opt for the hermit lifestyle. Cellphones, computers, credit cards, and other conveniences are useful, even essential. So most of us make a mental bargain. We assume there’s a data trail and that for the most part it is nothing to worry about. Those security cameras deter crime. Those cookie-generated behavioral ads on the Internet may seem a little too familiar at times, but we’re adept at tuning out ads.
Even as Edward Snowden’s revelations of the scope of spying by the National Security Agency have boosted Americans’ concerns about privacy, according to recent opinion polls, there has not been a groundswell against the practice – perhaps because of continued concern about potential terrorism, perhaps a sense that only bad guys need worry.
But history shows that intelligence assets aimed at foreign threats can be employed domestically (see Cointelpro, Watergate, post-2001 warrantless surveillance – and far more egregious examples in other countries). Nor is it hard to imagine a mid-level employee in a government agency or private company (e.g., Mr. Snowden or Pfc. Bradley Manning) snooping out of curiosity or as a self-appointed whistle-blower. And ongoing phishing, spamming, and hacking problems on the Internet are a reminder that data hijackers are plentiful.
Here’s an easy prediction: Big Data is only going to get bigger. Every year, more sensors will produce more signals that will be more quickly analyzed. This will lead to more convenience. And more concern. Mr. Dyson – whose physicist father, Freeman Dyson, grappled with wondrous but fraught technologies such as nuclear energy – sums up the Big Data revolution this way: “Yes, we need big data, and big algorithms – but beware.”