Foundation Models / GPAI
foundation_models · AI-governance topic
Foundation Models / GPAI is obligations specific to general-purpose / foundation models above certain capability thresholds. Across 29 tracked AI-governance instruments, 18 address this topic explicitly, 5 via general principles, and 6 are silent.
Definition and scope
Obligations specific to general-purpose / foundation models above certain capability thresholds.
The cross-jurisdiction picture below shows how each of 29 tracked instruments treats this topic. The patterns vary substantially — and 6 regimes are silent, leaving gaps that future policy work could address.
Historical primacy & cross-jurisdiction tension
First addressed by OECD AI Principles (Recommendation) on (implicit). Subsequent regimes have either codified, diverged from, or remained silent on this baseline.
- Forum-shoppingEU AI Act↔Executive Order 14179 — Removing Barriers to American Leadership in AI
- Forum-shoppingExecutive Order 14110 on Safe, Secure, Trustworthy AI↔UN GA Resolution on Safe, Secure, Trustworthy AI
- Forum-shoppingInterim Measures for Generative AI Service Management↔African Union Continental AI Strategy
Cross-jurisdiction coverage
At a glance — same legend as the hub matrix
Silent regimes — gap signal
Instruments that do not address Foundation Models / GPAI — candidates for future policy work.
- Executive Order 14179 — Removing Barriers to American Leadership in AIUS
- UN GA Resolution on Safe, Secure, Trustworthy AIUN
- African Union Continental AI StrategyAfrican_Union
- NYC Local Law 144 of 2021 (Automated Employment Decision Tools)US
- Colorado Artificial Intelligence Act (SB 24-205)US
- Illinois HB 3773 / Public Act 103-0804 (AI Employment Discrimination)US
References
- EU-AIA-2024: Arts. 51-55 (general-purpose AI + systemic risk)
- US-EO-14110: §4.2(a) — Defense Production Act reporting
- UK-WHITEPAPER-2023: Cross-cutting principles; sector regulators apply
- CN-GENAI-2023: Art. 2 (applies to GenAI services regardless of size)
- G7-HIROSHIMA: Code applies to advanced AI
- OECD-AI-PRIN: 2024 update clarifies GPAI scope
- COE-AI-CONV: Applies to AI throughout lifecycle (Art. 3)
- NIST-AI-RMF: GenAI Profile (NIST AI 600-1, 2024)
- BLETCHLEY-2023: Declaration §1-2 (frontier AI defined as the subject)
- SEOUL-2024: Declaration + accompanying Frontier AI Safety Commitments (16 signatory companies)
- NIST-AI-RMF-GENAI: Entire NIST AI 600-1 scope is GPAI / GenAI
- CA-SB-1047: Cal. SB-1047 §22603 — 'covered model' = above 10^26 FLOPs OR $100M training cost
- IN-DPDP-2023: MEITY Apr-2024 advisory walked back the Mar-2024 pre-deployment-approval requirement; current approach is post-deployment incident reporting
- BR-AIBILL-2024: PL 2338/2023 Arts. 17-19 (general-purpose AI systemic-risk obligations)
- ASEAN-AI-GUIDE-2024: Guide §6 covers GenAI but with flexible implementation expectations
- ANTHROPIC-RSP-2024: RSP v2 §2 — ASL framework applies to frontier model releases
- OPENAI-PREPAREDNESS-2023: Preparedness Framework §1-2 — applies to all OpenAI frontier-model releases
- DEEPMIND-FSF-2024: FSF applies to Google DeepMind frontier-model releases
- META-FRONTIER-2024: Framework applies to Meta frontier-model releases (Llama family)
- UK-US-AISI-MOU-2024: MoU scope is frontier AI evaluation
- WH-VOLUNTARY-2023: Commitments §1-2 — internal + external security testing of frontier models
- SG-MODEL-AI-2024: Framework Dimension 3 (Trusted Development + Deployment) explicitly covers GenAI models
- JP-METI-AI-2024: Guidelines Part 3 — covers AI providers including foundation-model developers
Cite this article
6 formats · 1-click copyPersistent identifier: https://policywindow.org/wiki/foundation-models — committed-stable URL with content-versioning via ?asOf= (rollout pending per methodology §7). DOIs via Zenodo are on the roadmap.
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23 instruments tracked.