You may have noticed our brief hiatus. Since publishing our series on AI - which covered the quest for human-level intelligence, data-set risks, ethical considerations and much more - the ongoing deluge of content and commentary on AI in the wider world has continued to accelerate. This year has seen a surge in developments that sit at the intersection of data science and AI: from the growing use of synthetic data to overcome privacy and bias challenges, to the rise of multi-modal models that demand increasingly sophisticated data engineering and integration techniques. The emergence of Agentic AI has sparked new conversations around data provenance, model interpretability, and the reproducibility crisis in machine learning. Meanwhile, the meteoric rise of open-source disruptor DeepSeek triggered stock-market ruptures and industry panic, before cyber-attacks, data leaks and a failed safety test complicated its standing - a parable for the volatility of the space, where data governance failures and safety oversights can rapidly derail innovation. Meanwhile, governments worldwide are investing heavily in national data infrastructure and advanced analytics capabilities, while grappling with how best to regulate a field that is evolving faster than policy can keep up.
The world of data science has been a dizzying place over the last few months, so we took a moment to pause and take stock. In the face of rapid change and constant noise, it felt important to reflect with intention on the role Real World Data Science can and should play in this evolving landscape. Now we’re back - ready to rejoin the conversation with renewed clarity and purpose.
As a project from the Royal Statistical Society, in partnership with the American Statistical Association, we are backed by organisations with nearly two centuries of history in championing sound evidence, rigorous methodology and ethical data use. These values form the foundation of our next phase - distilled into the essential pillars: data, evidence and decision. With an esteemed editorial board representing the cutting-edge of industry and academia, and an international network of practitioners working at the coalface of modern data science, we are uniquely placed to navigate the pace and complexity of today’s data-driven world. Real World Data Science will meet that world in real time with the RSS’s trademark steadying presence, bridging the gap between rigorous analysis and real-time relevance.
We are now returning with a slightly refreshed site, encompassing four editorial sections:
The Pulse - covering news, updates and real-time commentary
Applied Insights - exploring how data science is used to solve real-world problems in business, public policy and beyond
Foundations & Frontiers - unpicking the ideas behind the impact: the concepts, tools and methods that make data science possible
People & Paths - offering strategic reflections on careers, leadership and professional evolution in data science.
You can find the full details of these sections, plus guidance around submitting to them, in our new Call for Submissions.
Despite these updates, we remain committed to providing content that is useful and relevant for practicing data scientists seeking to learn good practices in the field and new potential applications.
The choices we make now will shape how data and AI serve society for years to come. If you’re working on the front lines of these changes, whether through research, practice, or critical reflection, we invite you to share your insights and help us build a future for data science that is thoughtful, transparent and grounded in real world understanding.
- Copyright and licence
- © 2025 Royal Statistical Society
This article is licensed under a Creative Commons Attribution 4.0 (CC BY 4.0) International licence.
- How to cite
- Real World Data Science Editorial Board. 2025. “We’re Back: Real World Data Science Relaunches” Real World Data Science, July 7, 2025. URL