2 citations · 4 across the 4 of their papers we have counts for
4 papers
Manipulation Risks in Explainable AI: The Implications of the Disagreement Problem
Sofie Goethals, David Martens, Theodoros Evgeniou
Artificial Intelligence (AI) systems are increasingly used in high-stakes domains of our life, increasing the need to explain these decisions and to make sure that they are aligned…
Calculating and Visualizing Counterfactual Feature Importance Values
Bjorge Meulemeester, Raphael Mazzine Barbosa De Oliveira, David Martens
Despite the success of complex machine learning algorithms, mostly justified by an outstanding performance in prediction tasks, their inherent opaque nature still represents a chal…
Unveiling the Potential of Counterfactuals Explanations in Employability
Raphael Mazzine Barbosa de Oliveira, Sofie Goethals, Dieter Brughmans +1
In eXplainable Artificial Intelligence (XAI), counterfactual explanations are known to give simple, short, and comprehensible justifications for complex model decisions. However, w…
Disagreement amongst counterfactual explanations: How transparency can be deceptive
Dieter Brughmans, Lissa Melis, David Martens
Counterfactual explanations are increasingly used as an Explainable Artificial Intelligence (XAI) technique to provide stakeholders of complex machine learning algorithms with expl…