MILLIE P. ARORA MIKKEL KRENCHEL JACOB MCAULIFFE ReD Associates POORNIMA RAMASWAMY Cognizant [s2If is_user_logged_in()] Download PDF [/s2If] [s2If current_user_can(access_s2member_level1)] [/s2If] As algorithms play an increasingly important role in the lives of people and corporations, finding more effective, ethical, and empathetic ways of developing them has become an industry imperative. Ethnography, and the contextual understanding derived from it, has the potential to fundamentally change the way that data science is done. Reciprocally, engaging with data science can help ethnographers focus their efforts, build stronger and more precise insights, and ultimately have greater impact once their work is incorporated into the algorithms that increasingly power our society. In practice, building contextually-informed algorithms requires collaboration between human science and data science teams who are willing to extend their frame of reference beyond their core skill areas. This paper aims to first address the features...