Season Nine of Data Malarkey – the podcast about using data, smarter – has a satisfying shape to it: not a victory lap for data, but a clear-eyed tour of what using data smarter looks like when the world is messy, incentives are misaligned, and technology is moving as quickly as it does today. In the season wrap-up, host and Master Data Storyteller, Sam Knowles, threads together a set of conversations that share a common concern: if data is to be useful, it must remain trustworthy, human, and fit for purpose.
The season opens with Kelly Beaver, Chief Executive of Ipsos in the UK and Ireland and a leading figure at the Market Research Society (MRS). Her focus is the MRS’s Campaign for Better Data, positioned as a practical response to the opportunities and risks created by widespread, increasingly casual use of artificial intelligence in research.
Beaver is clear that AI can improve work that matters: translations, analysis of large data sets, and the identification of emerging trends. But she is equally clear about what can go wrong when AI is adopted without discipline: survey fraud becomes more sophisticated; synthetic data can drift from reality if it is not grounded in high-quality real data; and, reputations can be damaged when credibility and trust are treated as optional extras.
Her most memorable contribution is an analogy that lands because it is both accessible and precise: “ultra-processed data”. Like ultra-processed food, it may be cheap, convenient, and quick to produce, but it can also be full of artificial additives and lacking in the “nutrients” of good research. For Beaver those nutrients are transparency, representativeness, and an auditable link back to real human experience. The MRS’ Campaign for Better Data, in this framing, is the whole-food movement for insight.
From there, Angus Fletcher, Director of Story Science at the Ohio State University and author of the 2025 best-seller, Primal Intelligence, offers a different lens on what humans do well and will always do better than AI.
Fletcher argues that “narrative cognition” – story thinking – is how we invent new plans in uncertain (i.e. low data) environments. He breaks it into four interacting powers: Intuition (spotting anomalies), Imagination (turning them into possible paths), Common sense (matching plans to context), and Emotion (choosing what fits our own life story). The implication is quietly challenging: in domains with patchy data, story thinking is not a weakness to be managed; it is a capability to be cultivated. And this is a domain where humans will always dominate AI.
The season also steps away from the technology debate to examine the conditions that make better thinking possible. Kerry Watkins, who runs the Brighton-based agency Social for Good, describes her journey into digital wellbeing that begins as parenting curiosity and becomes professional purpose. Her 24/six concept – a pushback against “always on” culture – is rooted in lived practice: digital detox experiences in the company of Data Malarkey alumna Anastasia Dedyukhina, the discomfort of boredom, and the return of what she memorably calls a “sparkly brain” when the noise subsides.
A parallel concern with standards and repeatability runs through conversations with Stephen Waddington. With an engineering background, Waddington makes the case that communications often lacks respect for the kind of scientific process that underpins credibility elsewhere. His cheeseburger analogy is funny precisely because it is serious: consistency and systemisation McDonald’s-style may not be glamorous, but they are how organisations scale trust. And when it comes to influence, his conclusion is simple: data gives a story foundations, but nobody is persuaded by an Excel spreadsheet alone.
In the greatest hits episode, Angela Balakrishnan brings a regulatory perspective grounded in public trust. As Executive Director at the UK Information Commissioner’s Office, she explains how data protection hinges on fairness, accountability, and human impact, highlighting campaigns that show data breaches are never “just admin errors”.
Finally, AI Pathfinder and TED Talker, Susan Etlinger returns the season to first principles: data does not create meaning; we do. She argues for humility in the face of powerful tools and reminds us that facts, like data, have no agency. They cannot defend themselves from misuse.
Across this latest season’s guests with hugely varied backgrounds and experience, the point converges: better data is not just cleaner numbers. It is a set of choices – ethical, practical, and human – about how we collect, interpret, and act.
This is how we can – in the words of the legendary David Byrne – start making sense.
—
The first draft of this blog was written by ChatGPT, using a transcript of the episode and an ever-refined prompt. It was then edited by real humans.