Inteligência Artificial

OpenAI aligns safety practices with EU AI Act’s GPAI Code

Publicado porRedacao AIDaily
4 min de leitura
Autor na fonte original: Ryan Daws

OpenAI has outlined how it aligns safety, security, and transparency work with the EU AI Act’s GPAI Code as enforcement approaches. The company has contributed to and endorsed the EU’s General-Purpose AI (GPAI) Code of Practice and the Code of Practice on Transparency of AI-Generated Content. Both emerged from multi-stakeholder processes. The GPAI Code sets […] The post OpenAI aligns safety practices with EU AI Act’s GPAI Code appeared first on AI News .

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OpenAI has outlined how it aligns safety, security, and transparency work with the EU AI Act’s GPAI Code as enforcement approaches. The company has contributed to and endorsed the EU’s General-Purpose AI (GPAI) Code of Practice and the Code of Practice on Transparency of AI-Generated Content . Both emerged from multi-stakeholder processes. The GPAI Code sets a shared bar for transparency, safety, and security across general-purpose models sold or deployed in the EU. OpenAI points to a stack of existing practices as evidence it already operates near that bar: pre-release testing of models, published system cards accompanying major launches, and outside red-teaming through what it calls its Red Teaming Network. The company also maintains a public Model Spec document describing how it shapes model behaviour. Two internal frameworks sit underneath that work. The Preparedness Framework has been in place since 2023 and was updated in 2025; it sets out how OpenAI identifies, evaluates and manages serious risks from advanced systems. A separate Frontier Governance Framework builds on it, explaining how the company’s safety and security practices map onto legal requirements including the GPAI Code specifically. Together, OpenAI says, those two documents govern risk assessment, safeguards, model reporting, security posture, incident response, and how external experts get pulled into the process. OpenAI cites its participation in the Frontier Model Forum alongside collaborations with the US Center for AI Standards and Innovation and the UK AI Security Institute , plus contributions to third-party evaluation standards more broadly. The stated goal is shared safety research and clearer testing benchmarks across the industry, not just within one company’s walls. Provenance gets harder as modalities multiply The Transparency Code commitments centre on a different problem: helping people tell when content was made or altered by AI. OpenAI’s approach rests on two mechanisms that are meant to reinforce each other. Content Credentials, built on the C2PA standard , attach context directly to a file. SynthID watermarking provides a fallback signal for cases where that metadata gets stripped out somewhere along the way. Coverage is expanding from images into audio outputs, and OpenAI says it’s working toward extending provenance measures across further modalities, including text, as the underlying standards and tooling mature. The company is also building signals and guidance aimed at developers who need to meet their own transparency obligations when building on top of its models. None of this solves provenance outright. Metadata gets lost and labels don’t always survive a transfer between platforms. No single signal, whether cryptographic or watermark-based, catches everything on its own. OpenAI’s response is a layered approach paired with continued work across the wider standards community rather than a claim that any one mechanism closes the gap. Cybersecurity as the test case for adaptive governance Capabilities that help defenders spot and patch vulnerabilities are the same capabilities that could help an attacker find them first. OpenAI believes the answer is its Trusted Access for Cyber programme, designed to give vetted defenders access to more advanced cyber capabilities while limiting exposure for misuse. That programme now has a European deployment arm. OpenAI states it launched its EU Cyber Action Plan in early May 2026, working with EU and national cyber agencies, private sector partners, and infrastructure operators to give them access to its more advanced cyber models. The stated aim of the plan is to strengthen cyber resilience across the continent. Whether “most advanced” translates into measurable defensive gains inside these agencies is a claim from OpenAI itself; the source material offers no independent verification of outcomes from the programme. The company positions this work as consistent with the European Commission’s Action Plan on Cybersecurity and Artificial Intelligence , which calls for coordinated handling of AI’s risks alongside its use in strengthening defensive capability, including secure access arrangements for cybersecurity purposes specifically. OpenAI says it will keep adjusting its compliance approach as EU AI Act implementation continues, and that it expects to keep learning from regulators and the wider community involved in shaping the rules. The company argues that rules need enough flexibility to adapt as the technology moves, so that businesses and organisations can keep benefiting from it. The GPAI Code and the Transparency Code are still relatively new instruments, and OpenAI’s compliance documentation is a moving target rather than a finished product. Teams building on OpenAI’s models in regulated European markets should treat the current system cards and Frontier Governance Framework as a starting point for their own due diligence, not a substitute for it. See also: Zuckerberg details Meta’s personal AI superintelligence strategy Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is part of TechEx and is co-located with other leading technology events including the Cyber Security & Cloud Expo . Click here for more information. AI News is powered by TechForge Media . Explore other upcoming enterprise technology events and webinars here . The post OpenAI aligns safety practices with EU AI Act’s GPAI Code appeared first on AI News .

