s Google’s Flu Trends (GFT) tracking system a failure of big data?

A new article published this afternoon in Science magazine suggests that Google’s much-covered algorithmic Flu Trends model, used to monitor search queries to track the spread of the flu, has routinely failed to accurately predict flu prevalence since it’s inception in 2008. While the report is another setback for Google (a 2013 article in the science journal Nature came to a similar conclusion about GFT’s accuracy), GFT’s failures represent a bigger struggle for data-driven research and threaten to cast a shadow on the broader, much-hyped concept of big data.

In late 2008, Google announced Google Flu Trends to a series of cautiously optimistic early reviews. The New York Times described it as “what appears to be a fruitful marriage of mob behavior and medicine” and many held out hope that Google’s algorithm could outperform CDC data models, which have long been held as the standard for flu detection and prediction.