Continuous Subject-in-the-Loop Integration: Centering AI on Marginalized Communities
This paper addresses the problem of AI reinforcing existing social structures for marginalized communities by proposing a framework for infrastructure development.
This paper argues that existing AI infrastructure hinders the adoption of 'radical AI' which aims to center marginalized communities. It proposes a guiding principle to identify these infrastructure gaps and evaluate new infrastructure proposals for their effectiveness in centering marginalized voices.
Despite its utopian promises as a disruptive equalizer, AI - like most tools deployed under the guise of neutrality - has tended to simply reinforce existing social structures. To counter this trend, radical AI calls for centering on the marginalized. We argue that gaps in key infrastructure are preventing the widespread adoption of radical AI, and propose a guiding principle for both identifying these infrastructure gaps and evaluating whether proposals for new infrastructure effectively center marginalized voices.