Explain to whom? Putting the User in the Center of Explainable AI

Abstract : The ability to explain actions and decisions is often regarded as a basic ingredient of cognitive systems. But when researchers propose methods for making AI systems understandable, users are usually not involved or even mentioned. However, the purpose is to make people willing to accept the decision of a machine or to be better able to interact with it. Therefore, I argue that the evaluation of explanations must involve some form of user testing.
Type de document :
Communication dans un congrès
Proceedings of the First International Workshop on Comprehensibility and Explanation in AI and ML 2017 co-located with 16th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2017), 2017, Bari, Italy
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01845135
Contributeur : Alexandra Kirsch <>
Soumis le : vendredi 20 juillet 2018 - 10:41:59
Dernière modification le : jeudi 2 août 2018 - 09:34:31
Document(s) archivé(s) le : dimanche 21 octobre 2018 - 15:47:27

Fichier

kirsch17explain-preprint.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01845135, version 1

Citation

Alexandra Kirsch. Explain to whom? Putting the User in the Center of Explainable AI. Proceedings of the First International Workshop on Comprehensibility and Explanation in AI and ML 2017 co-located with 16th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2017), 2017, Bari, Italy. 〈hal-01845135〉

Partager

Métriques

Consultations de la notice

34

Téléchargements de fichiers

41