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Found 7 papers, 3 papers with code
Towards Responsible AI in Banking: Addressing Bias for Fair Decision-Making
In an era characterized by the pervasive integration of artificial intelligence into decision-making processes across diverse industries, the demand for trust has never been more pronounced.
Evaluative Item-Contrastive Explanations in Rankings
The remarkable success of Artificial Intelligence in advancing automated decision-making is evident both in academia and industry.
Fair Enough? A map of the current limitations of the requirements to have "fair" algorithms
In the recent years, the raise in the usage and efficiency of Artificial Intelligence and, more in general, of Automated Decision-Making systems has brought with it an increasing and welcome awareness of the risks associated with such systems.
Investigating Bias with a Synthetic Data Generator: Empirical Evidence and Philosophical Interpretation
Machine learning applications are becoming increasingly pervasive in our society.
Counterfactual Explanations as Interventions in Latent Space
Explainable Artificial Intelligence (XAI) is a set of techniques that allows the understanding of both technical and non-technical aspects of Artificial Intelligence (AI) systems.
A Clarification of the Nuances in the Fairness Metrics Landscape
In recent years, the problem of addressing fairness in Machine Learning (ML) and automatic decision-making has attracted a lot of attention in the scientific communities dealing with Artificial Intelligence.
BeFair: Addressing Fairness in the Banking Sector
Algorithmic bias mitigation has been one of the most difficult conundrums for the data science community and Machine Learning (ML) experts.
