But, as an article in Science earlier this month made clear, Google Flu Trends has systematically overestimated the prevalence of flu every single week since August 2011.
Mikkel Krenchel & Christian Madsbjerg
Mikkel Krenchel is a Senior Manager at ReD Associates, where Christian Madsbjerg is a founding partner. Madsbjerg is also co-author of “The Moment of Clarity: Using the Human Sciences to Solve Your Toughest Business Problems.” Their company, ReD Associates, is an innovation and strategy consultancy based in New York and Copenhagen. The consultants at ReD employ methods from the social and human sciences to put a deep understanding of real people back at the center of business decision making. Their clients include Samsung, Intel, Adidas, LEGO and Novo Nordisk.
And back in 2009, shortly after launch, it completely missed the swine flu pandemic. It turns out, many of the words people search for during Flu season have nothing to do with Flu, and everything to do with the time of year flu season usually falls: winter.
Now, it is easy to argue – as many have done – that the failure of Google Flu Trends simply speaks to the immaturity of big data. But that misses the point. Sure, tweaking the algorithms, and improving data collection techniques will likely make the next generation of big data tools more effective. But the real big data hubris is not that we have too much confidence in a set of algorithms and methods that aren’t quite there yet. Rather, the issue is the blind belief that sitting behind a computer screen crunching numbers will ever be enough to understand the full extent of the world around us.
Why Big Data Needs Thick Data
Big data is really just a big collection of what people in the humanities would call thin data. Thin data is the sort of data you get when you look at the traces of our actions and behaviors. We travel this much every day; we search for that on the Internet; we sleep this many hours; we have so many connections; we listen to this type of music, and so forth. It’s the data gathered by the cookies in your browser, the FitBit on your wrist, or the GPS in your phone. These properties of human behavior are undoubtedly important, but they are not the whole story.
To really understand people, we must also understand the aspects of our experience — what anthropologists refer to as thick data. Thick data captures not just facts but the context of facts. Eighty-six percent of households in America drink more than six quarts of milk per week, for example, but why do they drink milk? And what is it like? A piece of fabric with stars and stripes in three colors is thin data. An American Flag blowing proudly in the wind is thick data.
A PIECE OF FABRIC WITH STARS AND STRIPES IN THREE COLORS IS THIN DATA. AN AMERICAN FLAG BLOWING PROUDLY IN THE WIND IS THICK DATA.
Rather than seeking to understand us simply based on what we do as in the case of big data, thick data seeks to understand us in terms of how we relate to the many different worlds we inhabit. Only by understanding our worlds can anyone really understand “the world” as a whole, which is precisely what companies like Google and Facebook say they want to do.
Knowing the World Through Ones and Zeroes
Consider for a moment, the grandiosity of some of the claims being made in Silicon Valley right now. Google’s mission statement is famously to ”organize the world’s information and make it universally accessible and useful.” Mark Zuckerberg recently told investors that, along with prioritizing increased connectivity across the globe and emphasizing a knowledge economy, Facebook was committed to a new vision called “understanding the world.” He described what this “understanding” would soon look like: “Every day, people post billions of pieces of content and connections into the graph [Facebook’s algorithmic search mechanism] and in doing this, they’re helping to build the clearest model of everything there is to know in the world.” Even smaller companies share in the pursuit of understanding. Last year, Jeremiah Robison, the VP of Software at Jawbone, explained that the goal with their Fitness Tracking device Jawbone UP was “to understand the science of behavior change.”
These goals are as big as the data that is supposed to achieve them. And it is no wonder that businesses yearn for a better understanding of society. After all, information about customer behavior and culture at large is not only essential to making sure you stay relevant as a company, it is also increasingly a currency that in the knowledge economy can be traded for clicks, views, advertising dollars or simply, power. If in the process, businesses like Google and Facebook can contribute to growing our collective knowledge about of ourselves, all the more power to them. The issue is that by claiming that computers will ever organize all our data, or provide us with a full understanding of the flu, or fitness, or social connections, or anything else for that matter, they radically reduce what data and understanding means.