WAO helps workers and allies investigate black-box algorithmic systems
We're crowdsourcing the data necessary for meaningful, scientific audits
Our group is building tools and support for workers and allies
We're building tools to investigate black-box algorithmic systems
FairFare crowdsources fare data from drivers to help stakeholders understand the ride-hail industry. Drivers securely link job data to analyze fare trends in multiple states.
Learn moreThe WAO is a crowdsourced auditing collaboration.
Investigating black-box platform algorithms, such as those used by Uber and DoorDash, faces major challenges in accessing the data necessary for a meaningful audit. To solve this, we're developing tools and support for workers and allies to crowdsource data and investigate the black-box algorithmic systems behind the platforms that determine pay, schedule, and more, in the platform economy and beyond. We launched the WAO in 2022. We are currently a nonprofit initiative with funding from the Mozilla Tech Fund 2023 "Auditing AI" cohort.
Abani Ahmed, Christine Ao, Dana Calacci, Felix Chen, Clayton, Samantha Dalal, Ananya Gollakota, Amado Krsul, Varun Mani, Caroline McLaughlin, Andrés Monroy-Hernández, Ryan Oet, Varun Rao, Cindy Tong
Eesha Agarwal, Youjean Cho, Cathy Di, Mihir Kshirsagar, Amna Liaqat, Eduardo Moreno, Serhiy Ozhbiko, Kok-Wei Pua, Andrew Schwartz, Satya Shodhaka, Danny Spitzberg, Tobey Switzer
Stay up to date on our research, tools, and worker-led audits.
We help workers and allies audit platform algorithms and AI