Artificial intelligence promises (or threatens) to completely revolutionise the workforce. From manufacturing to healthcare, we’re building machines to make important decisions that will create all kinds of industry efficiencies.
But here’s the thing: artificial intelligence isn’t naturally intelligent. And the machines we’re building aren’t actually smart – yet. But they could be, once we equip them with mathematical reasoning.
This is where Lamiae Azizi comes in. In order to improve robot performance, we need to teach machines to think and interact with the world around them. What data do we need, how do we get there and when does privacy become a concern? Exploring this ethical minefield, Lamiae will discuss what’s being done to develop the next generation of AI-based machines and the moral conundrums that this may present.
For Lamiae Azizi, mathematics has the capacity to transform the world. To her, teaching and learning maths is so much more than just memorising formulas – it’s about applying mathematical sequences to solve exciting real-world problems.
A lecturer in the School of Mathematics and Statistics and the Deputy Director at the Centre for Translational Data Science, Lamiae’s research focuses on developing and applying statistical machine learning models to create personalised solutions, particularly within the healthcare sector.