Participation is NOT a Design Fix for Machine Learning

August, 2020


This paper critically examines existing modes of participation in design practice and machine learning. Cautioning against 'participation-washing', it suggests that the ML community must become attuned to possibly exploitative and extractive forms of community involvement and shift away from the prerogatives of context-independent scalability.

Perspectives on Big Data, Ethics, and Society

Jacob Metcalf, Emily F. Keller, Danah Boyd


The Council for Big Data, Ethics, and Society was convened to bring together researchers from diverse fields who were thinking deeply about ethical, social and policy challenges associated with the rise of “big data” research and industry, with an eye toward developing recommendations about future directions for the field.