Argumentation and Logic Programming for Explainable and Ethical AI


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Roberta Calegari, Andrea Omicini, Giovanni Sartor

Cataldo Musto, Daniele Magazzeni, Salvatore Ruggieri, Giovanni Semeraro (eds.)
“XAI.it 2020 – Italian Workshop on Explainable Artificial Intelligence 2020”, pages 55-68
CEUR Workshop Proceedings (AI*IA Series) 2742
Sun SITE Central Europe, RWTH Aachen University
November 2020

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.

(keywords) explainable AI, ethical AI, argumentation, logic programming, abduction, probabilistic LP, inductive LP

Proceedings of the Italian Workshop on Explainable Artificial Intelligence co-located with 19th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2020)

Talks

Journals & Series

Events

  • 19th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2020) — 24/11/2020–27/11/2020

Publication

— authors

— editors

Cataldo Musto, Daniele Magazzeni, Salvatore Ruggieri, Giovanni Semeraro

— status

published

— sort

paper in proceedings

— publication date

November 2020

— volume

XAI.it 2020 – Italian Workshop on Explainable Artificial Intelligence 2020

— series

CEUR Workshop Proceedings / AI*IA Series

— volume

2742

— pages

55-68

URLs

original page

identifiers

— DBLP

conf/aiia/CalegariOS20

— IRIS

11585/780458

— Scopus

2-s2.0-85098916778

notes

— note

Proceedings of the Italian Workshop on Explainable Artificial Intelligence co-located with 19th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2020)

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