In an era drowning in information, how do we separate fact from fiction? This is the burning question at the heart of academic podcasting, a medium that Rob O’Connor, a computer science lecturer and researcher at South East Technological University (SETU), believes holds immense potential. O’Connor, a Waterford native with a background in music and radio, found his way into the world of technology almost by accident. After a stint working abroad, he returned to Ireland during the dot-com bust and eventually pursued an MSc in network management, which led him to a lecturing position at SETU. But it’s his passion for podcasting that’s truly shaping his career today.
But here’s where it gets controversial: While podcasts have exploded in popularity, their potential in academia remains largely untapped. O’Connor argues that podcasts can make complex topics more accessible by fostering a conversational tone, breaking down ideas into digestible steps, and using analogies to clarify concepts. This became especially evident during the Covid-19 pandemic, when the demand for accessible science communication surged, yet disinformation proliferated. And this is the part most people miss: Podcasts excel at communicating uncertainty, a stark contrast to the confident, often misleading narratives of disinformation spreaders. O’Connor emphasizes, ‘We need different ways of speaking with people and providing high-quality information.’
Inspired by his wife, Dr. Jenny O’Connor, who hosts the podcast ‘The Nerve,’ Rob launched his own podcast, ‘The Machine,’ for his students. He’s also involved in ‘9plus,’ a SETU podcast showcasing university research. These experiences led him to pursue a PhD at Trinity College Dublin’s Adapt Research Centre, where he’s developing a framework for academic podcasting—something he calls the ‘7 Ps of podcasting’: planning, preproduction, production, post-production, publication, promotion, and preservation. Boldly, he suggests an EU repository for podcasts, a non-commercial platform to ensure open access and longevity, addressing concerns about data privacy and platform dependency.
Ethical considerations loom large in O’Connor’s work, particularly regarding AI. While he’s focused on automation tools for podcasting, he’s also grappling with generative AI (GenAI) in education. Surprisingly, many of his students express ethical concerns about AI, from data usage to environmental impact. O’Connor challenges the stereotype of computer scientists as ‘tech bros,’ advocating for a nuanced view of AI’s role in academia. He sees AI-generated podcasts as a solution to the ‘crisis of complexity’—the overwhelming volume of scientific knowledge that makes it hard to stay informed. For instance, in the medical field, AI could help professionals keep up with the latest research.
Yet, O’Connor acknowledges the complexity of AI’s role. ‘Truthfully, I don’t think anyone has the answer,’ he admits. What he’s certain about, however, is the value of podcasting. His students are deeply engaged, with one even shouting across campus, ‘When is the next episode out?’ He also involves students in podcast production, fostering interdisciplinary collaboration and soft skills—a critical asset in today’s job market. ‘You can have brilliant ideas, but if they’re locked in your head, they’re useless,’ he notes.
At its core, O’Connor’s work is about amplifying evidence-based science in a noisy world. ‘It’s not about creating more noise,’ he says, ‘it’s about helping people create more useful signal.’ But here’s the question for you: As AI and podcasting evolve, how can we ensure they serve as tools for clarity rather than confusion? Share your thoughts in the comments—let’s spark a conversation!
