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.

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.
AIxIA 2020 – Advances in Artificial Intelligence
19
36
Roberta Calegari, Andrea Omicini, Giovanni Sartor
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/838789
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