Upcoming William Guy Lecturers 2025-26
The theme for the coming academic year (1 August 2025–31 July 2026) is Statistics and AI.
The lecturers will be aiming to inspire the next generation about the importance of statistics and data to the world around us. This year we seek to raise the profile and demonstrate the importance of statistics in AI.
The speakers will be delivering talks on a broad range of topics relating to AI – explaining how statistics underpins AI and drives the AI we see in everyday life (eg entertainment platform recommendations), as well as exploring ethical and environmental considerations relating to AI, eg bias and how to assess if algorithms are fair.
Find out more about the 2025-26 lecturers and their talks below. Lecturers will be contactable from 1 August and their talks will be available on this page ahead of the start of the academic year.
- Rebecca Duke, Principal Data Scientist at the Science and Technology Facilities Council (STFC) Hartree Centre, Cheshire, William Guy Lecturer for ages 5–11 – Little Bo-Peep has lost her mother duck – what nursery rhymes teach us about AI.
- Jennifer Hall, RSS Data Science and AI Section committee member, London, William Guy Lecturer for ages 11–6 – From data to decisions: how AI & stats solve real-world problems.
- Arthur Turrell, economic data scientist and researcher at the Bank of England, London, William Guy Lecturer for age 16+ – Economic statistics and stupidly smart AI.
Rebecca Duke – William Guy Lecturer for ages 5–11
About Rebecca
Rebecca is a Principal Data Scientist at the Science and Technology Facilities Council (STFC) Hartree Centre. She supports companies in implementing data science applications to improve business performance across a range of industries including the energy sector, retail, and creative industries. Her public outreach experience includes supporting large public events, working with local primary schools and facilitating work experience placements.
Rebecca’s talk: Little Bo-Peep has lost her mother duck – what nursery rhymes teach us about AI.
The introduction to the talk will cover the types of AI that children might encounter, including generative AI systems such as ChatGPT.
We will then use nursery rhyme lyrics to build our own generative AI. We will start with a simple algorithm which picks the next word based on the most popular combinations of words. We will increase the complexity using random chance and then implement a common AI algorithm. This will show how by using statistics, we gradually improve our AI nursery rhyme.
The last section will discuss some of the positive and negative aspects of generative AI to help children to become more informed and responsible users of the technology.
Jennifer Hall – William Guy Lecturer for ages 11–16
About Jennifer
Jennifer has extensive experience applying data science and analytics to real-world challenges across a wide range of industries, including finance, travel, healthcare, and insurance. This breadth of experience has deepened Jennifer’s understanding of how responsible data-driven solutions can make a tangible impact on both business outcomes and society.
As a long-standing committee member of the RSS’s Data Science and AI Section, Jennifer has presented at a number of RSS events and is currently leading a Data Science and AI practitioner interview series. Through this work, Jennifer champions the sharing of practical insights and real career journeys to inspire the next generation of data professionals.
A passionate communicator, Jennifer is committed to making complex technical and AI concepts not only understandable, but engaging and relevant to a range of audiences. Whether through public speaking, mentoring, or outreach, Jennifer strives to bridge the gap between cutting-edge analytics and everyday understanding – helping others see the value of data in shaping the world around them and their own career paths within it.
Jennifer’s talk: From data to decisions: how AI & stats solve real-world problems
How does AI forecast the weather, diagnose diseases, and help with business decisions? The answer lies in the powerful partnership between statistics and AI. Together, they help us spot patterns, understand data, and make better decisions.
In this interactive session for students aged 11–16, we’ll explore what AI really is – and look at real-world examples of how it’s being used today. Students will discover why statistics is essential for training AI algorithms, and how data helps machines “learn”.
Through a hands-on activity, students will step into the role of data scientists as they train a type of simple AI algorithm called a decision tree. By the end of the session, students will be able to:
- Define what AI is and give examples of its real-world applications
- Explain why statistics is needed in AI
- Train an AI model to make basic predictions using a business case study.
Arthur Turell – William Guy Lecturer for age 16+
About Arthur
Dr Arthur Turrell is an economic data scientist and researcher at the Bank of England. He is passionate about bringing applied mathematics and statistics to a wider audience – because why shouldn't everyone get to enjoy the fun!?
Arthur is very active in the AI and data science community: he is the former Deputy Director and Acting Director of the UK's Data Science Campus, hosted at the Office for National Statistics, he has released the free online textbooks "Coding for Economists" and "Python for Data Science", and he has published open source software. The topics covered by his research are unified by applied mathematics and statistics: they range from statistical distributions in physics, to the gender pay gap, to using AI to forecast the economy. He was also lucky enough to be asked to choose the elements of Alan Turing's work to feature on the £50 note.
Arthur's outreach activities have taken him to schools, lecture halls, the internet, television, and even some pubs! He has also written a popular science book, The Star Builders: Nuclear Fusion and the Race to Power the Planet about his work in physics. He is particularly excited about reaching demographics who might not normally think that maths and statistics is for them.
Arthur’s talk: Economic statistics and stupidly smart AI
Our statistics are under pressure! It's harder to count the things that we mostly produce today, like tourists' hotel stays and business services, than it was to count the things we used to make, like crops and clothes.
This is Bad News as these "economic statistics" are part of our country's critical infrastructure, like the roads or water pipes: they are used to inform everything from how the government spends its money to whether men and women are paid equally well.
What can we do? In this talk I'm going to show you how clever use of AI can improve statistics and help us make sense of our nation. Amazingly, AI is itself built on maths, and this gives it superpowers when it comes to dealing with numbers.
We'll see how AI can count cows from space, read between the lines of newspaper stories to predict where the economy will go next, and even tell whether you're a lamp post or a person — more useful for statistics than you might think!
Of course, like all technologies, AI can be good or bad. So we'll also see how AI is only "stupidly smart": like with a mischievous genie, you have to be very careful what you wish for. And, to cap it all off, I'll let you in on the secret of how getting to grips with AI could win you millions of dollars.