LAION-Aesthetics Predictor reinforces Western and male biases by preferentially selecting images associated with women and realistic Western/Japanese art while excluding men, LGBTQ+ references, and other styles.
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Case studies with blind UK residents and people from Kerala and Tamil Nadu demonstrate that community input at the systematization stage produces culturally grounded definitions of appropriateness for text-to-image model outputs.
citing papers explorer
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The Algorithmic Gaze of Image Quality Assessment: An Audit and Trace Ethnography of the LAION-Aesthetics Predictor
LAION-Aesthetics Predictor reinforces Western and male biases by preferentially selecting images associated with women and realistic Western/Japanese art while excluding men, LGBTQ+ references, and other styles.
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Evaluating AI-Generated Images of Cultural Artifacts with Community-Informed Rubrics
Case studies with blind UK residents and people from Kerala and Tamil Nadu demonstrate that community input at the systematization stage produces culturally grounded definitions of appropriateness for text-to-image model outputs.