“Beneath this veneer of ‘oh, AI is the future, and we have all these sparkly, nice things’, both AI academia and AI industry are fundamentally conservative,” says multilingual_s.
Maria Skoularidou has worked to improve accessibility at a major artificial-intelligence conference.PhD candidate in biostatistics at the University of Cambridge, UK, and founder and chair of {Dis}Ability in AI.in 2018, because I realized that disabled people weren’t represented at conferences and it didn’t feel right. I wanted to start such a movement so that conferences could be inclusive and accessible, and disabled people such as me could attend them.
Since 2019, {Dis}Ability in AI has helped facilitate better accessibility at NeurIPS. There were interpreters, and closed captioning for people with hearing problems. There were volunteer escorts for people with impaired mobility or vision who requested help. There were hotline counsellors and silent rooms because large conferences can be overwhelming.
Most people doing the work in Queer in AI are graduate students, including me. You can ask, “Why isn’t it the senior professor? Why isn’t it the vice-president of whatever?” The lack of senior members limits our operation and what we have the resources to advocate for. In large part because of my work with Queer in AI, I switched from being a roboticist to being an ethicist. How queer peoples’ data are used, collected and misused is a big concern. Another concern is that machine learning is fundamentally about categorizing items and people and predicting outcomes on the basis of the past. These things are antithetical to the notion of queerness, where identity is fluid and often changes in important and big ways, and frequently throughout life.
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