Episodes
301
Latest episode
Sep 2026
Language
EN-GB
Stories from a social enterprise that uses mathematical sciences in impact-oriented work around the world. Our experiences range from helping some of the world's poorest farmers get value from data, to enabling academics to use AI responsibly in their teaching. We never know what our next task will be but the last 6 years have shown that it is likely to lead to a story.
Continuing their reflections on 20 years of research methods support, Lily and David explore the value of observational studies in understanding complex systems. Through examples from agricultural research in West Africa, they discuss how looking beyond experiments and surveys can reveal the hows and whys behind people’s choices, generating insights and research questions that might otherwise be missed.
For the 300th episode of the IDEMS Podcast, David and Kate discuss IDEMS’ first patent and the ideas behind it. They explore how rethinking some of the foundations of how technology is built could make it easier to reuse and adapt across different contexts, and how AI is creating new possibilities for technology that can respond to the needs and decisions of the people using it.
David and Kate make the case for funding IDEMS as it takes its technology and innovation to the next stage. They explain why building a different digital future requires alternatives to conventional models of technology and investment, and invite people to help fund an approach that puts social impact, distributed ownership and long-term mission at its heart.
Michele and David explore two different approaches to building AI systems: tools that enable experts to work faster and more effectively, and tools designed to help more people develop and apply expertise. Drawing on Michele’s work building multi-agent systems for STACK, they discuss how AI can remove technical barriers while keeping human knowledge, judgement and meaningful contribution at the centre.
Lily and David reflect on a new world map that reveals just how much larger Africa is than conventional maps make it appear. They explore why familiar maps distort the size of countries and continents, the mathematics behind different map projections, and why representing Africa at its true scale matters for how we see and understand the continent.
Prompted by the recent potential AI-generated proof related to the Navier–Stokes problem, George and David reflect on what this could mean for mathematics and mathematicians. They explore the role of proof in advancing mathematical knowledge, what might change if AI becomes increasingly capable of producing proofs, and why mathematics has always been about more than solving problems alone.
Following their reflections on climate data rescue, James and David explore how the challenges of making rescued data genuinely usable are playing out in Zambia and Zimbabwe. Through their experiences working with meteorological services in both countries, they discuss the work needed to improve data quality, bring valuable historical records back into use, and build sustainable processes for keeping them usable over time.
James and David reflect on their experiences supporting climate data rescue across several countries. They discuss why preserving historical climate records is increasingly important for understanding a changing climate, and why rescuing data is only truly valuable when it can be put to use, exploring what it takes to bridge the gap between data rescue and real-world applications.
Continuing their reflections on 20 years of research methods support, Lily and Roger explore the often-overlooked problem of zeros in real data. Through examples from agricultural research, they discuss why understanding what zeros represent can change how data is summarised and reveal important patterns that might otherwise be missed.
Santiago and David discuss recent progress towards integrating STACK assessment into IDEMS’ open statistics textbooks. They explore how AI is helping match existing questions to textbook content, the work involved in adapting and improving those questions, and how richer forms of assessment can help students develop a deeper understanding of statistical concepts.
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