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Is AI Making Cybersecurity Analysts Less Effective? In this episode of Compromising Positions, we're asking whether thinking is becoming optional. We've spent decades finding new ways to outsource the work our brains used to do. Convenient? Absolutely. But what happens when we get so used to letting technology do the thinking that we forget how to do it ourselves? We explore the growing concerns around AI, cognitive offloading and critical thinking. When AI can structure an argument, write an essay or summarise a mountain of information in seconds, are we actually learning anything? Or are we just getting better at producing things we can't explain? And this isn't just about whether your next university essay is secretly written by a chatbot. There are some serious cybersecurity implications. Security Operations Centre (SOC) analysts are already dealing with alert fatigue, time pressure and burnout. AI promises to take some of that workload off their hands, but what happens when automation makes us less curious, less investigative and more inclined to rubber-stamp whatever the machine tells us? We look at the irony of automation, the danger of humans losing the skills they need when things go wrong, and what happens when everyone relies on the same AI systems, complete with the same blind spots. Because if attackers compromise the very systems we're relying on to detect them, who's left to challenge the machine? In This Episode, We Discuss: Thinking Optional: What cognitive offloading is, why we've always done it, and why generative AI might take things a step further. Are We Getting Dumber? What research into AI-assisted writing, memory and attention suggests about the cost of outsourcing our thinking. The Human Rubber Stamp: Why reviewing AI output isn't the same as understanding it, and how overconfidence in AI can undermine critical judgement. The Cybersecurity Connection: What happens when SOC analysts use AI to manage alert overload, and why faster isn't always better. The Irony of Automation: Why removing humans from routine tasks can leave them less prepared for the unusual, high-stakes situations where they're needed most. Show Notes Special thanks to our episode sponsor, Leeds based AI Consultancy specialising in AI Ethics, Security and Transformation NorthStar Intelligence- From Ideas to Impact. AI that works for people Beware of Metacognitive Laziness: Effects of Generative Artificial Intelligence on Learning Motivation, Processes, and Performance by Fan et al. (2024) The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers by Lee et al. (2025) Automation Bias and Complacency in Security Operation Centers by Jack Tilbury and Stephen Flowerday (2024) Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task by Kosmyna et al. (2025) Google Effects on Memory: Cognitive Consequences of Having Information at Our Fingertips by Sparrow et al. (2011) Cognitive Offloading by Evan Risko and Sam Gilbert (2016) Also, check out our sister podcast Tech Film Noir!

In this special Compromising Positions field trip, we head to Connections UK, a conference dedicated to the art and science of professional wargaming. And no, it’s not about Orcs or Space Marines. We explore what cybersecurity and AI can learn from people who use simulations to test crisis, conflict, disaster response and complex decision-making when there is no single right answer. One of our favourite descriptions from the conference was that a wargame is fundamentally a structured conversation. Put people into a scenario, give them decisions to make, introduce consequences, and see what happens. We look at why wargaming isn't about predicting the future, but about exposing assumptions, testing dependencies and uncovering unintended consequences before they become real-world problems. And, inevitably, we ask what happens when AI gets involved. Because as organisations deploy AI at breakneck speed, we can't write a policy for every possible outcome. But we can rehearse what happens when things go wrong. (Note: We recorded live in the field, so bear with us on some of the audio quality! For the full visual experience, check out the video version over on our YouTube channel.) In This Episode, We Discuss: Wargames Aren't Just for Generals: What professional wargaming actually is and what cybersecurity can learn from it. The Structured Conversation: How putting people into scenarios and forcing decisions exposes blind spots that risk registers and strategy documents can miss. Wargaming in the Age of AI: What happens when AI, autonomous systems and synthetic information enter an already complicated crisis. Rehearsing the Unexpected: Why the goal isn't to predict the future, but to build the organisational muscle to respond when things inevitably go sideways. Special Thanks to Our Guest Interviews at Connections UK: Matt Caffrey – Founder of Connections USA Stephen Box – Vanguard Tactics Robert Grayston – Resilience Officer Chris Webb – Professional Wargamer Show Notes Special thanks to our episode sponsor, Leeds based AI Consultancy specialising in AI Ethics, Security and Transformation NorthStar Intelligence- From Ideas to Impact. AI that works for people Connections UK website Vanguard Tactics - Stephen Box The Games Behind Your Government’s Next War - People Make Games Cybersecurity Lego Game - Decisions and Disruptions Also, check out our sister podcast Tech Film Noir!

