When Technology Goes Wrong: The Missed Opportunity in Financial Services, with David Pool

Episode Title: When diversity gets left behind: DEI failures in tech 👤 Guest: Mahima Sukhdev, Chief Growth Officer, GIST Impact Mahima works at the intersection of sustainability, equity, and technology - helping organisations measure their real-world impact through data and analytics.🧠 Episode summary: In this episode, host Paddy Dhanda explores how the tech industry’s failure to prioritise diversity, equity and inclusion (DEI) has led to deeper systemic issues - from biased algorithms to inaccessible products. Mahima help us to shine a light how impact measurement can drive accountability, why DEI is still treated as optional, and what it will take to shift the narrative. 💡 Key topics: - Why DEI is still seen as a “nice to have” in tech - The difference between intention metrics and impact metrics - How flawed metrics can lead to flawed behaviours - Real-world examples of product failures due to lack of diversity - The role of ESG frameworks in driving DEI accountability - What individuals can do to challenge bias in the workplace - How AI is accelerating social impact measurement 📌 Notable quotes: “Until you put the right data into the hands of decision makers, you’re not going to shift the system.” “DEI done badly is a reputational risk. Done well, it’s a strategic advantage.” “Checking your bias isn’t a burden - it’s a way to be present.”  This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit qaltd.substack.com

Episode title:  The cyber skills crisis: When the firewall isn’t enough 👤 Guest:  James Stanger, Chief Technology Evangelist, CompTIA  Globally recognised expert in cybersecurity, open source, and workforce development. Leads global conversations on tech skills, resilience, and the future of work. 🧠 Episode summary:  In this episode, host Paddy Dhanda explores how the tech industry's skills gap is creating vulnerabilities no firewall can fix. James Stanger shares real-world examples of cybersecurity failure rooted in human factors - from undertrained help desk teams to rushed development practices like ‘vibe coding.’  They unpack how poor culture, neglected frontline roles, and lack of foundational training are contributing to breaches - and what organisations can do to build a more resilient workforce.  💡 Key topics covered:  • Why help desk teams are critical to threat detection  • The dangers of vibe coding and slopsquatting  • How AI misuse is creating new attack surfaces  • What CEOs get wrong about AI speed vs safety  • Why curiosity and foundational knowledge still matter  • How to sell cybersecurity careers to creative minds  • The role of data analytics in modern cyber defence  • CompTIA’s new certs: AI Essentials, SEC AI+, SEC OT+ 📌 Memorable quote: “People don’t evaluate as much as they should, because ‘hey, we’re at the speed of innovation here. We’re doing vibe innovation or vibe coding’ or whatever. That’s a problem because if you get sloppy at the beginning, you end up with a whole lot of slop at the end - garbage in, garbage out kind of thing - and you end up with some serious security issues.” This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit qaltd.substack.com

🎙️ Episode Title: "What’s Holding the UK Back from AI Leadership?"👤 Guest: Simon Lambert, Chief Learning Officer, Microsoft UK Leads strategy for digital skills and learning culture, driving initiatives like Microsoft’s Get On campaign and AI skilling partnerships.🧠 Episode Summary: In this episode, host Paddy Dhanda explores the UK's ambition to become a global AI leader in conversation with Microsoft UK's Simon Lambert. They unpack the UK’s AI Action Plan, the critical role of AI literacy, and how tools like Microsoft Copilot are reshaping productivity. Simon shares insights on leadership, lifelong learning, and the evolving human-agent workplace dynamic.💡 Key Topics Covered:·       The UK’s AI Action Plan: infrastructure, adoption, skills, investment·       Microsoft’s £2.5B investment in UK data centres·       The Get On campaign and AI skilling goals·       AI literacy for all - not just technologists·       Leadership’s role in modelling curiosity and enabling learning·       The rise of “agent bosses” and hybrid human-agent teams·       Copilot use cases in healthcare, telecoms, and personal productivity📌 Notable Quotes:“AI skills are going to be a non-optional thing for people.” “Learning is a permanent requirement of work.” “If knowledge is power, then learning is a superpower.” — Jim KwikResources: Check out Microsoft’s Work Trend Index for 2025. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit qaltd.substack.com

