We help to build, govern, and advance AI in the public interest.
AI development must focus on outcomes that matter to people and communities, with accountability guardrails in place.
Our programming works at different levels:
- Early warning signals: we identify and support nascent efforts that strengthen the public interest in a rapidly changing AI field.
- Windows of opportunity: we collaborate with partners to incubate underexplored, early-stage interventions with high potential to shape AI in the public interest.
- Scale-up: we engage civil society, governments, philanthropy, and the private sector to scale up the initiatives with proven momentum to serve the public interest.
Our priorities
Our team identifies and defines problems and opportunities that hinder or drive AI in the public interest, through collaboration, consultation, and iteration. Then we develop systems-focused strategies to guide our direct engagement and grantmaking.
We share our problem definitions openly, expecting them to evolve as we learn and as the field changes, because partnerships and learning are central to our impact.
Our current priorities are building an open, global, decentralised AI stack and strengthening the political alliances needed to drive public interest outcomes.
Lack of infrastructure for public interest AI
Challenge
The AI industry is almost entirely privatised. The state seeks a standard-setting and accountability role, but is not present at either the frontier or in the adoption of the technology as a builder. Therefore, public interests tend to be displaced in favour of private interests.
Opportunity
Public interest AI systems can be built with a fraction of the resources hyperscalers demand. Smaller, frugal, open models, powered by high-quality datasets show that an alternative exists, built on trust, collaboration, and different rules.
Opportunities and threats within the AI supply chain
Challenge
AI companies extract and consume minerals, water and energy to build and run infrastructure. They also extract behavioural and other data, often treated as free inputs to the models. The opacity of the AI supply chain enables these practices.
Opportunity
A transparent, inclusive, and accountable global AI supply chain would open the field to public interest entrants and enable interest groups in and around the supply chain, such as communities close to data centre buildout and workers, to strengthen their positions and leverage to catalyse change.
Weak public interest demand for AI
Challenge
The development of artificial intelligence has become divorced from public demands and needs. For most of the public, AI is coming too fast, leaving little room for choice and agency, let alone time to imagine a different, alternative future where AI serves them. It is the companies leading the AI field, not the public, whose demands are defining that very field.
Opportunity
The public is increasingly making its voice heard. There is pushback against decisions made without meaningful public participation. Properly aligned demand will make it possible for people around the world to use AI when it helps them accomplish things they want to do, and refrain from using it when they choose to do so.
Case Studies
FAQs
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Our decisions about who to support are based on in-depth research and analysis of the field, in consultation with stakeholders across civil society, government, philanthropy, and the private sector. We place a priority on working in collaboration and partnership with other funders, both private and public.
We identify grantees through this research and analysis and accept grant proposals by invitation.
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No. We are a small team and do not have the capacity to manage and vet high volumes of funding requests and proposals. As a result we do not accept or consider unsolicited funding requests and proposals.
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