Why we should not mistake accuracy of medical AI for efficiency

In the medical literature, promising results regarding accuracy of medical AI are presented as claims for its potential to increase efficiency. This elision of concepts is misleading and incorrect. First, the promise that AI will reduce human workload rests on a too narrow assessment of what constitutes workload in the first place. Human...

Individual Fairness Guarantees for Neural Networks

We consider the problem of certifying the individual fairness (IF) of feed-forward neural networks (NNs). In particular, we work with the ϵ-δ-IF formulation, which, given a NN and a similarity metric learnt from data, requires that the output difference between any pair of ϵ-similar individuals is bounded by a maximum decision tolerance δ ≥ 0...