A Method and Analysis to Elicit User-Reported Problems in Intelligent Everyday Applications

摘要

The complex nature of intelligent systems motivates work on supporting users during interaction, for example, through explanations. However, as of yet, there is little empirical evidence in regard to specific problems users face when applying such systems in everyday situations. This article contributes a novel method and analysis to investigate such problems as reported by users: We analysed 45,448 reviews of four apps on the Google Play Store (Facebook, Netflix, Google Maps, and Google Assistant) with sentiment analysis and topic modelling to reveal problems during interaction that can be attributed to the apps' algorithmic decision-making. We enriched this data with users' coping and support strategies through a follow-up online survey (N = 286). In particular, we found problems and strategies related to content, algorithm, user choice, and feedback. We discuss corresponding implications for designing user support, highlighting the importance of user control and explanations of output rather than processes.