What can AI do?

So now we have a better understanding of how AI works: it’s a long training process of fine tuning neural networks until we get the outputs we’re looking for. And it can lead to extremely exciting technologies, not least the language models that have sent big tech companies scrambling to integrate AI systems into their products. But there are other and, for the moment at least, more tangible, real world examples of how it might actually be able to improve our lives. Chris Smith spoke with the tech journalist David McClelland…

David - Artificial intelligence, it isn't really a new technology or concept. You can go back centuries and people first started talking about AI. You look at the birth of modern AI back in the 1940s, 1950s - Turing, for example - but, over the last 18 or 24 months or so, I'd say, I think we've been riding what some would call an "innovation wave", or others might call it a "hype cycle" that's been powered by a subset of AI known as generative AI. And very crudely generative AI is a type of AI that can create new synthetic content, words, pictures, video based upon what it's been trained on. So, for example, I might have a tool like chat, GPT summarise the plot of lame, miserable, the musical in the style of a Shakespearean sonnet. And because that's been trained on, it's ingested the entire works of Shakespeare and it's got various synopses of West End musicals, it'll very quickly come back to me with a tight 14 lines on "Les Mis". But the thing to remember about these AI systems, they aren't really knowledge based. They are statistical. So chatGPT has got no concept of what a sonnet or a West End musical actually is. It is essentially just guessing what word is most likely to come next in a sentence based upon what it's come across before. And the same is true for these generative AI systems that can create amazing photo, realistically, photo realistic images and even videos. These outputs can look incredibly real, but they're also prone to some basic errors like misrepresenting human hands with too many or too few fingers because, again, it doesn't actually understand what a hand is. So my take on the overall AI narrative at the moment, generative AI, is that we are still at this "party tricks" phase. There's a lot of wow moments that look great in presentations and can impress friends indeed scare people as well. But examples of where generative AI is really adding and creating real value at scale to humanity are, are somewhat slower to emerge, but I think we are starting to see them now.

Chris - Yeah, indeed. We are seeing some examples in the medical space, for example, aren't we? We have seen people using this in radiotherapy for cancer treatment in imaging because AI can be taught to be better than we are at spotting certain diagnoses. It's that kind of thing. It does appear to be getting some traction?

David - Yeah, and there's a couple of areas, both like you say, in in medical imaging using more traditional machine learning models where these systems can update their knowledge based upon what they're seeing to identify cancer from scans. Studies have shown that they can perform at least on par with medical experts, faster than humans, which is really important when skilled resources around the world might be at a premium and waiting lists in certain nations are starting to grow as well. Some recent researchers found that AI plus human review of breast cancer screenings - this was a study in Sweden - it can increase the detection rate beyond just humans alone, even two humans looking at it. And there was an NHS trial in Scotland early this year of a tool called Mia, which was able to identify early stage cancers that doctors had failed to identify themselves. And that kind of benefit means much less invasive procedures for a cancer patient later on down the line, a much higher survival rate, but also with generative AI as well. One area of generative AI, which really does seem to be showing some promise, is chatbots. Now, chatbots have had a bit of a bad rap over the years. You know, whether they're used for customer services, for example, and they don't quite understand you, the more modern chatbots that use generative AI capabilities are really showing some potential. So academics at the University of Cambridge have been researching the use of chat GPT chatbots to triage people with potential eye or eyesight problems as a way of deciding which patients need urgently to be seen by specialists. And one of the most recent versions of the chatGPT model, chatGPT-4, it was found to perform better than junior doctors. And it's not expected to replace eye doctors. But these tools can support GPs and other non specialist medical practitioners in helping speed patient care and save people's eyes. And again, maybe that's something that in, in some countries we take for granted the availability of medical staff. But as you start looking elsewhere around the world, even having somebody who can just answer basic questions and steer you to the right course of of medical help can be invaluable.

Chris - It's a bit like the sort of "e-equivalent" of an exoskeleton suit that, you know, you hear people on production lines having these extra suits they can strap on to give them more strength to do bigger jobs. Because computer coders are saying that it's taking some of the grunt out of relentlessly recoding, or coding up bits of work; that people have already solved that problem, but instead of having to go and find that solution, string it together in the right way, you just tell a chatGPT type system, "go and get this and assemble me some code to do the following job." And it does it.

David - Developers are finding generative AI and have done for, for a few years now, incredibly useful. And given that the semantics of computer code are fairly rigid, very, very rigid. In fact, it actually plays very much into large language models and generative AI systems hands. It's the same as with some areas of creative work as well. It's that problem of having the blank piece of paper. How do you get started with a particular problem? What does the basic research look like? And whether you are a journalist or whether you are a software developer, being able to type a prompt, and this is what, you know, we're used to typing into a search engine, a search query. When you are conversing with a generative AI system, we, we type in what's known as a prompt. "Create something for me that does this. And it sounds like that," for example. When one is creating those prompts, you can get something back that might get you 70, 80, maybe 90% of the way there. It might not get you all of the way there, but you then as the, as the journalist, you become an editor and you are editing some work and making sure that it is factually accurate, that it, it tells the story that you want to create. And the same with a software developer as well. Does it solve the problem? Are there any gaps in the code? Is there anything that you might need to tweak? You can save so much time doing some of the basic work and it enables you to operate potentially at a, at a much higher level. Some people would, might be concerned that AI will come for their jobs and there is a a saying that it's not that you'll be replaced by an AI, it's that you may be replaced by a person who knows how to use an AI. And what I've been trying to do in my work is to find ways where I can use an AI to help me with some of my more menial tasks. And more often than not, I'm finding it to be very helpful.

Chris - Does it write better than you can?

David - No comment!