It is unlikely Meta will be the last to emerge with findings of models showing they have, as Prof Woodward puts it, “gone to school” – and learnt our own ways of finding and exploiting gaps in systems.
For some, these episodes point to clear security failures on the part of AI companies leading the charge on this game-changing, era-defining tech.
For others, they are merely another vehicle for tech firms to hype up their powerful models and compete with rivals.
For me, both theories hold some grain of truth.
But in rearing their head one after another, these events have nonetheless spurred fears about AI’s capabilities and where these are headed as developers forge ahead.
And the question inevitably moves to what regulators can and should do next.
Michael Birtwistle, associate director at the Ada Lovelace Institute, makes the point that the UK lacks legal incentives for AI firms to prevent systems from developing capabilities which could pose dangers, and that there are no repercussions if testing protocols fail.
More broadly, Dr Imogen Stead, AI policy manager at the Centre for Long-Term Resilience, told the BBC that with opportunities to test frontier AI systems narrowing for many, governments should follow the UK in setting up dedicated institutes for testing.
Improving third-party evaluations with initiatives such as a “trusted tester scheme” for the most risky types of challenges could also be used to limit adverse impacts, she said.
Rather than fear an AI-cyber apocalypse in the meantime, Prof Woodward says, “it’s a case of ‘keep calm and fix stuff'”.
Additional reporting by Philippa Wain and Imran Rahman-Jones
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