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UK and US sign agreement on AI safety testing

03/04/24
Hand holding AI icon
Image source: istock.com/Sutthiphong Chandaeng

The UK and US have signed a memorandum of understanding to work together to develop safety tests for AI models.

The agreement, signed by UK Technology Secretary Michelle Donelan and US Commerce Secretary Gina Raimondo, follows through on commitments made at the AI Safety Summit last November.  

It will involve the AI safety institutes of the two countries working to align their scientific approaches and to accelerate the development of robust suites of evaluations for AI models, systems and agents.

They intend to perform at least one joint testing exercise on a publicly accessible model. They also intend to explore the possibilities of personnel exchanges between the institutes.

In addition, they have committed to develop similar partnerships with other countries to promote AI safety across the globe. 

Landmark moment

Donelan said: “This agreement represents a landmark moment, as the UK and the United States deepen our enduring special relationship to address the defining technology challenge of our generation.   

“We have always been clear that ensuring the safe development of AI is a shared global issue. Only by working together can we address the technology’s risks head on and harness its enormous potential to help us all live easier and healthier lives.

“The work of our two nations in driving forward AI safety will strengthen the foundations we laid at Bletchley Park in November, and I have no doubt that our shared expertise will continue to pave the way for countries tapping into AI’s enormous benefits safely and responsibly.”

Raimondo said: “This partnership is going to accelerate both of our Institutes’ work across the full spectrum of risks, whether to our national security or to our broader society. Our partnership makes clear that we aren’t running away from these concerns – we’re running at them.

“Because of our collaboration, our institutes will gain a better understanding of AI systems, conduct more robust evaluations, and issue more rigorous guidance.”

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