Argumentation and Logic Programming for Explainable and Ethical AI


Roberta Calegari  /  Andrea Omicini, Giovanni Sartor, Roberta Calegari

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 to address some ethical concerns about AI.

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talk

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XAI.it 2020

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Torino

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25/11/2020

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