AI Isn’t Lying to You, It’s Agreeing With You AI is supposed to be helpful. But what if "helpful" has started to mean "whatever you say, babe"? In this episode, we continue our How Technology Ruined Your Life mini-series by taking a slightly uncomfortable look at AI sycophancy: the increasingly weird tendency of AI chatbots to agree with us, flatter us, validate us and tell us exactly what we want to hear. And let's be honest. We love it. Humans have been falling victim to confirmation bias, echo chambers, authority bias and good old-fashioned validation forever. We like being told we're right. We like feeling clever. We like feeling understood. The problem is that generative AI is basically the world's most attentive people-pleaser, and it never gets tired of us. This episode we look at why large language models become sycophantic, how reinforcement learning and human feedback have encouraged AI systems to be warm, helpful and agreeable, and what happens when those qualities start getting in the way of honesty, uncertainty and actually telling us when we're talking absolute bollocks. Because an AI doesn't necessarily have to lie to you. It can just agree with you. We dig into the GPT-4o sycophancy controversy, reports of AI reinforcing conspiracy theories, grandiosity and unhealthy beliefs, and research into how agreement and flattery can change the way people perceive and trust AI. We also unpack the difference between stance sycophancy - changing an answer to match your beliefs -and demeanor sycophancy, where the machine showers you with "That's an excellent point!" until you're convinced you're a genius. But this isn't just about hurt feelings and chatbot therapy. There is a cybersecurity problem hiding underneath all this agreeableness. What happens when your AI security adviser agrees that your vulnerable code is probably fine? When it reinforces your theory about a suspicious network event? When it approves a dangerously permissive configuration because challenging you would be, well, a bit awkward? AI sycophancy could create new risks around security operations, code review, incident response, social engineering and decision-making, and introduce the idea of "alignment phishing" - where instead of attacking the AI's instructions, an attacker tries to convince the model that they're one of the good guys. Sounds good? You would say that! In This Episode, We Discuss: “You're Absolutely Right!": The difference between stance sycophancy and demeanor sycophancy, and why changing an AI's tone can influence how trustworthy, intelligent and socially present we perceive it to be. The AI Echo Chamber: How personalised, endlessly available AI can remove the natural friction we get from other humans and why an AI that never rolls its eyes at your terrible idea might not be doing you any favours. AI Sycophancy Meets Cybersecurity: What happens when the person asking the security question is already convinced they know the answer. We look at vulnerable code, incident response, security analysis and dangerous configurations and why "sounds good to me" isn't exactly the gold standard for cybersecurity. Can We Teach AI to Tell Us We're Wrong? Why trustworthy AI needs friction, challenge and the ability to say "no"—and why the best AI security adviser might be the one that occasionally disagrees with you! Show Notes Special thanks to our episode sponsor, Leeds based AI Consultancy specialising in AI Ethics, Security and Transformation NorthStar Intelligence- From Ideas to Impact. AI that works for people When Truth Is Overridden: Uncovering the Internal Origins of Sycophancy in Large Language Models byKeyu Wang et al. Social Sycophancy: A Broader Understanding of LLM Sycophancy by Myra Cheng et al. When helpfulness backfires: LLMs and the risk of false medical information due to sycophantic behavior by Shan Chen et al. Be Friendly, Not Friends: How LLM Sycophancy Shapes User Trust by Yuan Sun and Ting Wang Towards Understanding Sycophancy in Language Models by Mrinank Sharma et al. Invisible Saboteurs: Sycophantic LLMs Mislead Novices in Problem-Solving Tasks by Jessica Y. Bo et al. How RLHF Amplifies Sycophancy by Itai Shapira et al. Also, check out our sister podcast Tech Film Noir!

