Samenvatting

Although ISO25000 claimed in 2011 that “the characteristics defined … are relevant to all software products and computer systems”, by now ISO is working on an specific SQuaRE version for AI systems. While waiting for that update I took (grey) literature on quality of AI systems as a starting point to list a number of important extension/changes that are needed to the existing quality model. The challenge is that many papers and posts do not phrase there discussion in terms of “quality of AI systems”, see the examples above. Instead, they discuss one or more aspect that are important for AI systems or different for AI systems. The discussion is often phrased from a user perspective and not from a technical or engineering perspective. In this blog post I summarize my findings in the form of an extended ISO25000 quality model. This should help AI engineering projects to define quality requirements for their AI systems. The AI quality model covers all possibly relevant aspects for AI systems. It is up to the team to define which aspects are relevant for the current AI systems and how to measure or test them. The AI quality model also serves as a standard dictionary for discussing relevant properties of trustworthy AI systems, also with non-technical stakeholders.