Challenges of Explaining the Behavior of Black-Box AI Systems

Aleksandre Asatiani; Pekka Malo; Per Rådberg Nagbøl; Esko Penttinen; Tapani Rinta-Kahila; Antti Salovaara

doi:10.17705/2msqe.00037

Challenges of Explaining the Behavior of Black-Box AI Systems

Aleksandre Asatiani
, Pekka Malo
, Per Rådberg Nagbøl
, Esko Penttinen
, Tapani Rinta-Kahila
, Antti Salovaara

Research output: Journal Article or Conference Article in Journal › Journal article › Research › peer-review

Abstract

There are many examples of problems resulting from inscrutable AI systems, so there is a growing need to be able to explain how such systems produce their outputs. Draw- ing on a case study at the Danish Business Authority, we provide a framework and recommendations for addressing the many challenges of explaining the behavior of black-box AI systems. Our findings will enable organizations to successfully develop and deploy AI systems without causing legal or ethical problems.

Original language	English
Article number	7
Journal	M I S Quarterly Executive
Volume	19
Issue number	4
Pages (from-to)	259-278
ISSN	1540-1960
DOIs	https://doi.org/10.17705/2msqe.00037
Publication status	Published - 1 Dec 2020

Keywords

Artificial intelligence
Explainability
Envelopment

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10.17705/2msqe.00037

Challenges of Explaining the Behavior of Black-Box AI SystemsAccepted author manuscript, 2.27 MB

https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1488&context=misqe

Cite this

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AU - Asatiani, Aleksandre

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AU - Nagbøl, Per Rådberg

AU - Penttinen, Esko

AU - Rinta-Kahila, Tapani

AU - Salovaara, Antti

PY - 2020/12/1

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N2 - There are many examples of problems resulting from inscrutable AI systems, so there is a growing need to be able to explain how such systems produce their outputs. Draw- ing on a case study at the Danish Business Authority, we provide a framework and recommendations for addressing the many challenges of explaining the behavior of black-box AI systems. Our findings will enable organizations to successfully develop and deploy AI systems without causing legal or ethical problems.

AB - There are many examples of problems resulting from inscrutable AI systems, so there is a growing need to be able to explain how such systems produce their outputs. Draw- ing on a case study at the Danish Business Authority, we provide a framework and recommendations for addressing the many challenges of explaining the behavior of black-box AI systems. Our findings will enable organizations to successfully develop and deploy AI systems without causing legal or ethical problems.

KW - Artificial intelligence

KW - Explainability

KW - Envelopment

KW - Artificial intelligence

KW - Explainability

KW - Envelopment

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M1 - 7

ER -

Challenges of Explaining the Behavior of Black-Box AI Systems

Abstract

Keywords

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