The Equitable AI Research Roundtable (EARR): Towards Community-Based
Decision Making in Responsible AI Development
- URL: http://arxiv.org/abs/2303.08177v1
- Date: Tue, 14 Mar 2023 18:57:20 GMT
- Title: The Equitable AI Research Roundtable (EARR): Towards Community-Based
Decision Making in Responsible AI Development
- Authors: Jamila Smith-Loud, Andrew Smart, Darlene Neal, Amber Ebinama, Eric
Corbett, Paul Nicholas, Qazi Rashid, Anne Peckham, Sarah Murphy-Gray, Nicole
Morris, Elisha Smith Arrillaga, Nicole-Marie Cotton, Emnet Almedom, Olivia
Araiza, Eliza McCullough, Abbie Langston, Christopher Nellum
- Abstract summary: The paper reports on our initial evaluation of The Equitable AI Research Roundtable.
EARR was created in collaboration among a large tech firm, nonprofits, NGO research institutions, and universities.
We outline three principles in practice of how EARR has operated thus far that are especially relevant to the concerns of the FAccT community.
- Score: 4.1986677342209004
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 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.
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