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Found 5 papers, 2 papers with code
Fairness in Algorithmic Recourse Through the Lens of Substantive Equality of Opportunity
Building upon an agent-based framework for simulating recourse, this paper demonstrates how much effort is needed to overcome disparities in initial circumstances.
Setting the Right Expectations: Algorithmic Recourse Over Time
The bulk of the literature on algorithmic recourse to-date focuses primarily on how to provide recourse to a single individual, overlooking a critical element: the effects of a continuously changing context.
Counterfactual Explanations for Graph Classification Through the Lenses of Density
Counterfactual examples have emerged as an effective approach to produce simple and understandable post-hoc explanations.
Large scale analysis of gender bias and sexism in song lyrics
We employ Natural Language Processing techniques to analyse 377808 English song lyrics from the "Two Million Song Database" corpus, focusing on the expression of sexism across five decades (1960-2010) and the measurement of gender biases.
Counterfactual Graphs for Explainable Classification of Brain Networks
In this paper we propose \emph{counterfactual graphs} as a way to produce local post-hoc explanations of any black-box graph classifier.
