Cybertrust: From Explainable to Actionable and Interpretable Artificial Intelligence

被引：21

作者：

Linkov, Igor ^{[1
]}

Galaitsi, Stephanie ^{[1
]}

Trump, Benjamin D. ^{[1
]}

Keisler, Jeffrey M. ^{[2
]}

Kott, Alexander ^{[3
]}

机构：

[1] US Army Corps Engineers, Engineer Res & Dev Ctr, Concord, MA 01742 USA

[2] Univ Massachusetts, Dept Management Sci & Informat Syst, Boston, MA 02125 USA

[3] US Army Futures Command, Adelphi, MD USA

来源：

COMPUTER | 2020年 / 53卷 / 09期

关键词：

Decision making; Prediction algorithms; Cognition; Stakeholders; Machine learning; Heart;

D O I：

10.1109/MC.2020.2993623

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

We argue that artificial intelligence (AI) systems should be designed with features that build trust by bringing decision-analytic perspectives into AI. Actionable and interpretable AI will incorporate explicit quantifications and visualizations of user confidence in AI recommendations.

引用

页码：91 / 96

页数：6

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