This article argues that the consideration of epistemological friction is essential to DH computing. It proposes a framework outlining common sites of friction with the intention that it be used as a pedagogical scaffold.

This article surveys the ways in which issues of race and gender bias emerge in projects involving the use of predictive analytics, big data and artificial intelligence (AI).