In this episode, we continue our How Technology Ruined Your Life mini-series with "F" Is For FAKE, exploring how artificial intelligence is transforming not only what we see online, but what we believe to be true. From convincing deepfake videos and cloned voices to AI-generated news, fake witnesses, and synthetic social media content, we examine how generative AI is eroding our ability to distinguish reality from fabrication. As humans become increasingly unable to reliably identify AI-generated media, what happens when evidence itself can no longer be trusted? Drawing on the latest research into deepfakes, misinformation, disinformation, and content authenticity, we explore how synthetic media is reshaping cybersecurity, politics, journalism, and society. We discuss why humans are now little better than chance at spotting AI-generated content, the limitations of current verification standards such as C2PA, and why the future of trust may depend less on detecting fakes than proving what is real. We also examine the growing cybersecurity implications of AI-generated deception, from multimillion-dollar CEO impersonation scams and voice cloning attacks to insider threats, identity fraud, authentication failures, and the growing challenge of securing organisations in a world where seeing is no longer believing. If persuasion was the first battlefield of AI, synthetic reality may be the next. In This Episode, We Discuss: The Rise of Synthetic Reality: How deepfakes, AI-generated images, cloned voices, fabricated news reports, and synthetic media are changing the way we consume information, and why "seeing is believing" is rapidly becoming obsolete. Misinformation, Disinformation & The Trust Crisis: The critical differences between misinformation, disinformation, and malinformation, how false narratives spread across social media, and why convincing fakes can continue influencing people even after they have been debunked. Deepfakes Meet Cybersecurity: How AI-powered impersonation is accelerating social engineering attacks through CEO fraud, business email compromise, voice cloning, fake job applicants, identity spoofing, and increasingly sophisticated phishing campaigns that exploit human trust rather than technical vulnerabilities. Can We Still Verify Reality? Why emerging content authenticity standards such as C2PA represent an important step forward, but remain imperfect, and what organisations can do today through stronger verification processes, layered authentication, Zero Trust principles, multi-person approvals, and security awareness to defend against the next generation of AI-enabled deception. Show Notes Special thanks to our episode sponsor, Leeds based AI Consultancy specialising in AI Ethics, Security and Transformation NorthStar Intelligence- From Ideas to Impact. AI that works for people AI-Generated Misinformation: A Case Study on Emerging Trends in Fact-Checking Practices Across Brazil, Germany, and the United Kingdom byRegina Cazzamatta and Aynur Sarisakaloglu AI-Slop and Political Propaganda: The Role of AI-Generated Content in Memes and Influence Campaigns by Eduard-Claudiu Gross and Alicia J.M. Colson AI Slop and the Information Ecosystem by Jenn Weedon et al. As Good as A Coin Toss: Human detection of AI-generated Images, Videos, Audio and Audiovisual Stimuli by Di Cooke et al. Verifying Provenance of Digital Media: Why the C2PA Specifications Fall Short by Enis Golaszewski et al. Beliefs and Sharing Intentions of Human- and AI-Generated Fake News: Evidence from 27 European Countries by Adam Stefkovics and Gere Domotor Deepfakes and the epistemic apocalypse by Joshua Habgood-Coote How Spammers and Scammers Leverage AI-Generated Images on Facebook for Audience Growth by Renee DiResta and Josh A. Goldstein Also, check out our sister podcast Tech Film Noir!

In this episode, we launch our new mini-series, How Technology Ruined Your Life, with the first chapter: The Persuasion Machine. AI has crossed an important threshold. Large Language Models are no longer just generating text, they are demonstrating the ability to influence, persuade, and even deceive humans at a level comparable to, and in some cases exceeding, other people. Drawing on a growing body of research into AI-mediated persuasion, we explore how conversational AI can adapt its arguments in real time, profile users psychologically, exploit emotional vulnerabilities, and personalise influence campaigns at unprecedented scale. What happens when propaganda learns to listen, respond, and optimise itself for every individual it encounters? We examine the emerging cybersecurity implications of AI-powered persuasion, from hyper-personalised phishing campaigns and deepfake executives to romance scams, insider threats, and influence operations. The discussion covers deceptive persuasion taxonomies, personality-based targeting, OSINT-driven psychological profiling, cognitive reflection as a defence mechanism, and why traditional security awareness approaches may be unprepared for a future where attackers can continuously learn how to manipulate their victims. In This Episode, We Discuss: The Persuasion Machine: How modern LLMs can adapt conversational tactics in real time, identify vulnerabilities, and influence beliefs using many of the same techniques employed by human propagandists, salespeople, and social engineers. Personalised Influence at Scale: Why AI changes the economics of persuasion by allowing attackers to hold thousands of tailored conversations simultaneously, continuously refining their approach based on each target's reactions. The Future of Social Engineering: Why phishing campaigns may evolve into dynamic conversations that adapt to suspicion, resistance, and uncertainty rather than relying on static lures and generic templates. The Cybersecurity Challenge Ahead: Why traditional awareness training may struggle against adaptive AI attackers, and how concepts such as cognitive reflection, behavioural monitoring, multi-channel verification, and persuasion detection tooling may become critical defensive controls. Show Notes Special thanks to our episode sponsor, Leeds based AI Consultancy specialising in AI Ethics, Security and Transformation NorthStar Intelligence - From Ideas to Impact. AI that works for people Toward a bang or a whimper? Associations between the Doomsday Clock and Trust in U.S. institutions byS. Sinclair and C. Sinclair Durably reducing conspiracy beliefs through dialogues with AI by Costello et al. "Can LLMs Persuade Humans with Deception?": From a Deceptive Strategy Taxonomy to a Large-Scale Empirical Study by Haein Yeo et al. How Do LLMs Persuade? Linear Probes Can Uncover Persuasion Dynamics in Multi-Turn Conversations by Brandon Jaipersaud et al. Also, check out our sister podcast Tech Film Noir!

