China's AI openness claims don't hold up under scrutiny

Key points

• China's GeoGPT, a geoscience AI system, was showcased at the World AI Conference in July 2025 as an example of open, jointly governed AI.
• Under the model openness framework endorsed in a recent UN report, GeoGPT would not qualify as open.
• GeoGPT's underlying model weights are built mainly on Alibaba's Qwen, whose licences do not meet the Open Systems Interconnection standard for genuine openness.
• Neither GeoGPT's training data nor its application source code has been released publicly.
• Its governance committee reports to Zhejiang Lab itself, not to an independent body.

China's AI labs have given the world some impressive, freely available tools. Qwen, DeepSeek, Kimi and others come from Chinese teams and have been released in ways that let developers worldwide download and run them. For researchers in the developing world working on modest computers, that matters a great deal.

But "openly released" and "truly open" are not the same thing, and that distinction is now the subject of a sharp debate.

What is GeoGPT and why does it matter?

GeoGPT is an AI system built for geoscience research by Zhejiang Lab, a Chinese state-backed research institute. At July's World AI Conference, it was held up as a model of open, jointly governed science, with governments in the developing world invited to treat it as a shared resource.

The problem: it doesn't meet the standard definition of "open" that independent experts and a recent UN report have endorsed.

Under the model openness framework, a genuinely open AI system must release its model weights (the internal settings that make the AI work), its training data, and its source code. GeoGPT releases only the weights, and even those come with conditions: they sit on top of Alibaba's Qwen model, which carries licences that don't comply with the Open Systems Interconnection standard, a widely recognised benchmark for open software. Training data and source code remain locked. The committee that supposedly governs the project answers to Zhejiang Lab itself.

That's less "open science" and more "open-ish, on our terms".

Our 27 July story on the first US-China joint statement backing open AI shows how much political weight the word "open" now carries, which makes precision about what it actually means more urgent than ever.

Is this just a China problem?

Not at all, and the researchers raising the alarm are careful to say so. Academics writing in response to a piece by China's ambassador to the UK argue that the gap between "open" as a marketing word and "open" as a technical standard runs across the whole industry.

Many Western labs also release model weights while keeping training data locked away. The push for shared standards that any country's AI must meet to claim the label applies everywhere.

For ordinary users, the practical point is this: when an AI tool is described as "open", ask what that actually covers. Can anyone inspect the data it learned from? Can anyone audit who controls it? Vague answers mean the word is doing a lot of heavy lifting.

Common questions

Why does it matter whether AI training data is public?

Without access to training data, nobody outside the lab can check whether the AI learned from biased, inaccurate or restricted material. That transparency is one of the main ways researchers and regulators hold AI systems to account.

What is the model openness framework?

It is a standard for judging how genuinely open an AI system is, covering weights, training data, source code, and governance structure. A recent UN report endorsed it as a benchmark, and more international bodies are beginning to use it when evaluating AI tools promoted for global use.