Matteo Baldoni, Stefania Bandini (eds.)
AIxIA 2020 – Advances in Artificial Intelligence, chapter 2, pages 19–36
Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence) 12414
Springer Nature
2021
In this paper we sketch a vision of explainability of intelligent systems as a logic approach suitable to be injected into and exploited by the system actors once integrated with sub-symbolic techniques. In particular, we show how argumentation could be combined with different extensions of logic programming – namely, abduction, inductive logic programming, and probabilistic logic programming – to address the issues of explainable AI as well as some ethical concerns about AI.
keywords
explainable AI, ethical AI, argumentation, logic programming, abduction, probabilistic LP, inductive LP
origin event
journal or series
Lecture Notes in Computer Science
(LNCS)
funding project
AI4EU — A European AI On Demand Platform and Ecosystem
(01/01/2019–31/12/2021)
CompuLaw — Computable Law
(01/11/2019–31/10/2025)
