The advent of big data was supposed to usher in a more precise and rational world. Instead, it might be leading us into the swamp of "alternative facts."

Data may not lie, but they can be interpreted in ways that have the same effect. Consider U.S. President Donald Trump's persistent claim that millions voted fraudulently in the 2016 election. In a twisted way, it might be based on data: In 2012, a study found that some 2.75 million people were registered to vote in two states or more. Although there's zero evidence that any of them actually voted twice, that doesn't matter to Trump or his supporters.

This sleight of hand both illustrates and contributes to a bigger problem: We're losing trust in numbers, especially statistics. Their sheer volume and variety can be overwhelming. In Politico's recent roundup of Trump's popularity figures, for example, the approval numbers among nine polls ranged from 36 percent to 54 percent. Add the hangover that many still suffer from the misleading presidential election predictions, and it's not surprising that people are starting to tune out data altogether, or simply interpret them in ways that support their beliefs.