6 papers
"I Just Don't Want My Work Being Fed Into The AI Blender": Queer Artists on Refusing and Resisting Generative AI
Jordan Taylor, Joel Mire, Alicia DeVrio +3
Art-making is a collective social activity through which queer people engage in political resistance, develop identities, archive queer memory, and form community. However, in rece…
Social Story Frames: Contextual Reasoning about Narrative Intent and Reception
Joel Mire, Maria Antoniak, Steven R. Wilson +4
Reading stories evokes rich interpretive, affective, and evaluative responses, such as inferences about narrative intent or judgments about characters. Yet, computational models of…
PluriHarms: Benchmarking the Full Spectrum of Human Judgments on AI Harm
Jing-Jing Li, Joel Mire, Eve Fleisig +4
Current AI safety frameworks, which often treat harmfulness as binary, lack the flexibility to handle borderline cases where humans meaningfully disagree. To build more pluralistic…
Where Do People Tell Stories Online? Story Detection Across Online Communities
Maria Antoniak, Joel Mire, Maarten Sap +2
Story detection in online communities is a challenging task as stories are scattered across communities and interwoven with non-storytelling spans within a single text. We address…
Un-Straightening Generative AI: How Queer Artists Surface and Challenge the Normativity of Generative AI Models
Jordan Taylor, Joel Mire, Franchesca Spektor +4
Queer people are often discussed as targets of bias, harm, or discrimination in research on generative AI. However, the specific ways that queer people engage with generative AI, a…
Rejected Dialects: Biases Against African American Language in Reward Models
Joel Mire, Zubin Trivadi Aysola, Daniel Chechelnitsky +3
Preference alignment via reward models helps build safe, helpful, and reliable large language models (LLMs). However, subjectivity in preference judgments and the lack of represent…