Opening the Software Engineering Toolbox for the Assessment of Trustworthy AI

July 14, 2020 Β· Declared Dead Β· πŸ› NeHuAI@ECAI

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Authors Mohit Kumar Ahuja, Mohamed-Bachir Belaid, Pierre BernabΓ©, Mathieu Collet, Arnaud Gotlieb, Chhagan Lal, Dusica Marijan, Sagar Sen, Aizaz Sharif, Helge Spieker arXiv ID 2007.07768 Category cs.SE: Software Engineering Cross-listed cs.AI, cs.CY Citations 12 Venue NeHuAI@ECAI Last Checked 3 months ago
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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