Attribution-Scores and Causal Counterfactuals as Explanations in Artificial Intelligence
Artificial Intelligence
2023-03-24 v2 Databases
Machine Learning
Abstract
In this expository article we highlight the relevance of explanations for artificial intelligence, in general, and for the newer developments in {\em explainable AI}, referring to origins and connections of and among different approaches. We describe in simple terms, explanations in data management and machine learning that are based on attribution-scores, and counterfactuals as found in the area of causality. We elaborate on the importance of logical reasoning when dealing with counterfactuals, and their use for score computation.
Keywords
Cite
@article{arxiv.2303.02829,
title = {Attribution-Scores and Causal Counterfactuals as Explanations in Artificial Intelligence},
author = {Leopoldo Bertossi},
journal= {arXiv preprint arXiv:2303.02829},
year = {2023}
}
Comments
Submitted as chapter contribution. In this version some additional comments were added, and some wrong equation references corrected