Asking ‘Why’ in AI: Explainability of intelligent systems – perspectives and challenges

Asking ‘Why’ in AI: Explainability of intelligent systems – perspectives and challenges Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a resurgence in interest in explainability of artificial intelligence (AI) systems, reviving an area of research dating back to the 1970s. The aim of this article is to view current issues concerning ML‐based AI systems from the perspective of classical AI, showing that the fundamental problems are far from new, and arguing that elements of that earlier work offer routes to making progress towards explainable AI today. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Intelligent Systems in Accounting, Finance & Management Wiley

Asking ‘Why’ in AI: Explainability of intelligent systems – perspectives and challenges

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Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
Copyright © 2018 John Wiley & Sons, Ltd.
ISSN
1055-615X
eISSN
1099-1174
D.O.I.
10.1002/isaf.1422
Publisher site
See Article on Publisher Site

Abstract

Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a resurgence in interest in explainability of artificial intelligence (AI) systems, reviving an area of research dating back to the 1970s. The aim of this article is to view current issues concerning ML‐based AI systems from the perspective of classical AI, showing that the fundamental problems are far from new, and arguing that elements of that earlier work offer routes to making progress towards explainable AI today.

Journal

Intelligent Systems in Accounting, Finance & ManagementWiley

Published: Jan 1, 2018

Keywords: ; ; ;

References

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