Can data find the first female Formula 1 champion?

Motorsports has long been a male-dominated arena, but what if data could change the story? In this session, Liselott Lading will present how an innovative data-driven approach can uncover and support racing talent irrespective of gender. Developed through a global collaboration between technology experts, motorsport professionals, academic researchers, and non-profit leaders, the initiative aims to identify and nurture young drivers in a fair and transparent way. You will learn how the underlying data model objectively tracks drivers’ progression from karting to Formula 4 later leading to 3, and 2, all the way to Formula 1. Beyond simply collecting data, the project applies AI techniques to recognize talent, monitor performance, and provide meaningful insights over time. Drawing on her direct involvement from the project’s inception, Liselott will offer an “under the hood” look into the challenges, methods, and decisions that shaped its development. She will also highlight how smarter use of resources – like redirecting even a fraction of the billions spent annually in motorsports – could fuel real change. Finally, get a glimpse into the initiative’s future and how data-driven strategies may transform talent evaluation.