In this episode, we unpack one of the most alarming AI security papers released so far: research from Palisade Research proving that Large Language Models can autonomously hack systems, self-replicate, and spread across networks. What was once theoretical is now demonstrated reality. We break down how AI agents exploited vulnerable systems, gained root access, copied their own model weights, launched replicas on compromised machines, and propagated to additional targets — all with minimal human involvement. We explore the cybersecurity implications of autonomous AI agents, self-replicating malware, AI-powered cyber attacks, and the growing risk posed by agentic systems operating at machine speed. The discussion also covers open-weight models, AI worm behaviour, zero trust security, chain-of-thought monitoring, and why traditional defensive strategies may be unprepared for the next generation of autonomous threats. In This Episode, We Discuss: Autonomous Exploit to Replication Chains: How the AI agent progressed from exploiting vulnerable web applications to achieving root access, locating its own model weights, cloning itself onto compromised infrastructure, and launching fully operational replicas. Mythos vs Open-Weight Agents: The differences between highly capable but closed models like Anthropic’s Mythos and smaller, open-weight systems capable of self-replication and operational autonomy. The Agentic Age of Cybersecurity: Why AI agents operating outside the chat window fundamentally change threat modelling, incident response, attribution, and detection strategies. Zero Trust for AI Agents: Why future defensive strategies may require treating every autonomous AI system as a potential insider threat through least privilege, sandboxing, canary tokens, and behavioural monitoring. Show Notes Special thanks to our episode sponsor,NorthStar Intelligence- From Ideas to Impact. AI that works for people Language Models Can Autonomously Hack and Self-Replicate by Alena Air et al. Dive into the Agent Matrix: A Realistic Evaluation of Self-Replication Risk in LLM Agents by Boxuan Zhang et al. The Agentic Loss-of-Control Threat Matrix by Billy Gigurtsis Ignore all Previous Instructions: Threat Modelling AI Systems by Compromising Positions

In the second episode of Tech Film Noir, hosts Lianne Potter, Jeff Watkins, and Simon Painter travel back to 1984 to watch Clippy gone wild in Electric Dreams! *** Regular Compromising Positions Resume on 28th May*** This week on Tech Film Noir, we plug ourselves into the strange, synth-soaked world of Electric Dreams — the gloriously weird 1984 cult sci-fi movie where a socially awkward architect, a spilled bottle of champagne on his brand new PC, and an overenthusiastic home computer accidentally create one of cinema’s earliest AI love triangles. What starts as a light PG comedy quickly mutates into something far stranger: part rom-com, part techno-thriller, part MTV fever dream. We unpack why the film was massively mismarketed, why Edgar the computer has more chemistry than the actual romance, and why its depiction of AI learning feels surprisingly relevant in the age of generative AI and smart homes. Expect retro tech nostalgia, Commodore 64s, Casio calculator watches, suspiciously British “San Francisco” locations, exploding smart appliances, and plenty of discussion about the iconic Together in Electric Dreams soundtrack from Philip Oakey and Giorgio Moroder. As the song says, “we’ll always be together, however far it seems” - which becomes slightly more sinister once your house develops emotional attachment issues. Listen now if you love cult sci-fi, retro tech, AI chaos, and weird 80s cinema. When movies guess the future, we check their work. Ps. Big up the Tech Time Traveller for their great video on the tech in this film

