We received nearly 1,000 applications across 113 countries. There were far more than 10 qualified teams, but a joint committee of OpenAI employees and external experts in democratic governance selected the final 10 teams to span a set of diverse backgrounds and approaches: the chosen teams have members from 12 different countries and their expertise spans various fields, including law, journalism, peace-building, machine learning, and social science research.

During the program, teams received hands-on support and guidance. To facilitate collaboration, teams were encouraged to describe and document their processes in a structured way (via “process cards” and “run reports”). This enabled faster iteration and easier identification of opportunities to integrate with other teams’ prototypes. Additionally, OpenAI facilitated a special Demo Day⁠(opens in a new window) in September for the teams to showcase their concepts to one another, OpenAI staff, and researchers from other AI labs and academia. 

The projects spanned different aspects of participatory engagement, such as novel video deliberation interfaces, platforms for crowdsourced audits of AI models, mathematical formulations of representation guarantees, and approaches to map beliefs to dimensions that can be used to fine-tune model behavior. Notably, across nearly all projects, AI itself played a useful role as a part of the processes⁠(opens in a new window) in the form of customized chat interfaces, voice-to-text transcription, data synthesis, and more. 

Today, along with lessons learned, we share the code that teams created for this grant program⁠(opens in a new window), and present brief summaries of the work accomplished by each of the ten teams: