Explainable AI: a narrative review at the crossroad of Knowledge Discovery, Knowledge Representation and Representation Learning.

Ikram Chraibi Kaadoud (1, 2) , Lina Fahed (1, 2) , Philippe Lenca (1, 2)

1 IMT Atlantique - LUSSI - Département Logique des Usages, Sciences sociales et Sciences de l'Information
2 Lab-STICC_DECIDE - Equipe DECIDE

Presentation in the context of the Twelfth International Workshop Modelling and Reasoning in Context (MRC) @IJCAI 2021, of the following article : Chraibi Kaadoud, Ikram, Lina Fahed, and Philippe Lenca. "Explainable AI: a narrative review at the crossroad of Knowledge Discovery, Knowledge Representation and Representation Learning." Twelfth International Workshop Modelling and Reasoning in Context. 2021. ⟨hal-03343687⟩ Abstract: EXplainable Artificial Intelligence (XAI) has recently become a very active domain, mainly due to the extensive development of black-box models such as neural networks. Recent XAI objectives have been defined in the state-of-the-art, for which specific approaches have been proposed. Implicit links can be found between XAI and other domains, especially related to knowledge and neural networks. We here aim to highlight these implicit links. We present a narrative review of research works in two domains: (i) Knowledge domain with focus on Knowledge Discovery and Representation, and (ii) Representation Learning. We discuss the similarity and joining points between these domains and XAI. We conclude that, in order to make black-boxes more transparent, XAI approaches should be more inspired and take advantage of past and recent works in Knowledge and Representation Learning domains. Through this paper, we offer an entry point to the domain of XAI for both multidisciplinary researchers and specialists in AI, as well for AI knowledgeable users. Link to article: TBC Link to the workshop: http://mrc.kriwi.de/hccs2021/ Link to IJCAI conference: https://ijcai-21.org/ About the authors: Ikram Chraibi Kaadoud, XAI Postdoctoral Researcher: https://www.imt-atlantique.fr/en/person/ikram-chraibi-kaadoud Lina Fahed, Associate professor in Computer Science: https://www.imt-atlantique.fr/en/person/lina-fahed Philippe Lenca, Professor at IMT Atlantique, Head of Logics in Uses, Social Science and Information Science department.: https://www.imt-atlantique.fr/en/person/philippe-lenca Research team: DECIDE Team : https://www.labsticc.fr/en/teams/m-570-decide.htm LAB-STICC laboratory : https://www.labsticc.fr/en/index/ LUSSI Department : https://www.imt-atlantique.fr/fr/l-ecole/departements-d-enseignement-recherche/lussi

Mots clés: Explainable AI; XAI; Knowledge Discovery; Knowledge representation; Representation learning; Explainable AI

Domaines: Informatique; Réseau de neurones [cs.NE]; Intelligence artificielle [cs.AI]; Sciences cognitives

Ikram Chraibi Kaadoud, Lina Fahed, Philippe Lenca. Explainable AI: a narrative review at the crossroad of Knowledge Discovery, Knowledge Representation and Representation Learning.. 2021. ⟨hal-03345646⟩