New Zealand released a suite of AI materials—a milestone as the last OECD country to publish a national AI strategy. The post New Zealand created its AI Strategy and Guidance products to incorporate O…
OECD AI Policy Observatory
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Discover key insights from the G7 Hiroshima AI Process transparency reports on AI governance, risk management, safety, and accountability. The post G7 AI transparency reporting: Ten insights for AI go…
Global AI red lines are one way to set enforceable limits on dangerous AI uses and behaviours to prevent unacceptable risks and build trust. The post AI governance through global red lines can help pr…
The OECD and Southeast Asia are shaping AI governance through dialogues and building tools for safe, trustworthy AI. The post A dynamic dialogue with Southeast Asia to put the OECD AI Principles into …
Sovereign AI and critical digital capacities can support assistive technologies, public services, and inclusive, resilient AI policy. The post Sovereign AI for assistive and public technologies: How p…
Egypt has accelerated its commitment to AI as a pillar of its vision for sustainable development. The post Governing AI with inclusion: An Egyptian model for the Global South appeared first on OECD.AI…
OpenAI introduced GPT-OSS, a series of open-weight AI models, in August 2025 to increase transparency and innovation in the AI community, sparking debates about the openness of such models. This move prompted discussions on finding a balance between innovation, transparency, and potential risks associated with sharing AI models.
The OECD has highlighted the distinction between safety and security in AI incidents, emphasizing the importance of their common reporting for cybersecurity measures. This information was shared in a post on the OECD.AI website.
The article discusses the shift in how people seek privacy by sharing personal information with AI assistants, with a recent survey showing 60% of US adults using AI chatbots. It raises concerns about privacy in the age of intimate assistants, where AI may know individuals better than anyone else.
The integration of data and artificial intelligence (AI) into agriculture and food systems has been rapidly increasing, with innovations like soil sensors, satellite imagery, and AI-powered crop management tools reshaping traditional farming practices. This transformation includes advancements such as disease monitoring and prediction, supply chain traceability systems, and weather forecasting models, aiming to enhance efficiency and sustainability in the agriculture sector.