Explaining data-driven personas to end users

Enabled by digital user data and algorithms, persona user interfaces (UI) are moving to digital formats. However, algorithms and user data, if left unexplained to end users, might leave data-driven personas (DDPs) difficult to understand and trust. This is because the data and the way it is processed are complex and not self-evident, requiring explanations of the DDP information and UIs. In this research, we provide a proof of concept for adding transparency to DDP using a real system UI. Furthermore, we demonstrate ways to add breakdown information that can help alleviate user stereotyping associated with the use of personas.