On The Role of Knowledge Graphs in
               Explainable AI

                                  Freddy Lecue

CortAIx (Centre of Research & Technology in Artificial Intelligence eXpertise)
                             Montréal, Kanada
                          freddy.lecue@inria.fr



    Abstract. The current hype of Artificial Intelligence (AI) mostly refers
    to the success of machine learning and its sub-domain of deep learning.
    However, AI is also about other areas, such as Knowledge Representation
    and Reasoning, or Distributed AI, i.e., areas that need to be combined
    to reach the level of intelligence initially envisioned in the 1950s. Ex-
    plainable AI (XAI) now refers to the core backup for industry to apply
    AI in products at scale, particularly for industries operating with critical
    systems. XAI can not only be reviewed from a Machine Learning per-
    spective, but also from the other AI research areas, such as AI Planning
    or Constraint Satisfaction and Search. We expose the XAI challenges of
    AI fields, their existing approaches, limitations and the great opportuni-
    ties for Semantic Web Technologies and Knowledge Graphs to push the
    boundaries of XAI further.




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mons License Attribution 4.0 International (CC BY 4.0).