Participation is not a Design Fix for Machine Learning
arXiv:2007.02423v3336 citations
AI Analysis
It addresses ethical concerns in ML design for practitioners and communities, highlighting potential harms in participation.
The paper critiques current participatory approaches in machine learning design, warning against exploitative practices and advocating for a shift away from scalability-focused methods.
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.