Pearl: A Technology Probe for Machine-Assisted Reflection on Personal Data

Reflection on one’s personal data can be an effective tool for supporting wellbeing. However, current wellbeing reflection support tools tend to offer a one-size-fits-all approach, ignoring the diversity of people’s wellbeing goals and their agency in the self-reflection process. In this work, we identify an opportunity to help people work toward their wellbeing goals by empowering them to reflect on their data on their own terms. Through a formative study, we inform the design and implementation of Pearl, a workplace wellbeing reflection support tool that allows users to explore their personal data in relation to their wellbeing goal. Pearl is a calendar-based interactive machine teaching system that allows users to visualize data sources and tag regions of interest on their calendar. In return, the system provides insights about these tags that can be saved to a reflection journal. We used Pearl as a technology probe with 12 participants without data science expertise and found that all participants successfully gained insights into their workplace wellbeing. In our analysis, we discuss how Pearl’s capabilities facilitate insights, the role of machine assistance in the self-reflection process, and the data sources that participants found most insightful. We conclude with design dimensions for intelligent reflection support systems as inspiration for future work.