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As AI becomes a daily helper for research managers, institutions are awaiting EU guidelines and learning from one another

Since the ‘AI made in Europe’ strategy launched in February 2020, the US has pulled further ahead. The EU’s problem is a lack of scale and focus. The answer is to adopt CERN’s approach to running large, coordinated and highly ambitious projects

Forty new rare disease programmes entering the clinic over the next decade. This is the goal of a new collaboration between Oxford University and the Harrington Discovery Institute, which aims to put up to £200M into getting projects out academic labs and into clinical development  

European and Japanese scientists will fine tune their scientific models on each other’s machines, hopefully boosting performance and future-proofing code. It’s the latest push from Brussels to create stronger research links with ‘like-minded’ democracies

Two scale-ups at the nexus between academia and industry are helping EIT Digital revise its masters’ programmes and keep pace with the fast-moving fields of cybersecurity and robotics

Politicians must not be allowed to harness fears around artificial intelligence to divide people, says Dragoș Tudorache MEP, who is leading Europe’s charge to regulate this powerful technology

A dedicated unit, a debate in the European Research Area Forum and pilot projects are in the works, as the Commission looks to set European guidelines for science’s AI revolution. Now member states need to ‘wake up’ to ensure rules don’t diverge

Shared values and principles did not stop the US and Europe going down different paths in data protection legislation. There is a risk that despite moves to promote harmonisation the same thing will happen in AI

As AI tools spread in the scientific world, we risk the tech giants coming to dominate the resulting ‘meta’ science. It’s time to ensure public research stays in the public sphere, argues Ramon Wyss of KTH

Tools like ChatGPT can give instructions on how to find, synthesise and order deadly pathogens, albeit incomplete ones. Biologists now want more involvement in the training and testing of AI models, while some worry that science’s culture of openness might need to change