Pois é, parece que sim. Ao menos de acordo com a Nature.
Para quem não sabe o que aconteceu, alguns pesquisadores realizaram análises no Google Flu Trends e encontraram problemas em relação ao modelo.
Os resultados estão nos artigos abaixo:
The Parable of Google Flu: Traps in Big Data Analysis
In February 2013, Google Flu Trends (GFT) made headlines but not for a reason that Google executives or the creators of the flu tracking system would have hoped. Nature reported that GFT was predicting more than double the proportion of doctor visits for influenza-like illness (ILI) than the Centers for Disease Control and Prevention (CDC), which bases its estimates on surveillance reports from laboratories across the United States (1, 2). This happened despite the fact that GFT was built to predict CDC reports. Given that GFT is often held up as an exemplary use of big data (3, 4), what lessons can we draw from this error?