2 citations · 5 across the 9 of their papers we have counts for
7 papers · 1 filter
The Algorithmic Gaze of Image Quality Assessment: An Audit and Trace Ethnography of the LAION-Aesthetics Predictor
Jordan Taylor, William Agnew, Maarten Sap +2
Visual generative AI models are trained using a one-size-fits-all measure of aesthetic appeal. However, what is deemed "aesthetic" is inextricably linked to personal taste and cult…
Minion: A Technology Probe to Explore How Users Negotiate Harmful Value Conflicts with AI Companions
Xianzhe Fan, Qing Xiao, Xuhui Zhou +4
AI companions are designed to foster emotionally engaging interactions, yet users often encounter conflicts that feel frustrating or hurtful, such as discriminatory statements and…
Not Like Us, Hunty: Measuring Perceptions and Behavioral Effects of Minoritized Anthropomorphic Cues in LLMs
Jeffrey Basoah, Daniel Chechelnitsky, Tao Long +5
As large language models (LLMs) increasingly adapt and personalize to diverse sets of users, there is an increased risk of systems appropriating sociolects, i.e., language styles o…
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…
Rethinking Theory of Mind Benchmarks for LLMs: Towards A User-Centered Perspective
Qiaosi Wang, Xuhui Zhou, Maarten Sap +2
The last couple of years have witnessed emerging research that appropriates Theory-of-Mind (ToM) tasks designed for humans to benchmark LLM's ToM capabilities as an indication of L…
User-Driven Value Alignment: Understanding Users' Perceptions and Strategies for Addressing Biased and Discriminatory Statements in AI Companions
Xianzhe Fan, Qing Xiao, Xuhui Zhou +4
Large language model-based AI companions are increasingly viewed by users as friends or romantic partners, leading to deep emotional bonds. However, they can generate biased, discr…