Coefficient Giving

Quick Assessment

Organization Details

Overview

Coefficient Giving is a major philanthropic organization that has directed over $4 billion in grants since 2014 across global health, AI safety, pandemic preparedness, farm animal welfare, and other cause areas. In November 2025, the organization rebranded from Open Philanthropy to Coefficient Giving, signaling an expansion from serving primarily one anchor donor (Good Ventures, the foundation of Dustin MoskovitzPersonDustin MoskovitzDustin Moskovitz and Cari Tuna have given $4B+ since 2011, with ~$336M (12% of total) directed to AI safety through Coefficient Giving (formerly Open Philanthropy), making them the largest individu...Quality: 49/100 and Cari Tuna) to operating 13 cause-specific funds open to multiple philanthropists. The name "Coefficient" reflects the organization's goal of multiplying impact through research, grantmaking, and partnerships—with "co" nodding to collaboration and "efficient" reflecting their unusual focus on cost-effectiveness.

Coefficient Giving is widely considered the largest funder of AI safety work globally. Since 2014, approximately $336 million (12% of total grants) has gone to AI safety research and governance, with roughly $46 million deployed in 2023 alone—making it the dominant external funder in a field where most safety research happens inside frontier AI labs. The organization's Navigating Transformative AI Fund supports technical AI safety researchCruxTechnical AI Safety ResearchTechnical AI safety research encompasses six major agendas (mechanistic interpretability, scalable oversight, AI control, evaluations, agent foundations, and robustness) with 500+ researchers and $...Quality: 66/100, AI governance and policyCruxAI Governance and PolicyComprehensive analysis of AI governance mechanisms estimating 30-50% probability of meaningful regulation by 2027 and 5-25% x-risk reduction potential through coordinated international approaches. ...Quality: 66/100 work, and capacity building, with a $40 million Technical AI Safety RFP launched in 2025 covering 21 research areas.

The organization distinguishes itself through its strategic cause selection methodology—identifying problems that are large, tractable, and neglected relative to their size. This approach, combined with a willingness to fund speculative research and support multiple funding mechanisms (direct grants, regranting programs, pooled funds), has made Coefficient Giving central to the effective altruism funding ecosystem. However, critics have noted concerns about funding concentration, the slow pace of spending relative to the scale of AI risks, and heavy focus on evaluations over alignment research in recent technical AI safety grants.

History and Evolution

Origins (2011-2017)

Coefficient Giving traces its origins to 2011 when GiveWell, the charity evaluator founded by Holden KarnofskyPersonHolden KarnofskyHolden Karnofsky directed $300M+ in AI safety funding through Coefficient Giving (formerly Open Philanthropy), growing the field from ~20 to 400+ FTE researchers and developing influential framewor...Quality: 40/100 and Elie Hassenfeld, began advising Good Ventures on how to deploy Dustin MoskovitzPersonDustin MoskovitzDustin Moskovitz and Cari Tuna have given $4B+ since 2011, with ~$336M (12% of total) directed to AI safety through Coefficient Giving (formerly Open Philanthropy), making them the largest individu...Quality: 49/100's philanthropic capital effectively. Good Ventures was established by Moskovitz (Facebook co-founder, net worth ≈$12 billion) and Cari Tuna in 2011. By 2014, this advising relationship formalized into "Open Philanthropy" as a distinct project within GiveWell, focused on identifying high-impact giving opportunities across a broader range of cause areas than GiveWell's traditional global health focus.

In 2017, Open Philanthropy spun off from GiveWell as an independent LLC, enabling it to pursue its own strategic priorities while GiveWell continued focusing on evidence-backed global health interventions. The separation reflected diverging methodologies: GiveWell prioritizes robust evidence of effectiveness, while Open Philanthropy embraced "hits-based giving"—funding speculative, high-variance projects where a few major successes could justify many failures.

Growth and AI Safety Focus (2015-2024)

Coefficient Giving began supporting AI safety work in 2015, when the field was nascent and institutional support was minimal. Early grants helped establish foundational organizations including the Machine Intelligence Research Institute (MIRIOrganizationMachine Intelligence Research InstituteComprehensive organizational history documenting MIRI's trajectory from pioneering AI safety research (2000-2020) to policy advocacy after acknowledging research failure, with detailed financial da...Quality: 50/100), the Center for Human-Compatible AI at UC Berkeley, and the Future of Humanity Institute at Oxford. By 2023, AI safety had become Coefficient Giving's largest longtermist cause area, reflecting growing concern about advanced AI risks among the leadership team.

