With the public release of large language models like Chat GPT putting Artificial Intelligence (AI) firmly on our radar, this episode explores what benefits this technology might hold for statistics and analysis, as well as policymaking and public services.  Joining host, Miles Fletcher, to discuss the groundbreaking work being done in this area by the Office for National Statistics (ONS) and across the wider UK Government scene are: Osama Rahman, Director of the ONS Data Science Campus; Richard Campbell, Head of Reproducible Data Science and Analysis; and Sam Rose, Deputy Director of Advanced Analytics and Head of Data Science and AI at the Department for Transport.  Transcript MILES FLETCHER Welcome again to Statistically Speaking, the official podcast of the UK’s Office for National Statistics. I'm Miles Fletcher and, if you've been a regular listener to these podcasts, you'll have heard plenty of the natural intelligence displayed by my ONS colleagues. This time though, we're looking into the artificial stuff. We'll discuss the work being done by the ONS to take advantage of this great technological leap forward; what's going on with AI across the wider UK Government scene; and also talk about the importance of making sure every use of AI is carried out safely and responsibly. Guiding us through that are my ONS colleagues - with some of the most impressive job titles we've had to date - Osama Rahman is Director of the Data Science Campus. Richard Campbell is Head of Reproducible Data Science and Analysis. And completing our lineup, Sam Rose, Deputy Director of Advanced Analytics and head of data science and AI at the Department for Transport. Welcome to you all. Osama let's kick off then with some clarity on this AI thing. It's become the big phrase of our time now of course but when it comes to artificial intelligence and public data, what precisely are we talking about?   OSAMA RAHMAN So artificial intelligence quite simply is the simulation of human intelligence processes by computing systems, and the simulation is the important bit, I think. Actually, people talk about data science, and they talk about machine learning - there's no clear-cut boundaries between these things, and there's a lot of overlap. So, you think about data science. It's the study of data to extract meaningful insights. It's multidisciplinary – maths, stats, computer programming, domain expertise, and you analyse large amounts of data to ask and answer questions. And then you think about machine learning. So that focuses on the development of computer algorithms that improve automatically through experience and by the use of data. So, in other words, machine learning enables computers to learn from data and make decisions or predictions without explicitly being programmed to do so. So, if you think about some of the stuff we do at the ONS, it's very important to be able to take a job and match it to an industrial classification - so that was a manually intensive process and now we use a lot of machine learning to guide that. So, machine learning is essentially a form of AI.   MILES FLETCHER So is it fair to say then that the reason, or one of the main reasons, people are talking so much about AI now is because of the public release of these large language models? The chat bots if you like, to simpletons like me, the ChatGPT’s and so forth. You know, they seem like glorified search engines or Oracles - you ask them a question and they tell you everything you need to know.   OSAMA RAHMAN So that's a form of AI and the one everyone's interested in. But it's not the only form – like I said machine learning, some other applications in data science, where we try in government, you know, in trying to detect fraud and error. So, it's all interlinked.     MILES FLETCHER When the ONS asked people recently for one of its own surveys, about how aware the public are about artificial intelligence, 42% of people said they used it in t