The IDEMS Podcast

Michele Pancera and David Stern critically discuss a recent Google paper on AI-augmented textbooks. They consider the paper's proposal of AI-generated personalised learning materials and how it compares to existing deterministic tools like STACK. The conversation highlights the differences between surface-level and deep personalisations, the importance of human involvement in AI processes, and the potential of AI in supporting teachers and enhancing education systems globally. They explore the vision of a customisable, community-driven textbook ecosystem that leverages AI to reduce educational inequalities while maintaining high-quality human interaction.

Access the paper from Google here: https://arxiv.org/abs/2509.13348

Lily and David discuss the often misunderstood concepts of “open” and “open source.” They discuss the origins of these terms within the programming community and how they have expanded into areas such as open data, open science, and educational resources. The conversation focuses on the various types of licenses, including Creative Commons, and their implications for use and reuse.

In this special two-year anniversary episode David and Kate reflect on their journey, from improving audio quality to hosting more expert guests. They explore the essence of IDEMS' work, emphasizing the combination between the IDEMS Collaboratory and CommonTech, as a breakthrough in IDEMS’ narrative, highlighting the challenge of communicating a complex, collaborative vision.

In this episode, Santiago and David delve into the two of IDEMS’ staffing principles: Individual Initiative and Collective Responsibility. They discuss how these principles support a culture where team members can take initiative while sharing responsibility collectively. Highlighting real examples, they introduce a recent breakthrough in implementation of these principles in the form of a tool designed to visualise and manage these principles effectively.

Michele and David discuss the Turing test, and its relevance today. They explore various philosophical questions about intelligence, the limitations of the Turing test, and the ethical dilemmas posed by AI, particularly in the context of self-driving cars. David emphasises the vital role of human observation in the Turing test and expresses skepticism about society's ability to make responsible choices regarding AI regulation.

Michele and David discuss the impact of AI in low resource environments. They discuss the complexities surrounding AI technology, the hype versus the actual value, and the potential for AI to either widen or reduce global inequalities. They consider the need for robust infrastructural and social frameworks, the promise of small language models, and the importance of local ownership in AI development.

Lily and David explore a powerful framework for data analysis: Explore, Describe, Present. They discuss the importance of exploring data to understand its structure, describing data in the context of specific objectives, and effectively presenting insights to various audiences. Highlighting the challenges of modern data analysis, including the role of AI and the influence of tools like the tidyverse and R-Instat, they emphasise the need for structured approaches to make sense of complex datasets.

David talks to Rikin Gandhi from Digital Green to discuss the organisation's innovative approach to integrating AI with farmer support systems. They discuss Digital Green’s approach to working with AI, including the importance of human-in-the-loop systems, the benefits of using multimodal inputs like voice, text, and images, and the advantage of open-source data for tuning AI models to meet local agricultural needs. They also explore the potential and challenges of leveraging small language models to provide tailored support to farming communities and the critical role of local expertise in enhancing AI's effectiveness.

David and Kate delve into the ongoing AI boom, questioning whether it's mere hype or has real substance. They explore the ethical and responsible use of AI, emphasizing the importance of making technology accessible and beneficial to low-resource communities. They argue that small language models could provide specific, efficient solutions. The conversation also touches on the societal impacts of AI, the need for regulatory frameworks, and the potential for AI to democratize technology, moving away from its current gatekept state.

David and Mike discuss Kenya's new competency-based curriculum and a UK-backed campaign to create innovative digital textbooks. They delve into the challenges and potential solutions, highlighting the role of PreText and STACK technologies in revolutionizing education across Africa.

https://www.crowdfunder.co.uk/p/open-digital-textbooks