The November 2025 Rebrand

On November 18, 2025, Open Philanthropy announced its rebranding to Coefficient Giving. The change reflected several strategic shifts:

Multi-Donor Expansion: The organization moved from primarily serving Good Ventures to operating pooled funds open to any philanthropist. In 2024, Coefficient directed over $100 million from donors besides Good Ventures; by 2025, non-Good Ventures funding had more than doubled.

Brand Clarity: The old "Open Philanthropy" name created confusion—journalists mistook it for OpenAIOrganizationOpenAIComprehensive organizational profile of OpenAI documenting evolution from 2015 non-profit to Public Benefit Corporation, with detailed analysis of governance crisis, 2024-2025 ownership restructuri...Quality: 62/100, and potential grantees confused it with Open Society Foundations. "Coefficient Giving" was chosen to provide a distinctive identity and resolve that confusion.

Structural Reorganization: The organization restructured from program areas to 13 distinct funds, each with dedicated leadership and transparent goals, allowing donors to support specific causes at scale.

Organizational Structure

flowchart TD
  GV[Good Ventures<br/>Moskovitz & Tuna] --> CG[Coefficient Giving<br/>4B+ directed]
  OD[Other Donors<br/>$100M+ in 2024] --> CG

  CG --> NTAI[Navigating<br/>Transformative AI]
  CG --> BPP[Biosecurity &<br/>Pandemic Prep]
  CG --> GCR[Global Catastrophic<br/>Risks Opportunities]
  CG --> GH[Global Health<br/>& Wellbeing]
  CG --> OTHER[10 Other Funds]

  NTAI --> TAIS[Technical AI<br/>Safety Research]
  NTAI --> GOV[AI Governance<br/>& Policy]
  NTAI --> CAP[Capacity Building<br/>& Field Growth]

  TAIS --> CAIS[Center for AI Safety]
  TAIS --> REDWOOD[Redwood Research]
  TAIS --> MIRI[MIRI]

  style GV fill:#e6f3ff
  style CG fill:#ccffcc
  style NTAI fill:#ffffcc
  style TAIS fill:#ffcccc

The 13 Funds Model

Since the November 2025 rebrand, Coefficient Giving operates through 13 cause-specific funds, each pooling money from multiple donors:

Navigating Transformative AI Fund

The Navigating Transformative AI Fund is Coefficient's primary vehicle for AI-related grantmaking, supporting:

Technical AI Safety Research: Work aimed at making advanced AI systems more trustworthy, robust, controllable, and aligned. This includes interpretability research, robustness to adversarial inputs, scalable oversight methods, and understanding emergent capabilities.

AI Governance and Policy: Frameworks for safe, secure, and responsibly managed AI development, including export controls, compute governance, international coordination, and corporate governance mechanisms.

Capacity Building: Growing and strengthening the field of researchers and practitioners working on AI challenges, including training programs, career development, and institutional infrastructure.

Short-Timeline Projects: New projects expected to be particularly impactful if timelines to transformative AI are short, reflecting Coefficient's view that advanced AI could emerge within the next 5-15 years.

Regrantor Model

Regrantor Criteria

AI Safety Grantmaking

2024 Technical AI Safety Funding Breakdown

An analysis of Coefficient Giving's Technical AI Safety funding revealed the following distribution of the $28M recorded in their database:

Note: The $28M figure underestimates total 2024 spending as some approved grants had not been posted to the database at time of analysis. Coefficient acknowledged spending "roughly $50 million" on technical AI safety in 2024.

Historical Major AI Safety Grants

Totals from Coefficient Giving's public grants database (includes grants made when the organization was named Open Philanthropy):

2025 Technical AI Safety RFP

In early 2025, Coefficient launched a $40 million Request for Proposals across 21 research areas, with funding available for substantially more based on application quality. Key features:

Priority Research Areas (starred items are especially prioritized):

Grant Characteristics:

Regranting Ecosystem

Coefficient Giving supports multiple regranting platforms and mechanisms to achieve faster, more distributed funding decisions. This represents a deliberate strategy to complement slower direct grantmaking with nimble, expert-driven allocation.

