Privacy is often perceived as an abstract concept by both internet users and software developers. When users are engaged in online activities, it is difficult for them to make informed decisions about their personal data due to the challenges they face in understanding and experiencing the privacy implications of their behaviors in advance. Similarly, many software developers lack the ability to comprehend how the data practices of their applications may impact user privacy and to implement proper data practices that conform to users’ privacy expectations. This project is tackling this problem by developing a new, empathy-based framework to enhance privacy education and design. The project team is using generative AI to create synthetic personas with AI-generated personal data. Using the personas, the team is designing, creating, and studying new interactive sandboxes and developer tools that allow individuals to empathize with these personas, leading to a more concrete and situated understanding of privacy. This understanding, in turn, fosters positive privacy-oriented behaviors among internet users and privacy-responsible software development practices among software developers. To enhance users’ privacy knowledge and developers’ privacy-responsible software development practices, the project is systematically studying the mechanisms and applications of empathy invocation in the context of privacy. The goal is to develop metrics, guidelines, and conceptual frameworks for