Episode Title: Digital Identity: Can the UK Get It Right This Time?Podcast Host: Paddy DhandaGuest: David Birch, Author and Global Authority on Digital IdentityEpisode Summary: Paddy Dhanda is joined by David Birch to explore the UK's renewed push for a national digital identity scheme. They discuss why the previous attempt failed, how technology and public attitudes have changed, and what a successful, privacy-preserving infrastructure could look like today.Key Topics Covered: ✔️ Why the Blair-era ID scheme failed✔️ The difference between identification, authentication, and authorisation✔️ How cryptographic credentials can reduce fraud and friction✔️ The role of banks in identity infrastructure✔️ How AI will reshape identity and customer interactionResources & Links: 🔗 David Birch’s books: Identity is the New Money, The Currency Cold War, Money in the Metaverse🎧 Listen on Substack: qaltd.substack.com▶️ Watch on YouTube: QA Podcast Playlist🎧 Spotify: Listen here🍎 Apple Podcasts: Listen here This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit qaltd.substack.com

Episode Title:A Year of Tech Failures - and What They Can Teach UsPodcast Host:Paddy DhandaGuest:Charlotte Jee, News Editor at MIT Technology ReviewEpisode Summary:In this episode, Paddy is joined by Charlotte Jee to explore MIT Technology Review’s annual list of the worst tech failures. From astronauts stranded in space to AI image generators gone rogue, the episode dives into the most memorable missteps of 2024 — and what they reveal about the state of modern technology.Charlotte shares behind-the-scenes insights into how the list is compiled, the common patterns behind tech failures, and why humility, simplicity, and user empathy are more important than ever.Key Topics Covered:✔️ Boeing’s Starliner disaster and the fragility of modern tech ✔️ AI slop, shrimp Jesus, and the dangers of unchecked generative tools ✔️ CrowdStrike’s outage and the ripple effects of a single update ✔️ Why 80% of cloud features go unused - and what that says about product design ✔️ The growing disconnect between tech creators and usersNotable Quotes:🔹 “Tech loves repeating the same mistakes - and we love pointing them out.” 🔹 “AI will always hallucinate. That’s not a bug - it’s the product.” 🔹 “We’re building faster than ever, but not necessarily better.”Resources & Links:🔗 Read the MIT Technology Review list: MIT Technology Review  🎧 Listen now on Substack, YouTube, or your favourite podcast platform. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit qaltd.substack.com

Episode Title:Why Most Companies Still Struggle with DataPodcast Host:Paddy DhandaGuest:Amma Ainsley, Strategic Account Executive at DatabricksEpisode Summary:In this episode of When Technology Goes Wrong, host Paddy Dhanda is joined by Amma Ainsley from Databricks to explore one of the most common and costly tech failures of our time: the failure to make the most of data. Despite the hype around AI and data-driven decision making, many organisations are still stuck with outdated tools, siloed teams, and a lack of data literacy.Amma shares her insights on how Databricks helps organisations overcome these challenges, the importance of data governance, and how generative AI is reshaping the future of analytics.Key Topics Covered:✔️ Why data maturity varies so widely across organisations✔️ The role of data literacy and organisational culture✔️ How Databricks unifies data without moving it✔️ The impact of generative AI on analytics and decision-making✔️ Advice for leaders looking to become more data-drivenNotable Quotes:🔹 “If you want to thrive and survive in the current economy, you need to be good at data.” – Amma Ainsley🔹 “You can have the best technology, but if the culture isn’t ready, it won’t work.”Resources & Links:🔗 Learn more about Databricks: https://www.databricks.com🎧 Listen now on Substack, Spotify, YouTube, or your favourite podcast platform. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit qaltd.substack.com

Episode Title:When Technology Goes Wrong: The Rise and Demise of Helix – The First Big Dark Web Cryptocurrency MixerPodcast Host:Paddy DhandaGuest:Geoff White, investigative journalist, author of Rinsed, and host of The Lazarus HeistEpisode Summary:In this episode of When Technology Goes Wrong, host Paddy Dhanda is joined by investigative journalist Geoff White to expose the story of Helix – the first major cryptocurrency mixer on the dark web. What began as a tool for privacy quickly became a hub for laundering billions in illicit funds.Geoff, author of Rinsed and presenter of the BBC podcast The Lazarus Heist, explains how Helix operated, how its creator Larry Harmon profited from criminal activity, and how law enforcement finally brought the operation down – with the help of a Google Glass selfie.Together, they explore the murky intersection of privacy, innovation, and criminal exploitation in the digital age.Key Topics Covered:✔️ What crypto mixers are and how Helix became the go-to tool for criminals✔️ How law enforcement traced Larry Harmon using blockchain forensics and Google Glass✔️ The ethical debate around privacy tools and their misuse✔️ The role of regulators and the challenges of policing the dark web✔️ Lessons for tech leaders, developers, and policymakersNotable Quotes:🔹 “It’s the ultimate. It’s a white glove privacy service.” – Geoff White🔹 “Every tech innovation opens up new space for money launderers to do their work in.”Resources & Links:🎙 The Lazarus Heist podcast – BBC Sounds📘 Rinsed by Geoff White – available on Bookshop.org, Amazon, and audiobook platforms🌐 More from Geoff White – geoffwhite.tech🎧 Listen now and discover how a seemingly clever privacy tool became a global criminal enabler. If you enjoy the episode, please subscribe, rate, and review to support the show.Would you like this formatted into a downloadable file or added to a podcast platform description template? This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit qaltd.substack.com

