Roberta Calegari, Andrea Omicini, Giovanni Sartor
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 |
- 19th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2020) — 24/11/2020–27/11/2020