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Workshop: XAI in Action: Past, Present, and Future Applications

Influence Based Approaches to Algorithmic Fairness: A Closer Look

Soumya Ghosh · Prasanna Sattigeri · Inkit Padhi · Manish Nagireddy · Jie Chen

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Sat 16 Dec 12:01 p.m. PST — 1 p.m. PST


In contemporary machine learning, there's a growing trend of utilizing ready-made pre-trained models. In real-world applications, it is essential that the pre-trained models are not just accurate but also demonstrate qualities like fairness. This paper takes a closer look at recently proposed approaches that re-weight the training data to edit a pre-trained model for group fairness. We offer perspectives that unify disparate weighting schemes from past studies and pave the way for new weighting strategies to address group fairness concerns.

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