A database and website maintained by Issa Rice that tracks people, organizations, and products in the AI safety and alignment field.
A database and website maintained by Issa Rice that tracks people, organizations, and products in the AI safety and alignment field.
People
Updated 05/18/26creator and maintainer
Funding Details
Updated 05/18/26- Annual Budget
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- Current Runway
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Org Details
Updated 05/18/26AI Watch is a database-driven website created and maintained by Issa Rice, a freelance researcher based in Bothell, Washington. Development began on October 23, 2017, motivated by Issa's desire to address a recurring problem: people frequently cited figures like "around 60 AI safety researchers in the world" without providing an accompanying list. AI Watch was designed to fill that gap by providing a structured, queryable record of people and organizations in the AI safety and alignment communities. The site tracks people's positions at organizations over time, including full historical records showing when individuals joined and left various organizations. As of recent data, the database contains over 340 people with documented positions and over 170 organizations. It also has a companion project, Org Watch, which extends similar tracking to organizations beyond the AI safety domain. The project is primarily maintained by Issa Rice, with data contributions from Sebastian Sanchez, Amana Rice, and Vipul Naik. Partial funding has come from Vipul Naik (who sponsors much of Issa Rice's research work) and Mati Roy (who in July 2023 paid for time Issa had spent answering questions about AI Watch). All code and data are released under the CC0 1.0 Public Domain Dedication. The GitHub repository has accumulated over 3,400 commits since the project's inception. AI Watch is not a formal nonprofit or registered organization; it is an individual research resource.
Theory of Change
Updated 05/18/26AI Watch improves the AI safety ecosystem by providing a clear, accurate map of who is working in the field, at which organizations, and for how long. By making this information easily accessible, it helps researchers, funders, and newcomers understand the structure and scale of the community, identify gaps, track career movements, and make better-informed decisions about where to focus effort or funding. The theory of change is indirect: better field-level transparency supports more effective coordination and resource allocation within the AI safety community.
Grants Received– no grants recorded
Updated 05/18/26Projects– no linked projects
Updated 05/18/26Discussion
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