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

Publikation: Artikel i tidsskrift og konference artikel i tidsskrift › Tidsskriftartikel › Forskning › 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.

Originalsprog	Engelsk
Artikelnummer	7
Tidsskrift	M I S Quarterly Executive
Vol/bind	19
Udgave nummer	4
Sider (fra-til)	259-278
ISSN	1540-1960
DOI	https://doi.org/10.17705/2msqe.00037
Status	Udgivet - 1 dec. 2020

Emneord

Artificial intelligence
Explainability
Envelopment

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10.17705/2msqe.00037

Challenges of Explaining the Behavior of Black-Box AI SystemsAccepteret manuskript, 2,27 MB

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

Citationsformater

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AU - Rinta-Kahila, Tapani

AU - Salovaara, Antti

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Challenges of Explaining the Behavior of Black-Box AI Systems

Abstract

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