How is AI going to change science?
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Hello, welcome to Inside Science from the BBC World Service with me, Tom Whipple. You may have thought that dinosaurs were wiped out 66 million years ago, but this fossil expert argues they still live among us, in a way. Birds are dinosaurs. They're just one group of strange dinosaurs that got small, evolved feathers and wings, started to fly. And so that means part of the dinosaur family tree lives on today. That fascinates me. Also, proposals to change details in an obscure White House document are raising red flags in science circles about their future.
Every discretionary grant will now be required to go through approval by a political appointee who will determine whether or not that particular grant demonstrably advances the president's policy priorities.
And we'll have the best of the week science journals picked over by journalist Caroline Steele. Caroline, what have you got?
I've got some news about doing laundry in space. Excellent, excellent news.
I like my astronauts to be clean. But first, before all that, there is a new scientist coming to the lab. It is like a postdoc, except it's also, with the greatest respect to postdocs, not like a postdoc.
The best co-worker in the lab because it's across every single database and all the literature.
This scientist will never turn up hungover. They will never spend the morning browsing the graduate jobs section.
Helping with everything without needing to progress one's career.
It will never turn up in tears after having broken up with its girlfriend.
It needs no pastoral care from me.
It is, as you've probably guessed, an AI scientist. All the big AI companies are trying to find ways in which AI cannot merely be a tool for science, but something else too. A thinking, reading, perhaps even analysing assistant. Is this the future of research science, an indefatigable partner that has read all the literature? Or is it just another way of introducing hallucinations into that literature? We spoke to Professor Claire Bryant from the University of Cambridge. She was one of a handful of researchers around the world given early access to Google's latest AI system, one that it thinks will be part of a new revolution in how science itself is done. She collaborated with Google co-scientist to hunt for the molecular switches that cause severe diseases in humans when pathogens leap between species.
They basically said it would be a really great aid in the lab. And this is what it proved to be because it's only as good as the questions that you ask it. So we were able to go in and ask some very, very specific questions. And then it gave us some answers back. We would then quality control the data out and we'd say, well, you know, we've got preliminary data, which says that that observation is not quite correct. And then we were able to go back, feed that data into co-scientists. and then get more answers back. And as we refined the output that co-scientists was giving us alongside our preliminary experiments, then we were able to refine more and more of the hypothesis such that we could get down to a specific protein and the amino acids in that protein that differ between humans and birds.
And that's what we're testing at the moment. So it was pretty exciting, really, because Number one, it was able to identify specifics at that level in a way that we all thought was very logical. And number two, it prioritised a protein that we would have got to eventually in the lab, but would not necessarily have been where I started. And that's actually really exciting as well. So it's been a lot of fun and really, really helpful, I think.
Can you give a sense of how much time you think it's saved?
I am probably two years ahead of the game on my graph. If it's right, of course. We won't know until we experimentally validate it. I suspect it is. But if it's right, it would have saved me two years of work.
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