This paper presents a user-centered approach to translating techniques and insights from AI explainability research to developing effective explanations of complex issues in other fields, on the example of COVID-19. We show how the problem of AI explainability and the explainability problem in the COVID-19 pandemic are related: as two specific instances of a more general explainability problem, occurring when people face in-transparent, complex systems and processes whose functioning is not readily observable and understandable to them (“black boxes”). Accordingly, we discuss how we applied an interdisciplinary, user-centered approach based on Design Thinking to develop a prototype of a user-centered explanation for a complex issue regarding people’s perception of COVID-19 vaccine development. The developed prototype demonstrates how AI explainability techniques can be adapted and integrated with methods from communication science, visualization and HCI to be applied to this context. We also discuss results from a first evaluation in a user study with 88 participants and outline future work. The results indicate that it is possible to effectively apply methods and insights from explainable AI to explainability problems in other fields and support the suitability of our conceptual framework to inform that. In addition, we show how the lessons learned in the process provide new insights for informing further work on user-centered approaches to explainable AI itself.

The number of hours spent using mobile phones has been increasing over the years and is especially visible in younger generations. Interestingly, the body of research on this emerging topic is mainly based on self-assessment measures of screen time. There are few studies on mobile phones in Croatia. Therefore the aim of this study was to examine how many hours Croatian high school students spend on mobile phones and see if there is a discrepancy in self-estimates of high-school students’ screen time compared to the objective measure obtained through an application for screen time tracking. Moreover, gender differences in screen time were analysed, as well as differences between different levels of students’ academic achievement. This study included 156 high-school pupils aged 14 to 18. They were asked to fill out a questionnaire about their smartphone usage habits and attitudes, while their smartphone usage was tracked for one week using the Screen Time application. The analysis was done based on data collected from 130 participants. Most of the students reported that they spend 2 to 4 hours a day using their smartphones, while their actual screen time is, on average, 5 hours and 29 minutes per day. 64.6% of the students underestimated the time spent on their smartphones. Moreover, most of the students believe that it is recommended to spend 1-2 hours a day using a smartphone, while addiction is formed when a phone is used for 2-4 hours a day. There were no significant differences in screen time between students with different school achievements, as well as between male and female students. However, when gender differences were examined for different categories of mobile phone applications, the results showed that female students spent more time on social media applications while male students spent more time using multimedia applications.