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Coefficient Giving Forecasting Fund
webCredibility Rating
4/5
High(4)High quality. Established institution or organization with editorial oversight and accountability.
Rating inherited from publication venue: Coefficient Giving
This is the landing page for a major philanthropic fund specifically targeting forecasting as an input to AI safety and global catastrophic risk decisions; useful for understanding funding landscape and active grant opportunities in this space.
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Importance: 52/100homepage
Summary
Coefficient Giving's Forecasting Fund supports probabilistic forecasting development and adoption for high-stakes decisions in AI safety, biosecurity, and national security, having made 30+ grants totaling $50M+. The fund backs platform development, forecasting research, tournaments, and efforts to bring rigorous quantitative judgment to domains currently relying on intuition. It reflects Coefficient Giving's philosophy that explicit probability estimates improve decision quality and enable learning from prediction track records.
Key Points
- •30+ grants totaling $50M+ to advance forecasting platforms, methods research, tournaments, and adoption in critical decision domains
- •Focus areas include AI risk evaluation, biosecurity, and national security where poor forecasting could lead to catastrophic outcomes
- •Supports AI-assisted forecasting tools through an active RFP for projects improving probabilistic reasoning and accuracy
- •Coefficient Giving applies forecasting internally, tracking grantmaker prediction accuracy to refine judgment over time
- •Emphasizes that explicit probability estimates eliminate ambiguity (e.g., what 'probably' means) and enable accountability through measurable accuracy
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| Good Judgment (Forecasting) | Organization | 50.0 |
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# Forecasting
We support work to develop high-quality forecasts on questions relevant to critical decisions, and to ensure those forecasts reach the right people.
- 30+
grants made
- $50+
million given
## Contents
- [About the Fund](https://coefficientgiving.org/funds/forecasting/#about-the-fund)
- [Research & Updates](https://coefficientgiving.org/funds/forecasting/#research-and-updates)
- [Featured Grants](https://coefficientgiving.org/funds/forecasting/#featured-grants)
## About the Fund
### Team
- [](https://coefficientgiving.org/team/benjamin-tereick/)
[Benjamin Tereick](https://coefficientgiving.org/team/benjamin-tereick/)
Associate Program Officer
### Partners
- [**Good Ventures**](https://www.goodventures.org/)
Interested in providing funding within this space? Reach out to [partnerwithus@coefficientgiving.org](mailto:partnerwithus@coefficientgiving.org).
Quantitative forecasting — estimating the odds of future events, and later checking those estimates against reality — has transformed fields like finance and sports. But in others, like national security or public health, major decisions are often guided by intuition or vague, qualitative judgments about the future. This makes it harder to learn from experience and to know whose predictions deserve trust.
Explicit, probabilistic forecasts can help. They make assumptions clearer — no guessing [whether “probably” means a 60% chance or 90%](https://www.researchgate.net/publication/335771404_Variants_of_Vague_Verbiage_Intelligence_Community_Methods_for_Communicating_Probability) — and allow accuracy to be measured. Over time, they can be used to improve decision-making.
At Coefficient Giving, we use forecasting internally: our grantmakers [often make probabilistic predictions](https://coefficientgiving.org/research/how-accurate-are-our-predictions/) about the outcomes of grants to test and refine their judgment. We aim to expand this practice more broadly — especially in areas like evaluating risks from AI or biotechnology, where errors in judgment could lead to disastrous outcomes. We also want to ensure that high-quality forecasts are available to inform decision-makers in those critical areas.
Work we support includes:
1. **Platform development and practical forecasting tools,** including those that use AI to make better or cheaper predictions.
2. **Research on forecasting methods,** including on ways to improve their accuracy and relevance for hard-to-measure questions.
3. **Forecasting tournaments** that explore questions relevant to our other focus areas.
4. **Projects promoting the use of forecasting** for high-stakes decisions **,** particularly those related to global catastrophic risks.
## Updates & Opportunities
- ### [How A
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