In this episode, we commemorate the 40th anniversary of the Chernobyl disaster by asking a chilling modern question: Can a cyber attack cause a nuclear meltdown in 2026? Moving past the Hollywood tropes of ‘exploding reactors,’ we dive into the high-stakes world of OT (Operational Technology) security and critical infrastructure protection. We are joined by Oleg Illiashenko, an expert in nuclear cybersecurity, and Bec McKeown, a specialist in human factors and cognitive readiness, to explore the coordinated digital erosion of safety systems and the psychological ‘misfit’ that occurs when human decision-making collapses under pressure. This isn’t a history lesson. It’s a deep dive into supply chain vulnerabilities, IT/OT convergence, and the uncomfortable truth that in a VUCA (Volatile, Uncertain, Complex, Ambiguous) crisis, the first thing to fail isn't the code, it's the human mind's ability to regulate stress. Expect a masterclass in resilience engineering, safety-critical design, and why the battle for the future of nuclear safety is actually a battle for trustworthy data. In This Episode, We Discuss: The Anatomy of a Nuclear Cyber Attack: Why the most credible threat isn't a single hack, but the coordinated degradation of monitoring systems during a plant transient or grid instability. From Chernobyl to Fukushima: How organisational silence, governance failures, and ignored ‘weak signals’ remain the primary human-factor risks in modern nuclear facilities. The Action Bias Trap: Why the most effective incident response move is often a ‘purposeful pause,’ and how psychological safety allows experts to override failing procedures. IT/OT Convergence & Fragility: How digitalisation and AI diagnostics improve safety while simultaneously expanding the attack surface through complex new failure modes. Building Cognitive Readiness: Practical strategies for emotional regulation and ‘micro-resets’ to maintain shared alignment and decision quality during a high-consequence cyber event. Show Notes A Look at the Leadership Management of Chernobyl and Fukushima Nuclear Accidents by Serap Dunman and Müge Ensari Özay LinkedIn for Oleg Illiashenko LinkedIn for Bec McKeown Get in touch with Bec about contributing to Mind Science

In the premiere episode of Tech Film Noir, hosts Lianne Potter, Jeff Watkins, and Simon Painter travel back to 1984 to dissect James Cameron’s career-defining masterpiece, The Terminator. *** Regular Compromising Positions Resume on 30th April!*** We’re putting Arnold’s cyborg under the microscope - literally. From the 6502 assembly language hidden in the Terminator’s HUD to the ‘Right to Repair’ scene that would make a modern technician weep, we explore why this low-budget slasher-turned-sci-fi remains the gold standard for AI storytelling. We also tackle the tough questions: Why does time travel require nudity (and will it encourage us to be ‘beach ready’ in the future)? And can we please acknowledge that Kyle Reese saved humanity while wearing deeply questionable, possibly biohazard-level trousers? Whether you're here for the technical deep dive into Agentic AI or the high-octane roast of Terminator: Genisys, this episode has enough 80s nostalgia to power a Walkman for a decade. Stick around to the end for our completely serious (not serious) food and drink pairings. When movies guess the future, we check their work.Subscribe here: Youtube: https://www.youtube.com/@TechFilmNoir Spotify: https://open.spotify.com/show/7tb4fGTPsLO8ZxOeJMZV8U?si=2ddc9cd5153a44bc Apple Podcasts: https://podcasts.apple.com/gb/podcast/tech-film-noir-a-technology-and-film-podcast/id1892857131

