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OECD AI Principles
The OECD AI Principles, adopted in May 2019, were the first intergovernmental standard on artificial intelligence: five values-based principles for trustworthy AI and five recommendations for governments.
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Visão geral
They are not binding law, but they shaped the G20 AI Principles, the EU AI Act's definition of an AI system, and many national AI strategies.
Mergulho profundo
The OECD Council adopted its Recommendation on Artificial Intelligence in May 2019. Member countries and several non-members adhered to it, and in June 2019 the G20 adopted AI principles drawn from it, extending its reach to major economies outside the OECD. The five values-based principles for trustworthy AI are: inclusive growth, sustainable development and well-being; respect for the rule of law, human rights and democratic values, including fairness and privacy; transparency and explainability; robustness, security and safety; and accountability. Alongside them are five recommendations for policymakers: invest in AI research and development; foster an inclusive AI-enabling ecosystem; enable an interoperable governance and policy environment; build human capacity and prepare for labour market transition; and cooperate internationally. The OECD revised its definition of an AI system in November 2023. It now describes a machine-based system that, for explicit or implicit objectives, infers from its input how to generate outputs such as predictions, content, recommendations or decisions that can influence physical or virtual environments, noting that systems vary in autonomy and adaptiveness. The EU AI Act's definition closely follows this wording, which helps companies and regulators speak a common language. In May 2024 the principles themselves were updated to address general-purpose and generative AI. Changes included stronger attention to misinformation and disinformation, safety, including the ability to override or safely decommission systems that behave in unwanted ways, environmental sustainability, and interoperability between governance regimes. The OECD supports the principles with the OECD.AI Policy Observatory, launched in 2020, which tracks national policies and data, and with work such as incident monitoring. A common misconception is that the principles impose obligations on companies. They are a government-level recommendation; their influence comes through national laws, standards and procurement that adopt them.
Impacto Estratégico
Risco e segurança
Os danos catastróficos e diários da IA dependem de quem entende os riscos e de quem pode agir.
Decisões mais claras
A literacia pública e profissional determina se uma política de segurança forte é politicamente possível.
Cortando o hype
Explicações claras reduzem a captura por exageros, relações públicas de laboratório e teatro de ética vaga.
The Future of OECD AI Principles
The OECD's role has grown as a coordination point rather than a regulator. It supports reporting under the G7 Hiroshima AI Process and works on incident tracking and measurement, which could give governments more comparable evidence. Because the principles are high level, their practical effect depends on whether national laws, standards bodies and procurement rules keep referring to them. Divergence between regional approaches, such as the EU's binding regulation and lighter-touch regimes elsewhere, makes a shared baseline useful, but it does not guarantee convergence. Further revisions are likely as AI capabilities change.
Implementação no mundo real
EU lawmakers aligned the AI Act's definition of an AI system with the OECD's updated 2023 definition, so the two frameworks describe the same kinds of systems.
A national government writing its AI strategy organises its commitments around the OECD's five recommendations, such as investing in AI research and preparing workers for labour market changes.
A policy researcher uses the OECD.AI Policy Observatory to compare how different countries fund AI research and regulate AI.
A company's responsible AI policy maps its internal rules to the OECD principles of transparency, robustness and accountability to show customers its approach follows an international baseline.
Riscos e guarda-corpos
Tratar o risco existencial como ficção científica enquanto aumenta a capacidade.
Confundir segurança do produto de superfície com alinhamento sob alta autonomia.
Deixando o público não-inglês e não especializado com apenas fontes de baixa qualidade.
Roteiro de implementação
Separe os riscos de danos ao produto, uso indevido e perda de controle/desalinhamento.
Pergunte quais evidências mudariam sua visão sobre prazos e gravidade.
Prefira fontes primárias e avaliações concretas em vez de afirmações de marketing.
Identifique um caminho de ação: carreira, política, financiamento ou habilidades – não apenas conscientização.
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Perguntas frequentes
What is OECD AI Principles?
The OECD AI Principles, adopted in May 2019, were the first intergovernmental standard on artificial intelligence: five values-based principles for trustworthy AI and five recommendations for governments. They are not binding law, but they shaped the G20 AI Principles, the EU AI Act's definition of an AI system, and many national AI strategies.
When were the OECD AI Principles first adopted?
The OECD Council adopted its Recommendation on AI in May 2019, the first intergovernmental AI standard.
Which of these is one of the five values-based principles?
The five are inclusive growth and well-being; rule of law, human rights and democratic values; transparency and explainability; robustness, security and safety; and accountability.
Which item is a recommendation for policymakers rather than a values-based principle?
Building human capacity is one of the five recommendations to governments; the others listed are values-based principles.
Which body adopted AI principles in June 2019 drawn from the OECD's?
The G20 AI Principles drew from the OECD Recommendation, extending its reach beyond OECD members.
What word in the OECD definition most distinguishes AI systems from simple rule-based software?
The definition says an AI system infers from inputs how to generate outputs, which is key to most readings of scope.
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