International audienceAmong challenges for eXplainable Artificial Intelligence (XAI) is explanation generation. In this paper we put the stress on this issue by focusing on a semantic representation of the content of an explanation that could be common to any kind of XAI. We investigate knowledge representations, and discuss the benefits of conceptual graph structures for being a basis to represent explanations in AI
The interest in Explainable Artificial Intelligence (XAI) research is dramatically grown during the ...
The diffusion of artificial intelligence (AI) applications in organizations and society has fueled r...
Explainable Artificial Intelligence (XAI) is an aspiring research field addressing the problem that ...
International audienceAmong challenges for eXplainable Artificial Intelligence (XAI) is explanation ...
The rapid growth of research in explainable artificial intelligence (XAI) follows on two substantial...
There is broad agreement that Artificial Intelligence (AI) systems, particularly those using Machine...
An important subdomain in research on Human-Artificial Intelligence interaction is Explainable AI (X...
The most effective Artificial Intelligence (AI) systems exploit complex machine learning models to f...
International audienceEXplainable Artificial Intelligence (XAI) has recently become a very active do...
eXplainable AI focuses on generating explanations for the output of an AI algorithm to a user, usual...
In this work, we report the practical and theoretical aspects of Explainable AI (XAI) identified in ...
Doctor of PhilosophyDepartment of Computer SciencePascal HitzlerArtificial intelligence (AI)---inclu...
67 pages, 13 figures, under review in the Information Fusion journalIn the last years, Artificial In...
Explainable artificial intelligence (XAI) aims to help people understand black box algorithms, parti...
Artificial Intelligence is increasingly driven by powerful but often opaque machine learning algorit...
The interest in Explainable Artificial Intelligence (XAI) research is dramatically grown during the ...
The diffusion of artificial intelligence (AI) applications in organizations and society has fueled r...
Explainable Artificial Intelligence (XAI) is an aspiring research field addressing the problem that ...
International audienceAmong challenges for eXplainable Artificial Intelligence (XAI) is explanation ...
The rapid growth of research in explainable artificial intelligence (XAI) follows on two substantial...
There is broad agreement that Artificial Intelligence (AI) systems, particularly those using Machine...
An important subdomain in research on Human-Artificial Intelligence interaction is Explainable AI (X...
The most effective Artificial Intelligence (AI) systems exploit complex machine learning models to f...
International audienceEXplainable Artificial Intelligence (XAI) has recently become a very active do...
eXplainable AI focuses on generating explanations for the output of an AI algorithm to a user, usual...
In this work, we report the practical and theoretical aspects of Explainable AI (XAI) identified in ...
Doctor of PhilosophyDepartment of Computer SciencePascal HitzlerArtificial intelligence (AI)---inclu...
67 pages, 13 figures, under review in the Information Fusion journalIn the last years, Artificial In...
Explainable artificial intelligence (XAI) aims to help people understand black box algorithms, parti...
Artificial Intelligence is increasingly driven by powerful but often opaque machine learning algorit...
The interest in Explainable Artificial Intelligence (XAI) research is dramatically grown during the ...
The diffusion of artificial intelligence (AI) applications in organizations and society has fueled r...
Explainable Artificial Intelligence (XAI) is an aspiring research field addressing the problem that ...