In this Comment, we examine how structural inequalities, biases, and racism in society are easily encoded in datasets and in the application of data science, and how this practice can reinforce existing social injustices and health inequalities. Approaching the problem from the perspective of data scientists, we follow the stages in an analytical pipeline to consider how and where things can go wrong. We then outline the essential role of data scientists in tackling racism and discrimination.
The Lancet Digital Health, Volume 3, March 2021,
Ancestry Group; Biomedical Research; Black Person; Caucasian; Continental Population Groups; Coronavirus Disease 2019; Data Analysis; Data Collection; Ethnic Group; Ethnic Groups; Health Care Delivery; Health Data; Health Disparity; Health Equity; Health Promotion; Human; Humans; Information Dissemination; Information Processing; Medical Ethics; Medical Research; Note; Pandemic; Personnel; Racism; Research Personnel; Social Justice; Stigma; Global