On the Rationality of Explanations in Classification Algorithms

被引：3

作者：

Falomir, Zoe ^{[1
,2
]}

Costa, Vicent ^{[3
,4
]}

机构：

[1] Univ Jaume 1, ES Tecnol & Cincies Expt, Castellon De La Plana, Spain

[2] Bremen Spatial Cognit Ctr BSCC, Bremen, Germany

[3] Univ Santiago de Compostela, Ctr Singular Invest Tecnol Intelixentes CiTIUS, Santiago De Compostela, Spain

[4] CSIC, IIIA, Artificial Intelligence Res Inst, Barcelona, Spain

来源：

ARTIFICIAL INTELLIGENCE RESEARCH AND DEVELOPMENT | 2021年 / 339卷

关键词：

Rationality; rational explanation; explainable AI; classification algorithm; AI ethics; trustworthy AI; GENERATION;

D O I：

10.3233/FAIA210165

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper is a first step towards studying the rationality of explanations produced by up-to-date AI systems. Based on the thesis that designing rational explanations for accomplishing trustworthy AI is fundamental for ethics in AI, we study the rationality criteria that explanations in classification algorithms have to meet. In this way, we identify, define, and exemplify characteristic criteria of rational explanations in classification algorithms.

引用

页码：445 / 454

页数：10

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