'IF WE LOOK AT IT FROM AN LGBT POINT OF VIEW…’ MOBILIZING LGBTQ+ STAKEHOLDERS TO QUEER ALGORITHMIC IMAGINARIES
DOI:
https://doi.org/10.5210/spir.v2023i0.13467Palabras clave:
algorithmic justice, algorithmic imaginaries, digital platforms, LGBTQ+ communities, queeringResumen
This paper presents the results of an exploratory study that examines the social implications that platform algorithms raise for LGBTQ+ communities. We share the preliminary results of our Phase 2 group interviews, which were conducted with Canadian social media managers of LGBTQ+ non-profit organizations and with Canada-based LGBTQ+ tech workers. Algorithmic controversies relating to LGBTQ+ communities identified in Phase 1 were used as prompts to elicit discussions among participants. In this paper, we pay close attention to how participants queered dominant algorithmic imaginaries. Our preliminary analysis highlights four main findings. First, participants questioned dominant discourses that depict AI technology as being inherently new, instead re-inscribing algorithmic controversies within a long-lasting history of gender and sexual oppression. Second, participants reconfigured the ideal-type user embedded in sociotechnical systems but also identified challenges with effecting sociotechnical change as LGBTQ+ stakeholders. Third, participants subverted the notion of algorithmic resistance by questioning whether effective technological resistance should rely on technological misuse or disuse. Fourth, participants translated algorithmic controversies via their positionality as LGBTQ+ stakeholders to move beyond purely technicist considerations. Finally, we highlight the importance of mobilizing stakeholders from marginalized communities to contest the dominant discourses through which society makes sense of AI technologies.Descargas
Publicado
2023-12-31
Cómo citar
Myles, . D. ., Chartrand, A., & Duguay, S. (2023). ’IF WE LOOK AT IT FROM AN LGBT POINT OF VIEW…’ MOBILIZING LGBTQ+ STAKEHOLDERS TO QUEER ALGORITHMIC IMAGINARIES. AoIR Selected Papers of Internet Research. https://doi.org/10.5210/spir.v2023i0.13467
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