Queer AI conversational chatbots are trained to embody the messiness of relationships, bodies, and identity, while also seeking to develop processes for working with AI that are fun, respectful, consensual, tender, pleasurable, and kind.
The first iteration of Queer AI (2018) is trained on 50,000+ conversational pairs derived from scripts in queer theatre. Authors featured in our dataset include Caryl Churchill, Jane Chambers, Harvey Fierstein, Jean Genet, Sarah Ruhl, Paula Vogel, and Oscar Wilde. The chatbot uses an RNN seq-to-seq algorithm developed by Google for machine translation.
The second iteration (2020) uses GPT-2, a large transformer-based language model with 1.5 billion parameters, trained on a dataset of 8 million web pages.
The project has grown to include A.I. generated zines, community workshops, and A.I. experiments for character development and world building. It also inspired this machine learning toolkit that centers the needs of communities interested in working with their own texts, archives, and “small data”.
Queer AI is a collaboration with Ben Lerchin.
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UX workshop and design sprint