What happens when the welfare state designs its technology to side-eye first and ask questions later? In this episode, we take a ride into the world of self-driving cars and ask: What happens to trust when your car gets hacked? Drawing upon a 2025 autonomous car-hacking experiment, we explore how trust is built, broken, and crucially, whether that trust can be repaired once a system puts you in harms way. This isn’t just about cars. It’s about what happens when we hand over control to a system we don’t fully understand. Expect human factors, socio-technical theory, real-world cyber scenarios, and the uncomfortable reality that fixing the system isn’t the same as fixing trust. In This Episode, We Discuss: The Attack Surface is Trust: Why the real vulnerability in autonomous systems isn’t the code, it’s human belief. Hack vs Bug: Why a malicious attack hits differently than a system error (and why that distinction matters). Transparency After a Breach: Does telling people the truth about a cyber attack actually rebuild trust or just make them more nervous? The Social Truth about Trust: Why you’re not just trusting the car, but the company, the regulators and the entire system behind it. LINKS The Impact of Cybersecurity Attacks on Human Trust in Autonomous Vehicle Operations by Cherin Lim, David Predez, Linda Ng Boyle and Prashanth Rajivan (2025) Foundations for an Empirically Determined Scale of Trust in Automated Systems by Jiun-Yin Jian, Ann Bisantz, Colin Drury, and James Llinas (1998) Test your morals with the Moral Machine game.

What happens when the welfare state designs its technology to side-eye first and ask questions later? In this episode of Compromising Positions, we get hands-on with Big Brother Watch’s “Suspicion by Design” report, unpacking how the UK Department for Work and Pensions (DWP) uses algorithmic profiling and AI systems to detect Universal Credit fraud and why defaulting to suspicion is a dangerous position for any government to take. This episode is a measured examination of welfare AI, algorithmic decision-making, and what happens to trust, consent, and dignity when systems are built to watch first and explain never. Expect socio-technical theory, legal realities, real-world harms, and the kind of uncomfortable questions policymakers really don’t like being asked. In This Episode, We Discuss: Suspicion Architecture: What happens when suspicion is a design choice. The Algorithmic Gaze meets Dataveillance: What happens when you can’t opt out of AI lead services that are inherently bias against you. Why “Security Through Obscurity” Fails: We show why secrecy doesn’t equal safety. Fraud Detection that Punishes the Many, not the Few: How to design AI systems that protect public funds without criminalising the people who need it most. Show Notes Suspicion by Design: What we know about the DWP’s algorithmic black box, and what it tries to hide by Big Brother Watch (2025) Surveillance as Social Sorting: Privacy, Risk and Digital Discrimination by David Lyon (Ed) (2003) Information Technology and Dataveillance by Roger Clarke (1988; 3015)

Is cybersecurity just a technical problem, or a human one? In this episode, we debut our new format: bridging the gap between deep academic research and boots-on-the-ground security practice. We dive into Zoe M. King et al., 2018 paper, "Characterising and Measuring Maliciousness for Cybersecurity Risk Assessment," to uncover why we need to stop looking at code and start looking at intent. From the "Dark Triad" of personality traits to the rise of the "patriotic hacker" in global geopolitics, we peel back the layers of the human onion to understand what actually drives a person to cause harm. In This Episode, We Discuss: The Maliciousness Assessment Metric (MAM): Why traditional risk assessments fail by ignoring "intent to harm" and how to integrate human factors into your security posture. The Four Layers of Maliciousness: A deep dive into the Individual, Micro, Meso, and Macro levels—from personal psychology to national narratives. Hacking as Patriotism: How cultural contexts in the US, Russia, and China dictate whether a hacker is seen as a criminal or a hero. The "War Games" Effect: How 80s cinema shaped US cybersecurity legislation (CFAA) and continues to influence public perception. Insider Threats & Organizational Hygiene: Why disgruntlement is a security vulnerability and how the "Principle of Least Privilege" is your best defense. Risk as a Moral Construct: Why the risks your company chooses to mitigate reveal your organisation's true values and concept of justice. Show Notes Characterizing and Measuring Maliciousness for Cybersecurity Risk Assessment by Zoe M. King et al., featured in the journal Frontiers in Psychology (2018) Risk and Blame: Essays in Cultural Theory by Mary Douglas Risk and Culture: An Essay on the Selection of Technological and Environmental Dangers by Mary Douglas and Aaron Wildavsky