Funding Flow Through Regranting

flowchart LR
  CG[Coefficient Giving] --> LTFF[Long-Term<br/>Future Fund]
  CG --> MF[Manifund<br/>Regrants]
  CG --> SFF[Survival &<br/>Flourishing Fund]

  LTFF --> I1[Individual<br/>Researchers]
  LTFF --> O1[Small Orgs]

  MF --> I2[Early-Stage<br/>Projects]
  MF --> I3[Emerging<br/>Talent]

  SFF --> O2[Established<br/>Orgs]

  style CG fill:#e6f3ff
  style LTFF fill:#ffffcc
  style MF fill:#ccffcc
  style SFF fill:#ffcccc

Long-Term Future Fund (LTFF)

The Long-Term Future Fund is a committee-based grantmaking fund that receives significant support from Coefficient. About half of LTFF funding historically comes from Coefficient Giving donations.

LTFF grants tend toward smaller, faster decisions than direct Coefficient grants, serving researchers and projects that may not yet warrant Coefficient's full evaluation process.

Manifund AI Safety Regranting

Manifund operates a distinct regranting model where individual experts receive budgets to make independent funding decisions. For 2025, Manifund raised $2.25 million and announced their first 10 regrantors.

Named 2025 Regrantors:

Manifund Regranting Characteristics:

Notable Manifund Grants:

Survival and Flourishing Fund (SFF)

The Survival and Flourishing Fund uses a unique "S-process" algorithm for grant allocation, primarily funded by Jaan TallinnPersonJaan TallinnProfile of Jaan Tallinn documenting $150M+ lifetime AI safety giving (86% of $51M in 2024), primarily through SFF ($34.33M distributed in a 2025 grant round). Co-founded CSER (2012) and FLI (2014),...Quality: 53/100 (Skype co-founder). While Coefficient and SFF are independent, they share many grantees and strategic priorities.

How to Apply for Funding

Direct Application to Coefficient

The most straightforward path for substantial funding requests:

Tips for Applicants (from Coefficient's guidance):

The bar is intentionally low for submitting expressions of interest. Key failure modes to avoid include not demonstrating understanding of prior work (read papers linked in relevant RFP sections) and not demonstrating that your team has prior experience with ML projects. Even uncertain proposals are worth submitting as the RFP is partly an experiment to understand funding demand.

Via Regranting Platforms

Faster and more accessible for smaller grants:

Finding Regrantors

Many regrantors are reachable through:

• Direct outreach: Email or social media (many are publicly active on Twitter/X, LessWrong)
• EA communities: EA Forum, Alignment Forum, local EA groups
• Professional networks: AI safety conferences (NeurIPS safety track, ICML), SERI MATS alumni
• Manifund platform: Create project and regrantors may proactively reach out

Comparison with Other AI Safety Funders

Funding Gap Analysis

According to an overview of AI safety funding, total external philanthropic AI safety funding (≈$100M annually) is dwarfed by:

This funding gap is a persistent concern in the AI safety community, though Coefficient and other funders argue that talent constraints, not funding, are often the binding limitation.

Critical Assessment

Strengths

Scale and Stability: With Good Ventures' multi-billion dollar backing, Coefficient can make commitments that smaller funders cannot. This enables multi-year organizational support, compute grants, and substantial research programs.

Strategic Sophistication: The organization's cause selection methodology and research depth (public writeups, shallow investigations, deep dives) provides unusually transparent reasoning for grant decisions.

Ecosystem Building: By funding LTFF, Manifund, and other regranting mechanisms, Coefficient amplifies its reach while maintaining quality through trusted intermediaries.

Hits-Based Giving: Willingness to fund speculative research acknowledges that transformative progress often comes from unexpected directions, though this increases variance in outcomes.

Limitations and Criticisms

Funding Concentration: With Coefficient representing ~60% of external AI safety funding, the field is heavily dependent on one organization's worldview and priorities. Critics note this could lead to "possible solutions being overlooked or assumptions no longer being questioned."

