Sep 9, 2026 · 1 hr 2 min · 11 segments
Questions, suggestions, or feedback? Send us a message! Welcome to the Where Shall We Meet podcast. Our guest this week is James Manyika, who is Senior Vice President of Research, Labs, Technology…
James ManyikaGuestBut what I was interested in in your paper was the suggestion that nothing's inevitable.
So yes, there are these predictions and likelihoods, and then they're tested and they're verified.
But when you spoke about the hallucinations, which has had hugely negative press, in this context, those could actually be very productive because they were outside of anything that we were able to predict.
So I suppose for me, there was like a third possibility that... you could enter into this hinterland that isn't human, but that then, as we were saying before, you need to have a sort of interlocutor to be able to translate whatever it was that was being, well, explored, if not discovered, and then sort of fed back to us.
And then that leads to greater questions around whether we then become the minions and we don't really understand anything, which is, I know, the big fear.
And the other thing about predictions is just are we then freighting all of our resources into something that we've decided already, you know, is important.
I can't remember who it was who had a particular paper or link to that, you know, like diseases in Africa, for example, which perhaps didn't receive nearly as much attention as Parkinson's or Alzheimer's.

Yeah, no, that was a paper by Kelly Chibale who was talking about, he wrote a fascinating paper just on drug discovery in Africa and how that can actually enhance possibilities in Africa.

But I think I want to go back to where you started, Natasha, which is hallucinations are a fascinating thing in the context of science in the following way, because hallucinations Typically, people worry about hallucinations in AI systems when you're looking for accuracy.

So when you're looking for accurate facts, accurate data, and you don't want hallucinations.

But at the same time, hallucinations can be a feature as opposed to a bug in the following sense.

When you're trying to explore... unrealized territory or you're trying to be creative.

Actually, hallucinations can be a feature in that sense because they could point you in directions that are interesting that you hadn't thought about that might spark ideas.

David Baker, who also got a Nobel Prize at the same time around proteins, he actually attributes some of the leaps that he made from a few hallucinations that then pointed him in directions he would not have looked at.

And then when he did look there, he was able to inspire his own creativity to come up with interesting designs.

You often see this, for example, even in creative work, when creative artists are using AI systems.

It's a bit like, you know, when you're trying to have a system that makes a prediction, peanut butter and...

Now, if you're trying to write a creative sentence, you may not want peanut butter and jelly.

You may want a more imaginative version, peanut butter and marmalade or something that's creative.

So a system that's trying to make an accurate prediction would have probably come up with peanut butter and jelly.
But what I was interested in in your paper was the suggestion that nothing's inevitable.
So yes, there are these predictions and likelihoods, and then they're tested and they're verified.
But when you spoke about the hallucinations, which has had hugely negative press, in this context, those could actually be very productive because they were outside of anything that we were able to predict.
So I suppose for me, there was like a third possibility that... you could enter into this hinterland that isn't human, but that then, as we were saying before, you need to have a sort of interlocutor to be able to translate whatever it was that was being, well, explored, if not discovered, and then sort of fed back to us.
And then that leads to greater questions around whether we then become the minions and we don't really understand anything, which is, I know, the big fear.
And the other thing about predictions is just are we then freighting all of our resources into something that we've decided already, you know, is important.
I can't remember who it was who had a particular paper or link to that, you know, like diseases in Africa, for example, which perhaps didn't receive nearly as much attention as Parkinson's or Alzheimer's.

Yeah, no, that was a paper by Kelly Chibale who was talking about, he wrote a fascinating paper just on drug discovery in Africa and how that can actually enhance possibilities in Africa.

But I think I want to go back to where you started, Natasha, which is hallucinations are a fascinating thing in the context of science in the following way, because hallucinations Typically, people worry about hallucinations in AI systems when you're looking for accuracy.

So when you're looking for accurate facts, accurate data, and you don't want hallucinations.

But at the same time, hallucinations can be a feature as opposed to a bug in the following sense.

When you're trying to explore... unrealized territory or you're trying to be creative.

Actually, hallucinations can be a feature in that sense because they could point you in directions that are interesting that you hadn't thought about that might spark ideas.

David Baker, who also got a Nobel Prize at the same time around proteins, he actually attributes some of the leaps that he made from a few hallucinations that then pointed him in directions he would not have looked at.

And then when he did look there, he was able to inspire his own creativity to come up with interesting designs.

You often see this, for example, even in creative work, when creative artists are using AI systems.

It's a bit like, you know, when you're trying to have a system that makes a prediction, peanut butter and...

Now, if you're trying to write a creative sentence, you may not want peanut butter and jelly.

You may want a more imaginative version, peanut butter and marmalade or something that's creative.

So a system that's trying to make an accurate prediction would have probably come up with peanut butter and jelly.
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