Organizations and teams whose primary mission is AI safety, alignment, or AI governance.
Includes safety teams inside large AI labs (estimated FTEs for safety-relevant staff only),
university research groups with dedicated AI safety funding, and government AI safety bodies.
Excludes broader responsible AI, AI ethics teams at tech companies, general ML fairness research,
and AI regulation bodies not focused on catastrophic/existential risk.
FTE estimates are from Stephen McAleese's AI safety organization dataset, as of 2025-09-27 (a few orgs refreshed individually since carry their own newer date).
Box area =
Color:
501(c)(3) 501(c)(4) otherGrouped by subfield. Boxes shown only where the metric is known.
Has budget data Missing budget data
Box area = cycle spend, to scale. Pro-industry money dwarfs pro-safety. Labels show actual $. Pro-industry Pro-safety
Box area = total disbursed. Grouped by funder type.
Scope caveat
"AI safety" here means organizations focused on alignment, safety research, and AI governance around catastrophic/existential risk. A 3x scope expansion (e.g. including all responsible-AI and ML fairness work) could increase headcount estimates by ~10x. These comparisons reflect the narrow scope defined above.
187 named grant decision-makers across 25 organizations — school, experience, and cause-area focus for each.
Unlike the rest of this field map, this tab is LLM-researched via multi-agent web search rather than hand-sourced. Degree/roster data is single-source (adversarial cross-checking was skipped by request); years-of-experience and cause-area are single-pass estimates. Treat as directional, not authoritative.
103
Grantmaking orgs found
25
Orgs with rosters built
187
Unique decision-makers
146
With school on record
Most common alma maters
Oxford
22
Stanford
19
UC Berkeley
19
Cambridge
16
MIT
11
Harvard
6
Toronto
6
Columbia
6
Degree fields
Computer Science
71
Mathematics
34
Engineering
25
Philosophy
24
Economics
14
Physics
12
Psychology
8
Political Science
7
Degree levels held (146 people with school data)
143
Bachelor's
82
Master's
64
Doctorate
Years of relevant experience (149 people)
0–2 yrs
12
3–5 yrs
41
6–10 yrs
64
11–15 yrs
17
16+ yrs
15
Organization types (25 orgs)
Fund
9
Foundation
8
Regranting platform
4
Government program
2
Individual donor
1
Corporate consortium
1
Specific cause area within AI safety (149 people)
AI Governance / Policy
36
Technical: Alignment (general)
14
Generalist / Leadership
13
Field-building / Capacity
12
Frontier Model Evals
10
Technical AI Safety (general)
9
s-risk / Suffering-focused
9
Interpretability
7
Agent Foundations / Decision Theory
6
Cooperative AI / Multi-agent
5
Cross-org connectors — people who sit on multiple grantmaking bodies
Jaan Tallinn— SFF, personal giving, Lightspeed Grants
Oliver Habryka— SFF, Lightspeed Grants, LTFF, ARM Fund
Andrew Critch— SFF, Jaan Tallinn personal giving, BERI