Developing Responsible Algorithmic Curation Features in Social Media through Participatory Design

As social media services have adopted algorithmic curation in various features such as targeted advertisements and content and friend recommendations, the technology has also resulted in varied manipulations such as polarization and privacy invasion. In response, responsibility-based approaches emphasizing transparency and accountability have been advocated in previous studies for developing algorithmic curations. However, detailed guidelines for designing user interfaces that can enhance users' trust around algorithmic curation have yet to be specified. As a first step in developing the guidelines, we conducted participatory design sessions with 16 social media users where we invited them to discuss their experiences and needs around the manipulation issues, such as privacy protection and filter bubble, and to develop prototypes for the corresponding user interfaces based on their visions. We discuss in this paper how these prototypes and identified users’ needs can be incorporated into designing algorithmic curation features on social media, and offer design suggestions for future study.