Data augmentation via diffusion model to enhance AI fairness

IntroductionAI fairness seeks to improve the transparency and explainability of AI systems by ensuring that their outcomes genuinely reflect the best interests of users. Data augmentation, which involves generating synthetic data from existing datasets, has gained significant attention as a solution...

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Bibliographic Details
Main Authors: Christina Hastings Blow, Lijun Qian, Camille Gibson, Pamela Obiomon, Xishuang Dong
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-03-01
Series:Frontiers in Artificial Intelligence
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Online Access:https://www.frontiersin.org/articles/10.3389/frai.2025.1530397/full
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