A systematic mapping of quality models for AI systems, software and components - Ali, Mohamed Abdullahi; Ng, Keng Yap; Abd Ghani, Abdul Azim; Zulzalil, Hazura; Admodisastro, Novia Indriaty; Najafabadi, Amin Arab (MDPI, 2022)
Recently, there has been a significant increase in the number of Artificial Intelligence (AI) systems, software, and components. As a result, it is crucial to evaluate their quality. Quality models for AI have in fact been proposed, but there is a lack of Systematic Mapping Studies (SMS) for quality models in AI systems, software, and components. The goal of this paper is to understand, classify, and critically evaluate existing quality models for AI systems, software, and components. This study conducts an SMS to investigate quality models proposed by various authors in the past. The study only found quality models for AI systems and software. So far, the SMS has revealed no work on AI software component quality models. Finally, the limitations of the quality models and the implications for future research and development efforts are discussed.