Abstract
In this paper, the factors of positive user experiences when using AI systems are investigated. For this purpose, a two-stage qualitative usability study was conducted for the OMA-ML platform as an example. OMA-ML is an AutoML platform that automates complex tasks in machine learning (ML) and generates ML pipelines. The usability of OMA-ML was measured against the ISO 9241-110:2020 standard in an expert evaluation. The vulnerabilities with the greatest impact on the application were prioritised and tested in a qualitative usability test. The results of the usability test are presented along with recommendations in a usability evaluation. This study aims to contribute to the understanding of the usability of AI systems and their impact on the experience of the different user groups. It found that special attention needs to be paid to those interaction principles that serve to build user trust towards the AI system. For this purpose, the interaction principles with the main design dimensions for interaction with AI systems were derived.
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