In response to China's ambassador to the UK, Zheng Zeguang, who celebrated openly released AI models and highlighted Chinese labs like Qwen, DeepSeek, and Kimi as leaders in competition that benefits all, two UK academics have raised critical points about the true nature of openness in AI development. Prof Paul H Cleverley from Robert Gordon University and Dr Claire Jenkins from Wollaton, Nottinghamshire, argue that while China's contributions are commendable, the claim that openness defines its AI ecosystem requires scrutiny.
GeoGPT: A Case Study in Limited Openness
Prof Cleverley points to GeoGPT, a geoscience system developed by Zhejiang Lab, which was showcased at the World AI Conference in Shanghai on 17 July 2026 as a model of jointly governed open science. Despite being promoted to countries as open, GeoGPT would not qualify as open under the model openness framework endorsed in a recent UN report. It releases model weights built mainly on Alibaba Qwen, whose licences are not Open Systems Interconnection-compliant, but it does not release training data or application source code. Furthermore, its governance committee answers to Zhejiang Lab itself, raising questions about independent oversight.
Contrasting Examples of Fuller Openness
To illustrate what fuller openness looks like, Prof Cleverley cites the European Space Agency's Earth Virtual Expert (EVE), which releases its training and evaluation tooling for Earth sciences, and the US non-profit Ai2's OLMo, which publishes everything needed for reproducibility. These examples highlight the distinction between a free hosted service and a genuinely open system. GeoGPT's users route their data through China's legal jurisdiction, creating real dependency and sovereignty risks, which Prof Cleverley argues is a significant concern.
Not Unique to China
Prof Cleverley acknowledges that this is not unique to China, as the US private-enterprise model raises similar concerns. He extends the ambassador's own point: no country's ecosystem is quite as open as its diplomacy suggests. To benefit from the cooperation proposed by Ambassador Zheng, Prof Cleverley advocates for shared openness standards, such as the UN-recommended model openness framework, as the basis for any joint work. He emphasizes that honest measurement, not just the language of openness, is where real partnership begins.
Britain's Distinctive Path in AI
Dr Claire Jenkins offers a complementary perspective, arguing that Britain cannot afford to be a passive consumer of AI while the US and China shape future technologies, but the debate should not be reduced to a geopolitical race. She suggests that Britain's greatest strengths lie not only in its research universities and life-sciences sector, but also in the NHS, public institutions, and a long tradition of ethical inquiry. These provide an opportunity to develop AI that is trustworthy, transparent, and directed towards the public good rather than solely commercial advantage.
Healthcare as a Test Case
Dr Jenkins highlights healthcare as an area illustrating both the promise and the risk of AI. AI can reduce administrative burdens, improve diagnosis, and widen access to care. However, public confidence depends on strong governance, meaningful human oversight, and assurance that patient data serves citizens rather than corporate or geopolitical interests. Recent work by the Medicines and Healthcare Products Regulatory Agency's national commission into the regulation of AI in healthcare has highlighted these concerns, according to Dr Jenkins.
A Call for Democratic Accountability
Dr Jenkins urges Britain to resist imitating either Silicon Valley's market dominance or China's state-led model. Instead, it could offer a distinctive path: AI that combines innovation with democratic accountability, scientific excellence, and social justice. This, she argues, would be a form of leadership worthy of Britain's traditions and one that others might choose to follow.
