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Enhancing Fairness Through Aleatoric Uncertainty
Background In recent years, advancements in machine learning have revolutionized various domains, but concerns about bias and unfairness in automated decision-making systems have gained significant attention. One of the causes of unfairness in AI systems is the reliance on training data. Aleatoric uncertainty refers to the inherent randomness or variability...
Published: 8/7/2024   |   Inventor(s): Anique Tahir, Lu Cheng, Huan Liu
Keywords(s): Artificial Intelligence, Machine Learning
Category(s): Physical Science, Computing & Information Technology, Intelligence & Security