Evaluation Focus: The heavy focus on evaluations/benchmarking (68% of 2024 technical grants) has drawn criticism. As one researcher noted, "This looks much worse than I thought it would, both in terms of funding underdeployment, and in terms of overfocusing on evals." Critics argue AI Safety Institutes are already well-resourced for evaluation work.

Alignment Neglect: Some researchers express disappointment that "there's so little emphasis in this RFP about alignment, i.e. research on how to build an AI system that is doing what its developer intended it to do."

Slow Spending: Coefficient has acknowledged that "in retrospect, our rate of spending was too slow, and we should have been more aggressively expanding support for technical AI safety work earlier." Key reasons cited include difficulty making qualified senior hires and disappointment with returns to past spending.

Grantmaking Depth vs. Volume Tension: Former technical AI safety lead Ajeya CotraPersonAjeya CotraAjeya Cotra is a member of technical staff at METR and former senior advisor at Coefficient Giving (formerly Open Philanthropy), where she led technical AI safety grantmaking including a $25M agent...Quality: 55/100 pursued a more "understanding-oriented" approach to grantmaking --- forming deep inside views about how specific research directions connect to preventing AI takeover, rather than relying on heuristics about researcher quality. This approach produced the narrowly targeted $25M agent benchmarks RFP but involved significant upfront research investment that reduced grant volume. Cotra characterized the broader organizational tension: "developing your views is a tonne of work... and in the meantime, you're not getting money out the door."

Grants Database Limitations: The public grants database "offers an increasingly inaccurate picture" of Coefficient's work, as it generally excludes funding advised from non-Good Ventures donors. Coefficient is considering deprecating it.

Strategic Questions

Future Strategy: From Salaries to Inference Compute

Ajeya CotraPersonAjeya CotraAjeya Cotra is a member of technical staff at METR and former senior advisor at Coefficient Giving (formerly Open Philanthropy), where she led technical AI safety grantmaking including a $25M agent...Quality: 55/100 has argued that Coefficient Giving's spending profile may need to fundamentally shift as AI capabilities advance. Currently, over 80% of grant money goes to human salaries. But in a future where AI systems surpass most human researchers, the optimal allocation might shift heavily toward purchasing API credits and GPU time. Cotra suggests the organization should track what fraction of spending goes toward AI inference for grantees (already occurring via ChatGPT subscriptions and API credits), assess whether this fraction is growing appropriately relative to AI capabilities, and build readiness to deploy large sums rapidly during "crunch time."

Key challenges to this transition include organizational inertia (Coefficient's multi-layer grant approval process is designed for human-scale decisions, not billion-dollar compute purchases), model access uncertainty (frontier models may not be commercially available during the intelligence explosion), and the jaggedness problem (AI may automate some research domains well before others, making it hard to judge the right moment to shift). Cotra suggests Coefficient may want to hedge by investing in AI-exposed assets (like GPU manufacturers) to offset rising compute prices during crunch time.

Sources and Citations

Primary Sources

• Coefficient Giving Official Website
• Open Philanthropy Is Now Coefficient Giving (Nov 2025)
• The Story Behind Our New Name
• Our Progress in 2024 and Plans for 2025
• Navigating Transformative AI Fund
• Technical AI Safety Research RFP

Analysis and Commentary

• An Overview of the AI Safety Funding Situation - LessWrong
• Brief Analysis of OP Technical AI Safety Funding - LessWrong
• Open Philanthropy Is Now Coefficient Giving - Inside Philanthropy
• How to Get a Grant from Coefficient Giving - Inside Philanthropy
• Coefficient Giving - Wikipedia

Regranting Programs

• Manifund AI Safety Regranting
• Manifund 2025 Regrants Announcement - EA Forum
• What Makes a Good Regrant? - Manifund Substack
• Long-Term Future Fund - EA Funds
• Survival and Flourishing Fund

Grantee Information

• Redwood Research Grant Page - Coefficient Giving
• MIRI AI Safety Retraining Program Grant - Coefficient Giving
• Center for AI Safety General Support - Coefficient Giving

External Links

• Coefficient Giving Website
• Coefficient Giving Funds
• Apply for Funding
• Navigating Transformative AI Fund
• EA Forum Topic: Coefficient Giving
• Manifund Regrants
• Long-Term Future Fund
• Survival and Flourishing Fund