Trusting any data set or analysis requires a leap of faith. Beyond an acceptance of margins of error and biases, all data-driven decisions necessitate a will to believe. When it comes to data that impacts or justifies institutional decisions, this belief must exist not only in the institution's ability to be honest and rigorous with data, but in the very authority of data itself to tell us something meaningful about the world. In an era of “alternative facts” and fear-based advocacy, we must contend with this; but it may also sometimes be a symptom of data tunnel vision. How can we be better at designing the conditions for people to develop faith in our (and their) ability to do good things with data? And how can purposefully-deployed inefficiencies improve the resilience of human systems?