People
Updated 05/18/26Executive Director
Managing Director
Founder
Senior Associate
Interim Program Director, Peace and Security
Operations Manager
Program Director, Artificial Intelligence
Funding Details
Updated 05/18/26- Annual Budget
- $727,915
- Current Runway
- -
- Funding Goal
- -
- Funding Raised to Date
- -
Org Details
Updated 05/18/26The Effective Institutions Project (EIP) is a global working group of academics, philanthropic leaders, businesspeople, and policymakers dedicated to strengthening society's ability to tackle major global challenges by improving institutional decision-making. Founded in 2021 by Ian David Moss as the Improving Institutional Decision-Making Working Group, the organization rebranded and incorporated as a 501(c)(3) nonprofit in 2023 after initially operating under the fiscal sponsorship of the Nine Muses Foundation. EIP's work is built on the premise that leadership at important institutions frequently misjudges risks, makes choices based on political expediency, and fails to imagine wiser alternatives on issues ranging from pandemics to climate change to artificial intelligence. The organization identifies two key facets that determine the quality of an institution's decision-making: how altruistically motivated their decisions are and their technical competence. AI governance has been a core focus since EIP's founding and currently accounts for the majority of organizational resources. The team monitors national governments, major corporations, and multilateral bodies to identify actionable improvements in how these institutions approach AI development and deployment. EIP believes that many of the foundational laws, regulations, and norms governing AI will be forged in the coming years, creating an urgent window for intervention. Beyond AI governance, EIP works on institutional reform related to U.S. democracy, peace and security, and global health. The organization publishes research including landscape analyses of institutional improvement opportunities, primers on AI governance, and guides for philanthropic funders. It also operates the EIP Innovation Fund, a regranting vehicle that supports initiatives expected to improve institutional behavior. EIP has built a network spanning dozens of grantmaking foundations, philanthropic families, and civic leaders. The organization has received support from the William and Flora Hewlett Foundation, the David and Lucile Packard Foundation, Silicon Valley Community Foundation, Laidir Foundation, and the EA Infrastructure Fund, among others. Key advisors include leaders from Open Philanthropy, Ploughshares Fund, Metaculus, and Anthropic.
Theory of Change
Updated 05/18/26EIP believes that the quality of decisions made by the world's most important institutions -- governments, major corporations, and multilateral bodies -- has an outsized impact on global outcomes including existential risk. By researching which institutions matter most, identifying specific interventions that could improve their decision-making processes, building coalitions across different stakeholder groups (funders, researchers, policymakers), and mobilizing funding toward the most promising opportunities, EIP aims to shift institutional behavior toward outcomes that reduce catastrophic and existential risk. In the AI governance domain specifically, EIP works to ensure that the foundational laws, regulations, and norms being established now will lead to AI development that is safe, broadly beneficial, and aligned with human values. Their approach of educating and connecting major mainstream donors across AI funding silos is designed to increase the total volume and quality of philanthropic investment in AI governance.
Grants Received
Updated 05/18/26Projects
Updated 05/18/26
A pilot regranting vehicle run by the Effective Institutions Project that supports initiatives expected to improve decision-making at important institutions around the world.
Discussion
Key risk: As a small early-stage org with a broad scope (institutional reform plus donor advising) and largely confidential impact, their work may be hard to audit and risks diffusing focus or duplicating existing AI governance efforts, weakening counterfactual x-risk reduction.
Case for funding: EIP is well-positioned to shape foundational AI governance by pinpointing and influencing key decision points across labs, governments, and major donors—already evidenced by discreet wins improving a major lab’s safety practices—and can mobilize mainstream philanthropy to reduce power-concentration and misalignment risks.