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Chapter 1: What is the main topic discussed in this episode?
The Pat Kenny Show. With Timber Living Log Cabins. Saturday and Sunday from 10am. On Newstalk. Conversation that counts.
Now, we are welcoming into the studio Professor Luke O'Neill, Professor of Biochemistry at the School of Biochemistry and Immunology at Trinity College in Dublin. Luke, good morning. Good morning, Matt. You're talking about AI. I am, yes. Now, the reason is, I decided, you know, to ask, am I expendable in my job?
So I said to AI this morning, will you write me an introduction for Professor Luke O'Neill?
Chapter 2: How does AI threaten the graduate jobs market?
Yeah, go ahead. And this is what I got.
Today we are diving into the fascinating world of human health and groundbreaking science. Our next guest makes complex biology sound like a gripping thriller. He is one of the world's most influential immunologists. He's a best-selling author, an award-winning communicator, and Trinity College Dublin's own professor of biochemistry.
You know him from his tireless work explaining global health crisis, his infectious enthusiasm for discovery, and maybe even his passion for rock music. Will you welcome to the show the brilliant, the energetic... Professor Luke O'Neill.
That's fake news, Phil. That's not really AI generated. It's amazing. It just shows you somewhat, maybe half accurate. I'm not quite so sure.
I don't think you're quite expendable yet. Even if the facts are kind of there in it, it's not what I would write. No, exactly. I did ask you to do a Pat Kenny version, but it wasn't much. Different. No, no, no.
Isn't it amazing you can do that, though, nowadays? You can just stick things in and get things out.
Where, you know, as someone who's researching something would find it useful is you get a 200-page government document from a department, and you know most of it's puffery. Yeah. So you stick it in and you get the essence. You get the summary. The problem is you might miss nuance somewhere along the way, and that's the difficulty. Or maybe the AI machine will hallucinate. That's the trouble.
That's exactly right. But you've been looking at the principal problems that arise
From AI. Yeah, it's all over the news every time. Even the Pope himself made a speech about AI recently. I think in Forbes magazine this week, which I don't read that often, but it listed all the jobs that are threatened. And that's the fear, isn't it? They reckon 300 million jobs are at risk through AI. Globally. Globally, for example. It's hard to predict these things.
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Chapter 3: What jobs are predicted to be at risk due to AI?
I mean, I mentioned earlier this hallucination by AI, where AI is picking up stuff from God knows where, because it's a large language model. So it's sweeping. It is sweeping. So if it's sweeping lies. Yeah, this is the trouble.
It'll regurgitate lies. We're using it, Papa, and science is the big place that it's gone across. You still need to be an expert to see if it's correct or not. And I can use chat EPT. A third of it's wrong, you know. Now, I can spot that because I'm an expert and I can see what's right. So we'll still need humans with know-how, I suppose, to interpret it.
Earlier on this morning on News Talk, the TED Hour, and there was a doctor on talking about how, you know, reading scans and so on, that AI is so much better than humans are. Now, what happens when it predicts that someone's going to have a heart attack in five years' time? Yeah. the cardiologist can then go and have a look. That's right.
And maybe learn from what AI has, or say, that is a hallucination, that was a glitch in the machine, or whatever.
Yeah, and education, and education, the big thing about education, we have to change, by the way.
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Chapter 4: What are the positive aspects of AI in the job market?
There's a huge transition happening at the moment. They're calling it a new industrial revolution. It's coming, really. What does education do about this, for instance? And in medical education, they're teaching them not just to use AI. There's a phrase, Pat, if you've never skied, you can't talk about skiing.
So in other words, if you're a doctor, you'll still have to do the other stuff as well, to be a doctor anyway, and then bring AI in as a tool that you use.
Is AI principally a diagnostic tool? Or, for example, in your area, is it... a developmental tool. You know, when you were talking about designing proteins or other chemicals, that it can do it in the lab. If it doesn't have test tubes and Petri dishes, it's in the business of predicting if I mix this molecule with that molecule, I'll get something that might work.
But it doesn't actually do the Petri dish.
You still need to do an experiment. And the big paper this week, but on this actually, paper in Nature, where they use an AI system to read the literature on a topic. It was a type of blindness actually called Age-Related Macular Degeneration, AMD. Read all the papers itself. It took six minutes to read the literature. Came up with an idea. design the experiment.
Now, a human did the experiment, put the data back into the AI system and find the account of conclusion. And they found a new drug, actually, it's called Repastudil, which could be useful in AMD. Now, they reckon, Pat, it took the AI system two hours to do all that. It would have taken a human 424 hours to read the literature and design and interpret.
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Chapter 5: What key issues arise from AI usage?
All that part of it would have taken a lot longer than the AI machine. Now, of course, the drug isn't on the market yet. It's still very early. But talk about speeding up the discovery process.
It's funny that on that programme this morning, looking at AI and all the rest, he in passing was talking about the shingles vaccination. And he said, if you got the reduction, you were talking about this last week on this programme, if you got the reduction in dementia vaccine,
and that is being delivered by this shingles vaccine and it was it wasn't a vaccine it was a pill they'd be all over it like a rash they'd be saying this is a great breakthrough because it's a vaccination yeah for some reason it puts people off yeah dead right yeah yeah if you can reduce alzheimer's by 20 with a pill that'd be headline news wouldn't it you know the fact that it's a vaccine doing it doesn't seem to be making the headlines it's a strange business with that no
Now, where else do you see in science this being very useful? We mentioned Alzheimer's, and perhaps there are other molecules that can be produced by an AI deep dive into the literature.
Yeah, now, one issue is it is used in the literature. There's stuff there where they can read all these papers and all this historical stuff, and then get an idea. That's great to me. We read this literature all the time. Anyway, you know, can it really be creative is the question. Like, the really big breakthroughs in science are usually mavericks who think outside the box.
AI is not very good at thinking outside the box because it's looking inside the box, you know. So one question is, again, we'll still need creativity and humans to do it.
I mean, you're not going to have a robot hanging around in the cow bar inventing penicillin, are you?
You've got it. And nor at a conference talking like I do. My main skill for that, when I go to meet someone for a drink and you have a conversation, you get an idea that way from them by talking to them. AI won't replace that necessarily. The big one is data analysis. So one example of my own research, we had a thing with these guys in Edinburgh.
It took this guy about 10 minutes to use AI to assess the data he generated for us. It would have taken, I'd say, a day to analyse all the data with a human being, you know. So again, we're seeing a speeding up of data analysis. Okay, here's the big question for you. Nuclear fusion is always 10 years away. Yes, that's right. Can AI do anything about that?
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