Pontos-chave

  • A adesão da OpenAI ao GPAI da UE pode inspirar práticas semelhantes no Brasil.
  • A colaboração internacional em padrões de segurança é crucial para a regulamentação da IA.
  • A transparência na origem de conteúdos gerados por IA é fundamental para a confiança do consumidor.

Análise editorial

A adesão da OpenAI ao Código de Práticas do GPAI da UE é um passo significativo que pode influenciar o setor de tecnologia no Brasil, especialmente em um momento em que o país está discutindo regulamentações para a inteligência artificial. A transparência e a segurança são preocupações centrais para a adoção responsável da IA, e a OpenAI está se posicionando como um modelo a ser seguido. Isso pode incentivar empresas brasileiras a adotarem práticas semelhantes, promovendo um ambiente mais seguro e confiável para o desenvolvimento de tecnologias de IA.

Além disso, a colaboração da OpenAI com entidades internacionais, como o Frontier Model Forum e o Centro de Padrões e Inovação em IA dos EUA, demonstra uma tendência crescente de cooperação global em torno de padrões de segurança e transparência. Essa abordagem colaborativa pode ser um indicativo de como o Brasil deve se engajar em discussões internacionais sobre regulamentação de IA, buscando não apenas alinhar-se com as melhores práticas, mas também influenciar a criação de normas que considerem as particularidades do mercado local.

No que diz respeito ao futuro, é crucial que o Brasil observe como as práticas de transparência da OpenAI, como o uso de Content Credentials e a marcação por watermarking, evoluem e são implementadas. A capacidade de identificar a origem e a alteração de conteúdos gerados por IA será fundamental para a confiança do consumidor e a integridade das informações, especialmente em um cenário onde a desinformação é uma preocupação crescente. O desenvolvimento de tecnologias que garantam a proveniência do conteúdo pode ser um diferencial competitivo para empresas brasileiras.

Por fim, a implementação de frameworks internos, como o Preparedness Framework e o Frontier Governance Framework, pode servir de inspiração para empresas brasileiras que buscam estruturar suas práticas de segurança e gestão de riscos. A construção de uma cultura de responsabilidade e segurança em IA não é apenas uma questão de conformidade, mas uma necessidade estratégica para garantir a sustentabilidade e a aceitação das tecnologias emergentes no mercado brasileiro.

O que esta cobertura entrega

  • Atribuicao clara de fonte com link para a publicacao original.
  • Enquadramento editorial sobre relevancia, impacto e proximos desdobramentos.
  • Revisao de legibilidade, contexto e duplicacao antes da publicacao.

Fonte original:

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Sobre este artigo

Este artigo foi curado e publicado pelo AIDaily como parte da nossa cobertura editorial sobre desenvolvimentos em inteligência artificial. O conteúdo é baseado na fonte original citada abaixo, enriquecido com contexto e análise editorial. Ferramentas automatizadas podem auxiliar tradução e estruturação inicial, mas a decisão de publicar, a revisão factual e o enquadramento de contexto seguem responsabilidade editorial.

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