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UN partners with Google to launch AI-ready data platform to make global statistics easier to access
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UN partners with Google to launch AI-ready data platform to make global statistics easier to access

The United Nations has partnered with Google to launch the UN System Data Commons, making global statistics easier for people and AI agents to access. The platform supports natural-language searches and Model Context Protocol (MCP), allowing AI systems to retrieve data directly from UN sources.

The United Nations has partnered with Google to make its vast collection of global statistics easier for people and AI systems to access, according to Google's 17 September announcement. The initiative, announced Thursday, will create the UN System Data Commons, a new platform that integrates data from multiple UN agencies into one AI-ready system.

The platform is built on Google's open-source Data Commons and supports natural-language queries as well as the Model Context Protocol (MCP). It replaces the older UNData portal, which relied largely on traditional database searches. The decision will help AI systems to pull authoritative statistics and enable users to trace back to the original source, the UN says.

UN data gets an AI-ready platform

The UN System Data Commons will help to integrate statistics across various UN agencies in a common framework. At launch, 26 entities have pledged their support for the platform, and data from nearly 20 agencies are available. By 2027, the organization aims to provide 80% of all statistical datasets available in the UN system on the platform.

The move comes as more people turn to AI tools to search for information. However, a benchmark conducted by UNICEF found that AI models can struggle with basic development statistics.

UNICEF's chief statistician, João Pedro Azevedo, explained that the benchmark was applied to six AI models and tested across 1,33,000 responses, yielding an average accuracy of 21.2%. OpenAI, Anthropic and Google models were included in the study. The UNICEF research is still a working paper and has not been peer-reviewed.

Pragya Singha Roy

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