Queer In AI: A Case Study in Community-Led Participatory AI
Abstract
We present Queer in AI as a case study for community-led participatory design in AI. We examine how participatory design and intersectional tenets started and shaped this community's programs over the years. We discuss different challenges that emerged in the process, look at ways this organization has fallen short of operationalizing participatory and intersectional principles, and then assess the organization's impact. Queer in AI provides important lessons and insights for practitioners and theorists of participatory methods broadly through its rejection of hierarchy in favor of decentralization, success at building aid and programs by and for the queer community, and effort to change actors and institutions outside of the queer community. Finally, we theorize how communities like Queer in AI contribute to the participatory design in AI more broadly by fostering cultures of participation in AI, welcoming and empowering marginalized participants, critiquing poor or exploitative participatory practices, and bringing participation to institutions outside of individual research projects. Queer in AI's work serves as a case study of grassroots activism and participatory methods within AI, demonstrating the potential of community-led participatory methods and intersectional praxis, while also providing challenges, case studies, and nuanced insights to researchers developing and using participatory methods.
Keywords
Cite
@article{arxiv.2303.16972,
title = {Queer In AI: A Case Study in Community-Led Participatory AI},
author = {Organizers Of QueerInAI and : and Anaelia Ovalle and Arjun Subramonian and Ashwin Singh and Claas Voelcker and Danica J. Sutherland and Davide Locatelli and Eva Breznik and Filip Klubička and Hang Yuan and Hetvi J and Huan Zhang and Jaidev Shriram and Kruno Lehman and Luca Soldaini and Maarten Sap and Marc Peter Deisenroth and Maria Leonor Pacheco and Maria Ryskina and Martin Mundt and Milind Agarwal and Nyx McLean and Pan Xu and A Pranav and Raj Korpan and Ruchira Ray and Sarah Mathew and Sarthak Arora and ST John and Tanvi Anand and Vishakha Agrawal and William Agnew and Yanan Long and Zijie J. Wang and Zeerak Talat and Avijit Ghosh and Nathaniel Dennler and Michael Noseworthy and Sharvani Jha and Emi Baylor and Aditya Joshi and Natalia Y. Bilenko and Andrew McNamara and Raphael Gontijo-Lopes and Alex Markham and Evyn Dǒng and Jackie Kay and Manu Saraswat and Nikhil Vytla and Luke Stark},
journal= {arXiv preprint arXiv:2303.16972},
year = {2023}
}
Comments
To appear at FAccT 2023