Some checks are pending
Mirror PR to Forgejo / mirror (pull_request) Waiting to run
- Source: inbox/queue/2025-07-10-gpai-code-of-practice-final-loss-of-control-category.md - Domain: ai-alignment - Claims: 1, Entities: 1 - Enrichments: 3 - Extracted by: pipeline ingest (OpenRouter anthropic/claude-sonnet-4.5) Pentagon-Agent: Theseus <PIPELINE>
76 lines
No EOL
3.5 KiB
Markdown
76 lines
No EOL
3.5 KiB
Markdown
# EU GPAI Code of Practice
|
|
|
|
**Type:** Regulatory Framework
|
|
**Domain:** AI Alignment, AI Governance
|
|
**Status:** Active (enforcement begins August 2, 2026)
|
|
**Jurisdiction:** European Union (extraterritorial application)
|
|
**Authority:** EU AI Office
|
|
|
|
## Overview
|
|
|
|
The General-Purpose AI (GPAI) Code of Practice is the primary implementation vehicle for EU AI Act Articles 50-55, establishing mandatory obligations for providers of GPAI models with systemic risk (defined as models trained with >10^25 FLOPs).
|
|
|
|
## Scope
|
|
|
|
**Covered Providers (as of August 2025):**
|
|
- Anthropic (Claude)
|
|
- OpenAI (GPT-4o, o3)
|
|
- Google (Gemini 2.5 Pro)
|
|
- Meta (Llama-4)
|
|
- Mistral
|
|
- xAI (Grok)
|
|
|
|
## Four Mandatory Systemic Risk Categories
|
|
|
|
1. **CBRN risks** — chemical, biological, radiological, nuclear
|
|
2. **Loss of control** — AI systems that could become uncontrollable or undermine human oversight
|
|
3. **Cyber offense capabilities** — capabilities enabling cyberattacks
|
|
4. **Harmful manipulation** — large-scale manipulation of populations
|
|
|
|
## Requirements
|
|
|
|
**Safety and Security Model Report (before market placement):**
|
|
- Detailed model architecture and capabilities documentation
|
|
- Justification of why systemic risks are acceptable
|
|
- Documentation of systemic risk identification, analysis, and mitigation processes
|
|
- Description of independent external evaluators' involvement
|
|
- Details of implemented safety and security mitigations
|
|
|
|
**Three-Step Assessment Process (per major model release):**
|
|
1. **Identification** — must identify potential systemic risks from the four categories
|
|
2. **Analysis** — must analyze each risk, with third-party evaluators potentially required if risks exceed prior models
|
|
3. **Determination** — must determine whether risks are acceptable before release
|
|
|
|
**External Evaluation:**
|
|
Required unless providers can demonstrate their model is "similarly safe" to a proven-compliant model.
|
|
|
|
## Enforcement
|
|
|
|
- **Soft enforcement:** August 2025
|
|
- **Fines begin:** August 2, 2026
|
|
- **Penalty structure:** Up to 3% global annual turnover or €15 million, whichever is higher
|
|
- **Compliance presumption:** Signatories get presumption of compliance; non-signatories face higher AI Office scrutiny
|
|
|
|
## Signatories
|
|
|
|
As of August 2025: Anthropic, OpenAI, Google DeepMind, Meta, Mistral, Cohere, xAI, and ~50 other organizations.
|
|
|
|
## Development Process
|
|
|
|
Developed through multi-stakeholder process with significant industry input. AI safety researchers from GovAI, CAIS, and METR contributed to drafting committees. The four categories were contested — CBRN and cyber offense less controversial; loss of control and harmful manipulation reflect more contested AI safety concerns.
|
|
|
|
## Key Uncertainty
|
|
|
|
The specific technical definition of "loss of control" is in Appendix 1. Whether it means (a) behavioral human-override capability (shallow, consistent with current safety training) or (b) oversight evasion, self-replication, autonomous AI development (substantive alignment-relevant capabilities) determines whether GPAI enforcement produces genuine safety governance or documentation compliance theater.
|
|
|
|
## Timeline
|
|
|
|
- **2025-07-10** — Final version published by EU AI Office
|
|
- **2025-08** — Soft enforcement begins; major frontier labs sign as participants
|
|
- **2026-08-02** — Fines and full enforcement begin
|
|
|
|
## Related
|
|
|
|
- EU AI Act Articles 50-55 (parent legislation)
|
|
- EU AI Office (enforcement authority)
|
|
- Sessions 21-22 KB analysis (Bench-2-CoP finding: 0% compliance benchmark coverage of loss-of-control capabilities) |