Big data: are we making a big mistake?

Five years ago, a team of researchers from Google announced a remarkable achievement in one of the world's top scientific journals, Nature. Without needing the results of a single medical check-up, they were nevertheless able to track the spread of influenza across the US. What's more, they could do it more quickly than the Centers for Disease Control and Prevention (CDC). Google's tracking had only a day's delay, compared with the week or more it took for the CDC to assemble a picture based on reports from doctors' surgeries. Google was faster because it was tracking the outbreak by finding a correlation between what people searched for online and whether they had flu symptoms. Not only was "Google Flu Trends" quick, accurate and cheap, it was theory-free. Google's engineers didn't bother to develop a hypothesis about what search terms – "flu symptoms" or "pharmacies near me" – might be correlated with the spread of the disease itself.