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Found 2 papers, 1 papers with code
A Brief Tutorial on Sample Size Calculations for Fairness Audits
In fairness audits, a standard objective is to detect whether a given algorithm performs substantially differently between subgroups.
Designing monitoring strategies for deployed machine learning algorithms: navigating performativity through a causal lens
When an ML algorithm interacts with its environment, the algorithm can affect the data-generating mechanism and be a major source of bias when evaluating its standalone performance, an issue known as performativity.
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