The Equitable AI Research Roundtable (EARR): Towards Community-Based Decision Making in Responsible AI Development
This work addresses the problem of ethical AI development for tech firms and communities by proposing a community-based decision-making approach, though it is incremental as it builds on existing participatory methods.
The paper tackles the challenge of incorporating diverse expertise into responsible AI development by evaluating the Equitable AI Research Roundtable (EARR), a coalition that provided feedback on ethical and social harms through workshops, resulting in three principles for expanding expertise and fostering mutual learning in AI practices.
This paper reports on our initial evaluation of The Equitable AI Research Roundtable -- a coalition of experts in law, education, community engagement, social justice, and technology. EARR was created in collaboration among a large tech firm, nonprofits, NGO research institutions, and universities to provide critical research based perspectives and feedback on technology's emergent ethical and social harms. Through semi-structured workshops and discussions within the large tech firm, EARR has provided critical perspectives and feedback on how to conceptualize equity and vulnerability as they relate to AI technology. We outline three principles in practice of how EARR has operated thus far that are especially relevant to the concerns of the FAccT community: how EARR expands the scope of expertise in AI development, how it fosters opportunities for epistemic curiosity and responsibility, and that it creates a space for mutual learning. This paper serves as both an analysis and translation of lessons learned through this engagement approach, and the possibilities for future research.