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The Collective Intelligence Project (CIP) is a nonprofit R&D organization founded in August 2022 by Divya Siddarth and Saffron Huang, with Jasmine Wang as a third co-founder. The organization publicly launched with a whitepaper in February 2023 that outlined its vision for new governance models for transformative technology. CIP is headquartered in San Francisco, having opened its first office in Japantown in 2024.
CIP's central thesis is that existing governance approaches for transformative technologies force trade-offs between progress, safety, and democratic participation, what they call the Transformative Technology Trilemma. CIP works to develop a fourth path through collective intelligence capabilities that integrate all three priorities…
CIP identifies a Transformative Technology Trilemma in which existing governance approaches force trade-offs between technological progress, safety, and democratic participation. Their theory of change is that by developing and deploying collective intelligence tools -- scalable processes for surfacing, aggregating, and acting on diverse public values -- they can create a fourth path that integrates all three priorities. Concretely, CIP builds platforms for large-scale public deliberation (Global Dialogues), community-driven AI evaluation (Weval), and participatory model alignment (Community Models), then partners with AI labs and governments to embed the resulting insights into actual development and policy decisions. This creates a feedback loop where public input directly influences how AI systems are built, evaluated, and governed, reducing the risk that transformative AI is developed without adequate democratic accountability or diverse safety considerations.
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View on grantmaking.aiA collaboration that runs cultural and social evaluations of frontier AI across regions, partnering with local experts and NGOs to build context‑specific benchmarks so AI systems work globally, not just in English‑speaking settings.
A six‑month, fully remote research fellowship for three early‑career scholars to use CIP’s proprietary datasets to produce original work on AI, public values, and democratic governance.
A series of democratic deliberation processes that bring diverse publics into questions like AI release, risk, and governance, translating their preferences into guidance for labs, governments, and civil-society partners.
An open, collaborative platform that lets communities design and run qualitative AI model evaluations so anyone can test what matters to them across domains like medicine, law, and education.
A platform and methodology that enable communities to collaboratively design, train, and refine AI models based on collectively defined constitutions, so model behavior reflects shared local values.
A research and policy roadmap that lays out concrete steps stakeholders can take in the near term to build a more democratic AI ecosystem that is adaptive, accountable, and aligned with public values.
A series of large-scale, AI‑enabled public dialogues and surveys that convene thousands of people in many countries to articulate what they want from AI and to feed those views into AI policy and model development.