Explainable and Ethical AI: A Perspective on Argumentation and Logic Programming

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

Journals & Series

Events

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

Projects

  • AI4EU — A European AI On Demand Platform and Ecosystem (01/01/2019–31/12/2021)

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Publication

— status

published

— sort

paper in proceedings

who

— authors

— editors

Matteo Baldoni    Stefania Bandini

where & when

— publication date

2021

— volume

AIxIA 2020 – Advances in Artificial Intelligence

— series

Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence

— volume no.

12414

— chapter

2

— pages

19–36

— number of pages

18

URL

identifiers

— IRIS

11585/838789

— Google Scholar

13475146938124131264

— WoS / ISI

000886994000002

ISBN & ISSN

— print ISSN

0302-9743

— electronic ISSN

1611-3349

— print ISBN

978-3-030-77090-7

— electronic ISBN

978-3-030-77091-4

files
Open Access PDF

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