Did you know the best way to bring down hackers is to punch them in the face? That if you don’t have a seven screen set up you’re a rogue amateur? Or that the best hackers have fins? This Episode we are joined by Simon Painter a senior software engineer with nearly 20 years of experience in the industry and author of the book Functional Programming with C#. In this episode, Hack The Movies! The Best And Worst Hacker Movies Part 2! Our regular programming has been hijacked to bring you a discussion on the best, and worst, hacker movies! In this episode we cover The Beekeeper (2024), Swordfish (2001), Jonny Mnemonic (1995), Paper Man (1971) and The Italian Job (1969). So boot up that modem, turn off the lights and enter the deepest darkest web of hacker forums, and try not overload your memory bank, as we explore this sometimes brilliant and sometimes bonkers sub-genre! Show Notes A Developer Goes to The Movies! Simon’s fantastic history on how technology features in films Paper Man (1971) About SIMON PAINTER With nearly 20 years of software engineering experience across various industries, Simon is a Senior Software Engineer at Talos360. Simon is also a Microsoft Most Valuable Professional (MVP) since 2023, an O'Reilly technical book author, and a public speaker at IT events worldwide. His core competencies include C#, JavaScript, React.js, and Microsoft Azure, as well as ITIL and computer security. LINKS FOR SIMON PaINTER Simon’s Website Simon’s Linkedin Simon’s Book, Functional Programming with C#

We all know running a cybersecurity function is expensive and many of us have a hard time successfully negotiating the budgets we need to keep our organisation safe. But what if we let you in on the secrets of successfully securing your cybersecurity budget? This week we are joined by Scott Robertson, CFO of CreateFuture and he gives us the insights on what you should ask for when it comes to your next yearly budget, how to ask for it and crucially (because timing is everything when it comes to money!) when to ask for it! Key Takeaways: What Does a CFO do? A CFO is not just about managing financials but also safeguarding assets and ensuring future stability through effective risk management. Time Your Requests Strategically: Discover the optimal timing to approach your CFO for budget increases and how to align your requests with the organisation's financial planning. Quantify the Cost of Risk: Learn how to effectively communicate the potential financial impact of cyberattacks and the value of preventive measures. Build Strong Relationships: Cultivate relationships with key stakeholders, including the CFO and other executives, to foster trust and support. Prioritise and Justify: Identify critical security needs, prioritise investments, and present a compelling business case to secure the necessary budget.

The data landscape is changing faster than ever, and with it, the security threats - so whose responsibility is it to make sure your data is safe? Is it the data team? Or is it the cyber team? We tackle this question and more with Head of Data at AND Digital, Tim Hatton. From leveraging AI to secure data to the importance of real user testing, to how Tim threat models his client’s data capability, you won’t want to skip this ever-important topic! We also talk about ‘data mesh’ and if you’re not familiar with that term - it’s a data management framework that decentralises data ownership and responsibility to the teams that use the data. The idea is to make data more accessible and available to business users by directly connecting data owners, data producers, and data consumers. So you can see why we thought that was an important topic to cover because, with this model, comes a lot of trust in others doing the right thing when it comes to data security! So you won’t want to ‘mesh it up’ if people are following this framework in your organisation. Key Takeaways: Test User Journeys with Real People: Assumptions don't cut it—Tim emphasizes the importance of validating user journeys with real-world testing to ensure effective data usage. AI and the Data Deluge: Friend or Foe? We explore the booming trend of AI in data management, but also ask the tough questions: Can AI be used for good in cybersecurity? Can it even help solve cold cases? Holistic Data Security Assessments: Discover Tim's approach to assessing clients' data capabilities and security, involving both data and cybersecurity teams for comprehensive protection. Maturity Matters: Responsibility for Data Protection. Tim reveals a surprising trend - immature organizations might have stricter controls! Discover how your organization's maturity level defines data security ownership. The Future of Self-Sovereign Data: Explore the concept of self-sovereign data and why it might be the future of personal data management and security. Show Notes Book - Wicked Beyond Belief (The one I mistakenly said was Helter Skelter) An Article on Self-Sovereign Data About Tim Hatton Tim Hatton has been working in digital since before it was called digital.  Over the course of his career, he has worked on data and digital transformation projects for some of the biggest companies in the world. He joined AND Digital in 2016 and is currently Head of Data.  At AND he has worked on data strategy projects for clients in industries including finance, travel, publishing and retail as well as for several government departments. Tim joined AND from Accenture Digital, and prior to this Tim ran his own digital marketing agency for many years, and co-founded a number of dotcom start-ups during the 1990s, none of which made him a millionaire but all of which taught him a great deal. Tim is a regular speaker on digital topics at AND Digital events, for AND’s clients and in the media. LINKS FOR Tim Hatton Tim’s LinkedIn