Language both reflects and reinforces our ideas about gender — in gendered grammar, in what we call people, and in how AI systems learn from biased text. This session explored Judith Butler’s theory that language doesn’t merely describe gender identities but constitutes them, then moved to practical examples: from “you guys” as an unmarked plural to the challenges trans parents face when existing categories don’t fit. We also examined how gendered assumptions get encoded into AI systems.
Materials
Main
- Paper on gender identity and language (paper)
- TED Talk: gender bias in language (YouTube)
- The Allusionist podcast: trans parents and the language of parenthood — what happens when "mum" and "dad" don't fit (Spotify)
- Paper on "you guys" and gendered language — why our default plurals matter (paper · Sage)
Supplementary
- Judith Butler on language and gender performativity: selected text (article)
- HBR: four ways to address gender bias in AI (article · Harvard Business Review)
Session structure
- Intro: sharing pronouns
- Do you use pronouns in your introduction? What does it feel like to be asked?
- When did "pronoun sharing" become common in your world, and what drove it?
- Native language and grammatical gender
- Romance languages and the default masculine — what is lost when all groups become "guys"?
- What is gained when a language lacks grammatical gender?
- Language shapes gender — Judith Butler
- Performativity: language doesn't describe gender, it constitutes it
- Does calling something "women's work" make it so?
- Trans and queer experience of language
- The podcast on trans parents — navigating "mum," "dad," and what comes in between
- What happens when existing categories don't fit?
- "You guys" and everyday gendered language
- What do we normalise without noticing?
- Is policing language effective, or does it create backlash?
- Gender bias in AI
- How training data encodes gendered assumptions into language models
- Who is responsible — developers, companies, or all of us who use these systems?
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