Elliot Jones, Senior Researcher, Ada Lovelace Institute, writes:

Efforts such as the UK’s AI Safety Summit, and the follow-up AI Seoul Summit, have aimed to start an international discussion around AI safety and have led to the creation of national AI safety institutes in the UK, the US, Japan and Canada. There is a shared ambition to create an international AI safety network, and these institutes have begun to sign bilateral cooperation agreements. However, there is not currently a single, coordinated global institution seeking to promote or research safer AI. Recent research has explored how different existing models for international governance might be applied to AI, including whether institutions such as the Intergovernmental Panel on Climate Change (IPCC) or the International Atomic Energy Agency (IAEA) have features that could be borrowed or adapted for use in this emerging field.

One increasingly prominent proposal, circulating among some academics and policymakers, advocates the creation of an international coalition for AI research inspired by the scale and collaborative spirit of CERN, the European Organization for Nuclear Research. After the devastation of the Second World War, there was an effort to rebuild European science. Leading scientists, including the Danish nuclear physicist Niels Bohr, lobbied European governments to establish an international laboratory devoted to particle physics. In 1954, CERN was established under the umbrella of UNESCO. CERN is publicly funded by 23 member states (22 European states plus Israel).

CERN is both an international institution and a laboratory. It is famous for discoveries like the Higgs boson and for being the birthplace of the World Wide Web. Its primary function has been to provide the powerful and prohibitively expensive infrastructure and hardware – most notably the Large Hadron Collider – needed to conduct particle physics research. CERN has historically focused on fundamental science rather than on developing technical standards or benchmarks. Its significant resources have enabled it to fund and broker multinational research collaborations. In addition, CERN has been an explicit source of inspiration in the institutional design of organizations in molecular biology and astronomy. For these reasons, some people have argued that a similar institution could tackle the complex challenges of AI safety.

CERN’s broader legacy has been in enabling nations to work together on expanding scientific knowledge. Constructing its particle accelerators and detectors required member states to pool expertise and funding. This allowed them to achieve a scale and depth of scientific work that no single country could have reached alone. CERN represents the post-war ideal of science beyond borders in the service of discovery and peace.

If a CERN-like organization for AI were to exist, with the function of coordinating international AI safety research, it would require several features. First, as with the actual CERN’s particle accelerators and supercomputers, a CERN-like body for AI would need its own technical infrastructure to support computational research. This could include physical infrastructure such as data centres, high-performance computing resources, networking systems, and laboratory facilities tailored to AI work.

Social and organizational infrastructure would be needed to provide operational support, including to manage relationships with commercial labs and nation states, make platforms available for open and innovative research communication, and secure sustainable funding for international research networks and collaborations. A CERN-like body might also foster more interdisciplinary and international research collaboration on AI risks, enabling greater involvement of researchers from countries that are otherwise lacking in computational resources.

If this new organization were to study the safety of frontier AI models, it would also require privileged, structured access to state-of-the-art AI models from industry labs, and access to underlying ‘training’ datasets – used to train AI systems in different capabilities – and other critical materials relating to each model’s design and operation. Leading labs, including OpenAI, Google DeepMind and Anthropic, have already made voluntary commitments to open their models to select researchers for the purposes of safety and independent evaluations, though it remains unclear how meaningful these commitments will be unless underpinned by hard regulatory requirements.

However, a CERN for AI might be in a unique position to broker access to cutting-edge AI systems, allowing researchers to test and compare the safety, biases and robustness of models beyond what any single lab could achieve independently. The convention that underpins CERN grants it status as an intergovernmental organization, with the privileges and immunities that come with that, and provides for direct contributions from governments; all this insulates it from political pressures in a way not possible for even national labs. [Continue reading…]