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Opening the Software Engineering Toolbox for the Assessment of Trustworthy AI

Abstract

Trustworthiness is a central requirement for the acceptance and success of human-centered artificial intelligence (AI). To deem an AI system as trustworthy, it is crucial to assess its behaviour and characteristics against a gold standard of Trustworthy AI, consisting of guidelines, requirements, or only expectations. While AI systems are highly complex, their implementations are still based on software. The software engineering community has a long established toolbox for the assessment of software systems, especially in the context of software testing. In this paper, we argue for the application of software engineering and testing practices for the assessment of trustworthy AI. We make the connection between the seven key requirements as defined by the European Commission’s AI high-level expert group and established procedures from software engineering and raise questions for future work.
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Category

Academic article

Language

English

Author(s)

  • Mohit Kumar Ahuja
  • Belaid Mohamed-Bachir
  • Pierre Bernabé
  • Collet Mathieu
  • Gotlieb Arnaud
  • Lal Chhagan
  • Marijan Dusica
  • Sagar Sen
  • Sharif Aizaz
  • Spieker Helge

Affiliation

  • SINTEF Digital / Sustainable Communication Technologies

Year

2020

Published in

CEUR Workshop Proceedings

Volume

2659

Page(s)

67 - 70

External resources

View this publication at Norwegian Research Information Repository