Authors

Anaelia Ovalle, University of California, USA
Arjun Subramonian, University of California, USA
Ashwiin Singh, Queer in AI, India
Claas Voelcker, University of Toronto, Canada
Danica Sutherland, University of British Columbia, Canada
Davide Locatelli, Queer in AI, Spain
Eva Breznik, Uppsala University, Sweden
Felip Klubicka, Technological University Dublin, IrelandFollow
Hang Yuan, Queer in AI, United Kingdom
Hetvi J, Queen in AI, United Kingdom
Huan Zhang, Queer in AI, USA
Jaidev Shriram, University of California, USA
Kruno Lehman, Queen in AI, Switzerland
Luca Soldaini, Allen Institute for AI, USA
Maarten Sap, Carnegie Mellon University & Allen Institute for AI, USA
Marc Peter Deisenroth, University College London, United Kingdom
Maria Leonor Pacheco, University of Colorado, USA
Maria Ryskina, Queer in AI & MIT, USA
Martin Mundt, TU Darmstadt & Hessian, Germany
Melind Agarwal, George Mason University, USA
Nyx McLean, Rhodes University, South Africa
Pan Xu, Duke University, USA
A. Pranav, Queer in AI, Hong Kong
Raj Korpan, Iona University, USA
Ruchira Ray, Queer in AI, USA
Sarah Mathew, Georgia Institute of Technology, USA
Sarthak Arora, Queer in AI, India
S.T. John, Aalto University, Finland
Tanvi Anand, Queer in AI, USA
Vishakha Agrawal, Queer in AI, India
William Agnew, University of Washington, USA
Yanan Long, University of Chicago, USA
Zijie J. Wang, Georgia Tech, USA
Zeerak Talat, Queer in AI, Canada
Avijit Ghosh, Northeastern University, USA
Nathaniel Dennler, Queer in AI, USA
Michael Noseworthy, Queer in AI & MIT, USA
Sharvani Jha, Queer in AI, USA
Emi Baylor, Queer in AI, Canada
Aditya Joshi, SEEK, Australia
Natalia Y. Bilenko, Queer in AI, USA
Andrew McNamara, Microsoft, Canada
Raphael Gontijo-Lopes, Queer in AI, United Kingdom
Alex Markham, Queer in AI, Sweden
Evyn Dong, Queer in AI, USA
Jackie Kay, Queer in AI, United Kingdom
Manu Saraswat, Queer in AI, Canada
Nikhil Vytla, Queen in AI, USA
Luke Stark, Western University, Canada

Document Type

Conference Paper

Disciplines

1.2 COMPUTER AND INFORMATION SCIENCE, 5.9 OTHER SOCIAL SCIENCES

Publication Details

https://arxiv.org/abs/2303.16972

2023 ACM Conference on Fairness, Accountability, and Transparency, Hyatt Regency McCormick Place, Chicago,12th to 15th June 2023.

https://doi.org/10.1145/3593013.3594134

Abstract

Queerness and queer people face an uncertain future in the face of ever more widely deployed and invasive artificial intelligence (AI). These technologies have caused numerous harms to queer people, including privacy violations, censoring and downranking queer content, exposing queer people and spaces to harassment by making them hypervisible, deadnaming and outing queer people. More broadly, they have violated core tenets of queerness by classifying and controlling queer identities. In response to this, the queer community in AI has organized Queer in AI, a global, decentralized, volunteer-run grassroots organization that employs intersectional and community-led participatory design to build an inclusive and equitable AI future. In this paper, 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.

DOI

https://doi.org/10.1145/3593013.3594134

Creative Commons License

Creative Commons Attribution-Share Alike 4.0 International License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 International License.


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