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Monitoring Algorithmic Fairness under Partial Observations
Moreover, they can monitor only fairness properties that are specified as arithmetic expressions over the probabilities of different events.
Monitoring Algorithmic Fairness
While the frequentist monitors compute estimates that are objectively correct with respect to the ground truth, the Bayesian monitors compute estimates that are correct subject to a given prior belief about the system's model.
Runtime Monitoring of Dynamic Fairness Properties
Our goal is to build and deploy a monitor that will continuously observe a long sequence of events generated by the system in the wild, and will output, with each event, a verdict on how fair the system is at the current point in time.
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