Abstract
The concept of a public—a group of strangers drawn together through their mutual attention to a text—has historically been tied to the notion of human intentionality. The recent popularization of artificial intelligence (AI) large language models (such as ChatGPT) destabilizes this connection. When large language models generate text, they may inadvertently form stochastic publics—groups pulled together through the randomization of biased data patterns drawn from AI training material. This exploratory study draws on a three-phase dialogue with OpenAI's ChatGPT 4 to identify the risks of stochastic publics and suggest human-originated interventions grounded in feminist care ethics.
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