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.
Roberta Calegari, A.O. (2021). Explainable and Ethical AI: A Perspective on Argumentation and Logic Programming. Cham : Springer Nature [10.1007/978-3-030-77091-4_2].
Explainable and Ethical AI: A Perspective on Argumentation and Logic Programming
Roberta Calegari;Andrea Omicini;Giovanni Sartor
2021
Abstract
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.File | Dimensione | Formato | |
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