기술 가이드

GPAI Models with Systemic Risk Under the EU AI Act

The EU AI Act treats a general-purpose AI model as systemic-risk when it has high-impact capabilities or the Commission designates it for equivalent capabilities or impact.

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  • 마지막 업데이트
이 페이지에서3분 읽기
  1. 개요
  2. 심층 분석
  3. 전략적 영향
  4. The Future of GPAI Models with Systemic Risk Under the EU AI Act
  5. 실제 구현
  6. 위험 및 가드레일
  7. 구현 로드맵
  8. 계속 탐색하세요
  9. 자주 묻는 질문

개요

More than 10^25 training FLOP creates a presumption of high-impact capability, not an unchallengeable classification; systemic-risk providers have extra evaluation, risk-management, incident-reporting, and cybersecurity duties.

심층 분석

The AI Act’s systemic-risk category is a subset of general-purpose AI models. Article 51 provides two routes: a model has high-impact capabilities assessed with appropriate tools, indicators, and benchmarks; or the Commission designates it because capabilities or impact are equivalent, using Annex XIII criteria. Training compute above 10^25 floating-point operations creates a presumption of high-impact capability. The number is a threshold in the law and is subject to delegated adjustment; it is not the only way to qualify. Article 52 requires a provider whose model meets the compute condition to notify the Commission without delay, and no later than two weeks after the condition is met or it becomes known that it will be met. The provider may submit substantiated arguments that the model does not, due to its specific characteristics, present systemic risks. The Commission can reject that case or designate a model on its own initiative or following a qualified scientific-panel alert. Commission guidelines describe its interpretation and enforcement approach but are not binding law. Article 55 adds four duties beyond the general GPAI requirements: standardized model evaluation, including documented adversarial testing; assessment and mitigation of possible systemic risks at Union level; documentation and reporting of serious incidents and corrective measures; and adequate cybersecurity for both model and physical infrastructure. These duties are not waived just because a model is distributed under a free and open-source license. Providers can rely on an approved code or harmonised standards while available, or demonstrate alternative adequate means for Commission assessment. GPAI obligations began applying on August 2, 2025. The Commission’s guidance states that its enforcement powers apply from August 2, 2026, and qualifying models already on the market before August 2, 2025 have a compliance transition until August 2, 2027. Providers should track training-compute evidence, expected threshold timing, notification, and any designation decision. This is an overview, not a legal opinion on an individual model.

전략적 영향

비용 및 예산

아키텍처 결정은 수년 동안 성능과 운영 비용을 결정합니다.

더 명확한 결정들

기술 교육은 팀이 최신 스택뿐만 아니라 올바른 스택을 선택하는 데 도움이 됩니다.

품질 관리

더 나은 엔지니어링 선택은 생산 시 신뢰성 사고를 줄입니다.

The Future of GPAI Models with Systemic Risk Under the EU AI Act

The Act empowers the Commission to revise compute thresholds and benchmarks as capabilities and hardware efficiency evolve. A provider should not assume today’s FLOP threshold will remain fixed or that falling below it resolves designation risk. Monitor official Commission guidelines and any delegated acts, and review status when a model’s training run, capabilities, distribution, or deployment context changes. Track delegated updates to Annex XIII and any official changes to the compute presumption. Document threshold calculations consistently across training runs. Review changes before each release.

실제 구현

A provider forecasts training compute above 10^25 FLOP and prepares the Article 52 notification before the threshold is reached.

A provider crossing the threshold submits evidence with its notification explaining why the model’s specific capabilities do not create systemic risk.

A safety team documents adversarial testing, EU-level risk assessments, incident response, and infrastructure security for a designated model.

A company with an open-source systemic-risk model checks Article 55 duties rather than assuming Article 53’s limited exception covers it.

위험 및 가드레일

  • 하나의 벤치마크를 최적화하면 더 광범위한 시스템 약점을 숨길 수 있습니다.

  • 인프라 및 유지 관리 비용은 종종 과소평가됩니다.

  • 시스템이 더욱 복잡해짐에 따라 보안 및 관찰 가능성의 격차가 커질 수 있습니다.

구현 로드맵

  1. 구현하기 전에 지연 시간, 품질, 비용 목표를 정의하세요.

  2. 현실적인 로드 및 데이터 조건에서 벤치마킹합니다.

  3. 오류, 드리프트 및 사용자 영향에 대한 계측기 모니터링.

  4. 확장하기 전에 롤백 및 사고 대응 경로를 준비하세요.

계속 탐색하세요

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자주 묻는 질문

What is GPAI Models with Systemic Risk Under the EU AI Act?

The EU AI Act treats a general-purpose AI model as systemic-risk when it has high-impact capabilities or the Commission designates it for equivalent capabilities or impact. More than 10^25 training FLOP creates a presumption of high-impact capability, not an unchallengeable classification; systemic-risk providers have extra evaluation, risk-management, incident-reporting, and cybersecurity duties.

What does training compute above 10^25 FLOP do under Article 51?

Article 51(2) presumes high-impact capabilities above the compute threshold, while Article 51 and 52 allow other evidence and procedures.

Which second route can lead to systemic-risk designation besides the compute presumption?

Article 51(1)(b) and Article 52(4) allow Commission designation based on equivalent capabilities or impact using Annex XIII criteria.

When must a provider notify the Commission after a model meets or is expected to meet the compute condition?

Article 52(1) requires notice without delay and no later than two weeks after the condition is met or known to be expected.

Which item is an Article 55 duty for a systemic-risk GPAI provider?

Article 55(1)(a) requires model evaluation under state-of-the-art protocols, including documented adversarial testing.

What does Article 55 require about serious incidents?

Article 55(1)(c) requires tracking, documenting, and reporting serious-incident information and possible corrective measures.