Without Human Insight, Big Data Is Just A Bunch Of Numbers

Big data is undoubtedly useful, but it takes human analysis to figure out how to understand what it is we "know," and how to take action on it.

A recent USA TODAY piece by Chuck Raasch about Rick Smolan's new book, The Human Face of Big Data, looks at how humanity is impacted by the unparalleled ways we can now collect, analyze, and use data. Perhaps what struck me most was a phrase used by both the article title and Smolan, likening "big data" to a "planetary" or "global" nervous system. Jonathan Harris uses a similar phrase in the article about the Internet in general.)

Without a doubt, more things can be quantified than ever before. The myriad ways that benefits society is only hinted at in Raasch's article, and I'm sure the same can be said for Smolan's book. With the wealth of data we can now collect and analyze in increasingly sophisticated ways, we have only scratched the surface as to the vast number of advances we might find.

However, in any era with rapid technological change, it's easy to start slipping into what has been termed "technological determinism," to start speaking of the technology as if it drives culture and humanity, rather than thinking of technology as a tool.

"Big data as our global nervous system" presumes everything can be quantified, that culture can be culled down to quantitative data. It supposes the world is infinitely knowable. It posits that context and particularity is only so useful inasmuch as it can be captured by machines. And that's where the tail starts to wag the dog, to use a cliche.

Big data can't tell Lexus that my customer survey results were skewed by the fact that the person who sold me my car laid a guilt trip on me to fill out all "excellent" reviews on his survey, lest his pay get docked. Big data can't tell Target that it might be causing significant strife for a teenage-mom-to-be by giving prenatal coupons to her family. Big data couldn't tell one major company I worked with that their heralded and highly successful social media presence for job seekers was actually primarily a place people came to only when they'd narrowed their search down to the final few contenders, and that they weren't connecting with the audiences they sought to reach earlier in the job-hunting process.

Before we've completely decided what this new world looks like and what big data is, let's think long and hard about the things that can't—and won't ever be—quantifiable...or, to put it in better terms, what gets "boiled out" when you quantify human communication—the context and humanity that a spreadsheet can't capture. As I wrote last February, perhaps the answer is that our organizations must become "cyborgs": combining what can be gathered technologically with the humanity that can help us balance and make sense of what the quantitative can tell us, lest we be lose our humanity and just become robots.

I'm of the staunch belief that unparalleled development of both data and qualitative insight, in combination, can further help transform human understanding, technological advancement, and everyday life. New access to quantitative data gives us unparalleled access to information at a scale we've never had before. We can discover patterns in quantitative data we didn't know existed.

And qualitative insight helps us truly understand the lives of other people, to listen to them in the full context of what they are talking about—to pay attention to the particulars. Human analysis and thinking about what all that qualitative and quantitative data means is what helps us make sense of it all: to empathize with other people, to consider the ethical questions that will inevitably come along with how data is collected and what data tells us, and to perform the sort of qualitative pattern recognition that helps us identify what's happening in culture, in ways that numbers support but can't lead (because we have to know what we're looking for to find it in the numbers). Continuum's Lara Lee may have said it best in Stephanie Clifford's New York Times piece back in July: "Data can't tell you where the world is headed."

Perhaps, most of all, it will take human analysis to figure out how to understand what it is we "know," and how to take action on it. As Frank Eliason once told me, senior executives are rarely convinced by numbers that aren't financial, but a good story that illustrates an issue and creates empathy—with data that backs that story up—is a convincing package.

Grant McCracken, Emily Yellin, Carol Sanford, the aforementioned Lara Lee and I discussed this issue in-depth at the recent Futures of Entertainment 6 conference at MIT, in a session called "Listening and Empathy: Making Companies More Human". And coming out of that conference, finding this balance between big data and qualitative insights is a subject a group of us are planning to roll up our sleeves and tackle. I hope you'll join us.

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—Sam Ford is director of digital strategy for Peppercomm, a Futures of Entertainment Fellow, a research affiliate of the program in Comparative Media Studies at MIT, and an instructor with Western Kentucky University's Popular Culture Studies program. He is also coauthor of the forthcoming book Spreadable Media with Henry Jenkins and Joshua Green. Sam was named 2011 Social Media Innovator of the Year by Bulldog Reporter and serves on the Membership Ethics Advisory Panel for the Word of Mouth Marketing Association. He is also co-editor of with Abigail De Kosnik and C. Lee Harrington. Follow him on Twitter @Sam_Ford.

[Image: Flickr user Bogdan Suditu]

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