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How to measure the quality of Artificial Intelligence and robotics

Rik Marselis
August 15, 2018

This is the second in a series of papers focused on testing of Artificial Intelligence (AI). Our first paper “Testing of Artificial Intelligence; AI quality engineering skills – an introduction” discussed the skills needed for quality engineering (download this paper at: https://labs.sogeti.com/testing-of-artificial-intelligence/ OR  https://www.sogeti.com/explore/blog/testing-of-artificial-intelligence/ ) This second paper will provide the basis for measuring and ensuring the quality of intelligent machines and it will identify the quality characteristics and their testing in this fast-changing area of IT. We define software quality, introduce a generic taxonomy of quality characteristics, discuss the connections between these characteristics, and discuss future work leading to a quality-characteristics-based methodology for evaluating artificial intelligence based business processes. The key premise of this paper is that there is a need to extend the existing model of quality characteristics with new quality characteristics specifically for AI and robotics. For more information on this, download the paper here

About the author

Quality and Testing expert | Netherlands
Rik Marselis is principal quality consultant at Sogeti in the Netherlands. He has assisted many organizations in improving their IT-processes, in establishing their quality & testing approach, setting up their quality & test organization, and he acted as quality coach, qa-consultant, test manager and quality supervisor.

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