Add to ORKGInternational audienceExplanations do not affect human accuracy on an e-sport prediction task, even with a multi-explanation system. The benefits of XAI might be found regarding people's perception of difficulty and cognitive preferences.L'ajout d'explication dans à notre interface pour le pronostic de victoire dans League of Legends ne semble pas affecter la justesse de nos participants, même en les combinant.Le bénéfice apporté par l'explication doit se situer à un angle plus subjectif : l'utilisation de l'XAI se fait selon des préférences individuelles et une difficulté perçue localement
The rising popularity of explainable artificial intelligence (XAI) to understand high-performing bla...
Many of the successful modern machine learning approaches can be described as ``black box'' systems;...
Cette thèse se place dans le domaine de l’IA eXplicable (XAI) centrée sur l’humain, et plus particul...
International audienceEXplainable AI (XAI) offers a wide range of algorithmic solutions to the probl...
International audienceEXplainable AI (XAI) was created to address the issue of Machine Learning's la...
International audienceRecent advances in eXplainable Artificial Intelligence (XAI) led to many diffe...
This paper explores the interplay of feature-based explainable AI (XAI) tech- niques, information pr...
Cette thèse porte sur le domaine du XAI (explicabilité de l'IA), et plus particulièrement sur le par...
Introduction: Many Explainable AI (XAI) systems provide explanations that are just clues or hints ab...
International audienceThis paper provides empirical concerns about post-hoc explanations of black-bo...
Explainable AI (XAI) is a research field dedicated to formulating avenues of breaching the black box...
Artificial Intelligence is increasingly driven by powerful but often opaque machine learning algorit...
Artificial intelligence (AI) and machine learning (ML) have recently been radically improved and are...
Many of the successful modern machine learning approaches can be described as ``black box'' systems;...
In explainable artificial intelligence (XAI), researchers try to alleviate the intransparency of hig...
The rising popularity of explainable artificial intelligence (XAI) to understand high-performing bla...
Many of the successful modern machine learning approaches can be described as ``black box'' systems;...
Cette thèse se place dans le domaine de l’IA eXplicable (XAI) centrée sur l’humain, et plus particul...
International audienceEXplainable AI (XAI) offers a wide range of algorithmic solutions to the probl...
International audienceEXplainable AI (XAI) was created to address the issue of Machine Learning's la...
International audienceRecent advances in eXplainable Artificial Intelligence (XAI) led to many diffe...
This paper explores the interplay of feature-based explainable AI (XAI) tech- niques, information pr...
Cette thèse porte sur le domaine du XAI (explicabilité de l'IA), et plus particulièrement sur le par...
Introduction: Many Explainable AI (XAI) systems provide explanations that are just clues or hints ab...
International audienceThis paper provides empirical concerns about post-hoc explanations of black-bo...
Explainable AI (XAI) is a research field dedicated to formulating avenues of breaching the black box...
Artificial Intelligence is increasingly driven by powerful but often opaque machine learning algorit...
Artificial intelligence (AI) and machine learning (ML) have recently been radically improved and are...
Many of the successful modern machine learning approaches can be described as ``black box'' systems;...
In explainable artificial intelligence (XAI), researchers try to alleviate the intransparency of hig...
The rising popularity of explainable artificial intelligence (XAI) to understand high-performing bla...
Many of the successful modern machine learning approaches can be described as ``black box'' systems;...
Cette thèse se place dans le domaine de l’IA eXplicable (XAI) centrée sur l’humain, et plus particul...