30/09/2026
As the heads of the major U.S AI labs all gathered in the Whitehouse yesterday I was pleased to speak again to the BBC World Service yesterday on their Newshour programme.
We are racing towards capability when we haven't yet learned to govern what we already have.
These systems are increasingly being used to help build and improve the next version of themselves. The concern isn’t that the machine is suddenly thinking for itself. It’s that capabilities are advancing faster than human oversight processes can understand, test or control them.
These companies are racing towards enormous valuations, and demonstrating that their model is more powerful than their competitors’ is extremely valuable commercially. But there is also a power race happening, and there is a FOMO race.
The more urgent you make AI adoption feel, the more businesses worry that they’ll be left behind if they don’t buy in. That then creates commercial dependency. And once organisations have built their businesses around these systems, the bargaining position between the labs and their customers changes quite dramatically.
Some of these companies are telling us that their technology could pose existential risks that they themselves may not be able to control, while simultaneously arguing that they shouldn’t be responsible for what that technology does.
You can’t have it both ways.
If you are telling governments that your technology is extraordinarily powerful, unpredictable and potentially dangerous, it becomes rather difficult to argue that responsibility disappears when the system takes an action you didn’t specifically instruct.
AI doesn’t get a free pass simply because the technology is new. We do need stronger regulation and more consensus on defining assurance testing standards. But the arbiters of what safe, ethical, responsible AI looks like should not be the labs themselves.
So, why are they asking for more regulation? That's the topic I discussed with Rebecca Kesby.