Auditbot
Auditing Algorithmic Bias
User Research, Feature Design
We approached the issue of auditing algorithmic bias through social proof to motivate and improve confidence of end-users in the auditing process. Through our research, we discovered 3 overarching insights: end-user’s desire for simplicity, transparency, and anonymity.
We proposed a holistic solution that integrates a chatbot into Instagram’s user interface—AuditBot—to help social media end-users assess and audit potentially biased posts, enabling the co-creation of value between Instagram and its end-users.
October – December 2021.
Role: User Researcher.
Team: Martina Tan (PM), John Jongyeon Chae, Priya Jain, Yumi Sato, Professor Raelin Musuraca.
Tools: Figma, Generative Think-Aloud, Speed Dating, Affinity Maps.