It’s ironic that in an era of big data, truth sometimes seems more elusive than ever. To make better choices about how to manage our lives, our work, and our environment, we need to use the best possible information to guide us. But even with great data, humans don’t always make great choices- we misinterpret, we oversimplify, we fail to see fallacies in logic or flaws in the data itself- and even our most rational examinations of the numbers are fundamentally human, shaped by culture, prior experience, and our internal biases.In this podcast, we explore the process of how data becomes information, information becomes knowledge and knowledge becomes belief- and how, in turn, belief shapes the way we take and interpret data. From young learners to practicing scientists, the ways we incorporate information into our worldview is affected by our experiences. We combine social and data science perspectives with the study of how humans learn, in order to examine not just what we know, but how we know it.