Rethinking Fairness: An Interdisciplinary Survey of Critiques of Hegemonic ML Fairness Approaches

Fairness: a survey

In this paper I provide an excursus, as complete as I could, of the most important theoretical and experimental works concerning fairness. The aim is twofold. First of all, I want to underline the importance of the role played by experimental economics in testing and improving models on this topic. Secondly, I want to mention some evidence that, even for fair-minded people, economic factors suc...

Analysing the Fairness of Fairness-aware Classifiers

Calders and Verwer’s two-naive-Bayes is one of fairness-aware classifiers, which classify objects while excluding the influence of a specific information. We analyze why this classifier achieves very high level of the fairness, and show that this is due to a decision rules and a model bias. Based on these findings, we develop methods that are grounded on rigid theory and are applicable to wider...

Fairness, Computable Fairness, and Randomness

An Axiomatic Theory of Fairness

The tradeoff between fairness and throughput has been widely observed in network analysis and protocol design. Despite many existing fairness metrics (from simple ones like Jain’s index to more complex ones like α-fair utility), the meaning of fairness is largely based on problemoriented interpretations and judgments, with no well-established framework. To tackle this challenging problem, we pr...

A queueing analysis of max-min fairness, proportional fairness and balanced fairness

We compare the performance of three usual allocations, namely max-min fairness, proportional fairness and balanced fairness, in a communication network whose resources are shared by a random number of data flows. The model consists of a network of processorsharing queues. The vector of service rates, which is constrained by some compact, convex capacity set representing the network resources, i...