?asOf= parameter to see the current catalog state.Compute-Threshold Reporting
compute_reporting · AI-governance topic
Compute-Threshold Reporting is mandatory reporting based on training-compute or capability thresholds. Across 29 tracked AI-governance instruments, 3 address this topic explicitly, 5 via general principles, and 21 are silent.
Definition and scope
Mandatory reporting based on training-compute or capability thresholds.
The cross-jurisdiction picture below shows how each of 29 tracked instruments treats this topic. The patterns vary substantially — and 21 regimes are silent, leaving gaps that future policy work could address.
Historical primacy & cross-jurisdiction tension
First addressed by White House Voluntary AI Commitments 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↔UK Pro-Innovation Approach to AI Regulation (White Paper)
- Forum-shoppingCalifornia SB-1047: Safe and Secure Innovation for Frontier AI Models Act↔Interim Measures for Generative AI Service Management
Cross-jurisdiction coverage
At a glance — same legend as the hub matrix
Silent regimes — gap signal
Instruments that do not address Compute-Threshold Reporting — candidates for future policy work.
- Executive Order 14179 — Removing Barriers to American Leadership in AIUS
- UK Pro-Innovation Approach to AI Regulation (White Paper)UK
- Interim Measures for Generative AI Service ManagementCN
- G7 Hiroshima AI Process Code of ConductG7
- OECD AI Principles (Recommendation)OECD
- Council of Europe Framework Convention on AIcouncil_of_europe
- UN GA Resolution on Safe, Secure, Trustworthy AIUN
- NIST AI Risk Management FrameworkUS
- NIST AI RMF Generative AI ProfileUS
- India Digital Personal Data Protection Act + AI Advisory (MEITY)IN
- Brazil AI Bill (PL 2338/2023)BR
- ASEAN Guide on AI Governance and EthicsASEAN
- African Union Continental AI StrategyAfrican_Union
- Google DeepMind Frontier Safety FrameworkUS
- Meta Frontier AI FrameworkUS
- UK-US AI Safety Institute Memorandum of Understandingglobal
- Singapore Model AI Governance Framework for Generative AISG
- Japan METI AI Guidelines for BusinessJP
- 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: Art. 52 + Annex XIII (10²⁵ FLOP presumption)
- US-EO-14110: §4.2(a)(i) — 10²⁶ FLOP threshold
- BLETCHLEY-2023: Declaration §6 calls for capability evaluation but does not specify compute thresholds
- SEOUL-2024: Safety Commitments invoke capability thresholds; compute is one proxy
- CA-SB-1047: Cal. SB-1047 §22603(b) — annual reporting of training compute + safety determination
- ANTHROPIC-RSP-2024: RSP v2 capability evaluations triggered by capability rather than pure compute; compute is one signal
- OPENAI-PREPAREDNESS-2023: Capability-tier evaluations are the primary trigger; compute is a coincident signal
- WH-VOLUNTARY-2023: Self-reporting through commitments framework; binding compute thresholds came via EO 14110 §4.2(a)
Cite this article
6 formats · 1-click copyPersistent identifier: https://policywindow.org/wiki/compute-reporting — committed-stable URL with content-versioning via ?asOf= (rollout pending per methodology §7). DOIs via Zenodo are on the roadmap.
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8 instruments tracked.