Investigating how technology reshapes consumer choice. Author of Uberland. Currently researching and reporting on dark patterns in healthcare.
I audit opaque systems through qualitative research. My work surfaces what’s broken, then translates between different disciplines, industries, and institutions needed to close the gap.
At Uber, I evaluated algorithmic workflows and product features for fairness, transparency, and trust. I also built and managed programs that surfaced driver and courier concerns across a global platform and channeled them into internal advocacy, product decisions, and policy changes. Before that, I spent seven years at the Data & Society Research Institute, conducting fieldwork across 25 cities that became the book Uberland. While gig economy companies promised that anyone with a smartphone app could become an entrepreneur, I found that ridehail drivers do have a boss — an algorithmic one.
I’m currently investigating dark patterns in healthcare registration—the design choices that steer patients into sharing more data than they realize, or consenting to things they haven’t meaningfully agreed to. This work appears in The Markup & CalMatters and STAT News.
A foundational ethnographic study of ridehail work across the gig economy in the U.S. and Canada, based on four years of fieldwork. Examines how algorithmic management structures information and power for workers on ridehail platforms.
Translated into Japanese, Chinese, Korean, and Spanish. Reviewed in leading academic journals. Covered in the New York Times, Wall Street Journal, and MIT Technology Review and international media.