Evolving Fairness in AI
Fairness in machine learning is not a static concept; it evolves over time as societal values shift. The reliance on labeled data presents challenges, as comprehensive labels are often lacking, leading to potential biases. Additionally, different cultures have distinct notions of fairness, complicating the adaptation of models to diverse contexts and expectations.In this clip
From this podcast
Machine Learning Street Talk (MLST)
#92 - SARA HOOKER - Fairness, Interpretability, Language Models
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