The Royal Statistical Society has recently set out a clear and compelling message: AI is Statistics. This simple phrase captures a powerful truth about the foundations, practice, and future of artificial intelligence—and the central role of statistical thinking within it. It is also, of course, intentionally provocative and necessarily simplifies a highly complex and nuanced area.
This nuance and complexity is acknowledged and addressed in the paper itself, but no single publication can fully capture the breadth of perspectives on this topic - which is why we’ve launched a call for submissions to encourage a richer, more multidisciplinary dialogue. We are inviting writers, researchers, and practitioners across disciplines to respond to this theme with original pieces that inform, challenge, and inspire.
We are particularly interested in contributions that:
- Illuminate how statistical ideas underpin modern AI methods
- Explore the relationship between data, uncertainty, and decision-making in AI systems
- Offer case studies of statistics in real-world AI applications
- Examine ethical, societal, or policy implications through a statistical lens
- Challenge or expand the “AI is Statistics” framing in thoughtful ways
- Communicate complex ideas accessibly to a broad audience
We welcome a range of formats, including opinion pieces, explainers, case studies, and thought leadership essays.
This is an opportunity to shape an important narrative, one that positions statistics not just as a supporting discipline, but as a driving force behind trustworthy, effective, and responsible AI.
Help us tell the story: AI is Statistics.
To make your submission, please review our contributor guidelines and email us at rwds@rss.org.uk
- Copyright and licence
- © 2025 Royal Statistical Society
This article is licensed under a Creative Commons Attribution 4.0 (CC BY 4.0) International licence. Thumbnail photo by Virgina Johnson on Unsplash.
- How to cite
- Real World Data Science Editorial Board. 2025. “Call for Submissions” Real World Data Science, April 15th, 20256. URL