Episode Title: When Technology Goes Wrong: The Shiseido Data Breach and the Rise of Fake Companies  Podcast Host: Paddy Danda  Guest: Graham Barrow, financial crime specialist, co-host of The Dark Money Files, and co-founder of Risk Alert 247 Episode Summary: In this gripping episode of When Technology Goes Wrong, host Paddy Dhanda is joined by financial crime expert Graham Barrow to uncover the shocking ripple effects of data breaches. What begins as a leak of employee data quickly escalates into a sprawling web of fraud, with over 2,000 fake companies created using stolen identities. Graham shares how his obsession with uncovering fake companies led to the discovery of this massive fraud network—and why the UK’s company registration system is a goldmine for criminals. Together, they explore the vulnerabilities in corporate systems, the human cost of data breaches, and what needs to change to stop it. Key Topics Covered:  ✔️ How stolen HR data was used to create thousands of fake companies  ✔️ The role of Companies House   ✔️ Why corporate bank accounts are easier to exploit than personal ones  ✔️ The psychological and financial toll on victims  ✔️ What tech leaders and regulators must do to protect data  Notable Quotes:  🔹 "You can create a company without anybody looking at the details." – Graham Barrow  🔹 "Criminals aren’t interested in stealing data—they’re interested in what the data can do for them."  🔹 "There’s always a victim. White-collar crime isn’t victimless."  Resources & Links:  🎙 The Dark Money Files Podcast  🔍 Risk Alert 24/7   🎧 Listen now to uncover how a single breach can spiral into a nationwide fraud epidemic. If you enjoy the episode, subscribe, rate, and review to support the show.  This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit qaltd.substack.com

Episode Title: When Technology Goes Wrong: The Missed Opportunity in Financial Services with David Pool Description: In this episode, Paddy Dhanda is joined by David Pool, Portfolio Director for Data and AI at QA, to explore the unique challenges facing the financial sector, in the data revolution. From Alpha data to the Internet of Things, and from fintech disruptors to legacy system inertia, this conversation dives deep into how financial institutions can—and must—adapt to stay competitive. What You’ll Learn: What “alpha data” is and why it matters How fintechs are leapfrogging traditional banks The role of AI and data storytelling in financial services Why personalisation is the new battleground How legacy systems are holding back innovation The dangers of “pilotitis” in AI projects Guest: David Pool – Portfolio Director for Data and AI at QA Host: Paddy Dhanda – Head of Product Discovery and Agile Practices at QA  This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit qaltd.substack.com

Episode Title: When Technology Goes Wrong: The 2020 A-Level Algorithm FiascoPodcast Host: Paddy DhandaGuest: Tom Chatfield, philosopher of technology and author of Wise AnimalsEpisode Summary: In this episode of When Technology Goes Wrong, host Paddy Dhanda takes a deep dive into the 2020 A-Level algorithm fiasco—a moment when imperfect technology impacted thousands of students across the UK. Paddy is joined by acclaimed philosopher of technology, Tom Chatfield, to unpack how an algorithm designed to grade students led to controversy, public backlash, and an eventual government U-turn.Together, they explore the unintended consequences of algorithmic decision-making, what this story tells us about the relationship between humans and machines, and the critical lessons organisations can learn about implementing AI-driven systems.Key Topics Covered:✔️ The 2020 A-Level grading system and its flaws✔️ How the algorithm disadvantaged certain students✔️ The balance between fairness, bias, and human oversight✔️ How technology influences education and decision-making✔️ Lessons organisations can take from this storyNotable Quotes:🔹 "Fairness is not just about a statistically sound result—it's about perception and human judgment." – Tom Chatfield🔹 "When technology is deployed without accountability, we risk making decisions that harm real lives."Resources & Links:📖 Wise Animals by Tom Chatfield – Wise Animals – Tom Chatfield 🎧 Tune in now and explore the intersection of technology and fairness! Don’t forget to subscribe, rate, and review if you enjoyed the episode. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit qaltd.substack.com