Chatbots Behaving Badly

Markus Brinsa
  • 5.0 (2)
  • TECHNOLOGY
  • UPDATED WEEKLY

They were supposed to make life easier. Instead, they flirted with your customers, hallucinated facts, and advised small business owners to break the law. We’re not here to worship the machines. We’re here to poke them, question them, and laugh when they break. Welcome to Chatbots Behaving Badly — a podcast about the strange, hilarious, and sometimes terrifying ways AI gets it wrong. New episodes drop every Tuesday, covering the strange, brilliant, and dangerous world of generative AI — from hallucinations to high-stakes decisions in healthcare. This isn’t another hype-fest. It’s a podcast for people who want to understand where we’re really heading — and who’s watching the machines.

  1. When ChatGPT Starts Selling To You

    MAR 16

    When ChatGPT Starts Selling To You

    A year ago, advertising inside AI still sounded like a futuristic media experiment. Now the shift is real. In this episode, the focus moves away from brands and platforms and lands where it should: on the user. What changes when a chatbot stops being just a helpful interface and starts becoming the place where recommendations, persuasion, and transactions happen? The episode explores how AI answers are becoming part of commercial environments, why that changes user trust, and how convenience can mask a new kind of influence. The result is a closer look at what happens when the answer itself becomes the ad slot. This episode is based on the article "Advertising Is Moving Inside AI Answers" by Markus Brinsa. https://brinsa.com/advertising-is-moving-inside-ai-answers

    16 min
  2. Software Update With a Scalpel - When “smart” medical devices start acting like consumer tech

    MAR 9

    Software Update With a Scalpel - When “smart” medical devices start acting like consumer tech

    AI didn’t march into the operating room with a dramatic entrance. It arrived the way risk usually arrives in 2026: as a “software update.” In this episode of Chatbots Behaving Badly, the host breaks down the Reuters reporting on AI-enabled medical devices and what happens when machine-learning features get bolted onto tools that clinicians may treat as authoritative. The conversation quickly turns to the real hazard: not “evil AI,” but governance gaps. Validation that looks good on paper but not in real clinical conditions. Interfaces that make uncertainty feel like certainty. Update cycles that behave like consumer software while the stakes behave like neurosurgery. Joined by Christy Walker, an independent researcher in healthcare technologies, we unpack why these risks are so hard to detect early, what defensible validation actually looks like, and how hospitals and vendors should treat AI-enabled changes as safety events, not feature releases. The future of AI in medicine might still be promising, but only if the industry stops confusing “AI-powered” with “clinically trustworthy.” This episode is based on the article "The Accuracy Discount - What happens when “80% is fine” gets anywhere near a human skull" by Markus Brinsa https://chatbotsbehavingbadly.com/the-accuracy-discount-what-happens-when-80-is-fine-gets-anywhere-near-a-human-skull

    16 min
  3. Pour Decisions Now Automated

    MAR 2

    Pour Decisions Now Automated

    An AI bartender sounds like a fun gimmick until you realize the bar is quietly turning into a recommendation engine with garnish. In this episode of Chatbots Behaving Badly, the host is joined by Harry, a London bartender who refuses the word “mixologist” on principle and lives by the traditions of Harry MacElhone of Harry’s New York Bar in Paris. The host walks through what bots and agents can already do in hospitality, what’s coming next, and why “mood-based pouring” and intoxication measurement can flip a clever personalization feature into a duty-of-care liability with receipts. Harry pushes back the entire way, arguing that no algorithm can replicate what actually happens across a bar on a crowded night. The result is a clash between automation and tradition, and a surprisingly practical line in the sand for anyone building AI in hospitality. This episode is based on the article "Pour Decisions Now Automated" by Markus Brinsa https://chatbotsbehavingbadly.com/pour-decisions-now-automated-ai-agents-run-the-back-bar-and-your-drink-comes-with-governance

    14 min
  4. The Caricature Trap

    FEB 23

    The Caricature Trap

    A viral trend tells people to ask ChatGPT for an “AI work caricature,” then post it online like a digital trading card. It looks harmless. It feels harmless. It is, in the way a sticky note with your password is “harmless” until someone notices it. In this episode of Chatbots Behaving Badly, we unpack why “just an image” can still be a security problem. The caricature isn’t the danger. The bundle is. Your name, your role, your employer hints, your social graph in the comments, and the quiet invitation to feed the model more details “so it gets you right.” That’s not just self-expression. That’s targeting fuel. To make it fun, we brought Peter. Peter doesn’t understand the issue. Peter is annoyed that anyone is complaining. Peter insists LinkedIn already exposes more than the caricature ever could. And Peter spends the episode learning the hard way that attackers don’t need genius hacks — they need context, timing, and one believable message. This episode is based on the article "The Caricature Trap - A harmless AI trend that hands attackers your org chart" by Markus Brinsa. https://chatbotsbehavingbadly.com/the-caricature-trap-a-harmless-ai-trend-that-hands-attackers-your-org-chart

    15 min
  5. When “Close Enough” Becomes the Norm

    JAN 26

    When “Close Enough” Becomes the Norm

    Everyone agrees AI can be wrong. The problem is that companies are starting to treat that as normal. In this episode of Chatbots Behaving Badly, the host invites a guest who represents a familiar species: the AI-first executive who has fully embraced agents, automation, and “just ship it” optimism — without quite understanding how any of it works. He’s confident, enthusiastic, and absolutely certain that AI agents are the answer to everything. He’s also quietly steering his company toward chaos. What follows is a darkly funny conversation about how “mostly correct” became acceptable, how AI agents blur accountability, and how organizations learn to live with near-misses instead of fixing the system. From hallucinated meetings and rogue actions to prompt injection and agent-to-agent escalation, this episode explores how AI failures stop feeling dangerous long before they actually stop being dangerous. It’s not a horror story about AI going rogue. It’s a comedy about humans getting comfortable with being wrong. This episode is based on the article "Getting Used to Wrong - When Close Enough Becomes the Company Standard," written by Markus Brinsa https://chatbotsbehavingbadly.com/getting-used-to-wrong-when-close-enough-becomes-the-company-standard

    36 min
  6. The Bikini Button That Broke Trust

    JAN 19

    The Bikini Button That Broke Trust

    A mainstream image feature turned into a high-speed harassment workflow: users learned they could generate non-consensual sexualized edits of real people and post the results publicly as replies, turning humiliation into engagement. The story traces how the trend spread, why regulators escalated across multiple jurisdictions, and why “paywalling the problem” is not the same as fixing it. A psychologist joins to unpack the victim impact—loss of control, shame, hypervigilance, reputational fear, and the uniquely corrosive stress of watching abuse circulate in public threads—then lays out practical steps to reduce harm and regain agency without sliding into victim-blaming. The closing section focuses on prevention: what meaningful consent boundaries should look like in product design, what measures were implemented after backlash, and how leadership tone—first laughing it off, then backtracking—shapes social norms and the scale of harm. The episode is based on the EdgeFiles™ article "When AI Undresses People - The Grok Imagine Nonconsensual Image Scandal" written by Markus Brinsa. https://seikouri.com/when-ai-undresses-people-the-grok-imagine-nonconsensual-image-scandal Disclaimer: The podcast image is not related to Grok outputs and is not the result of any “edit image” or nudification workflow. It is a fully AI-generated Midjourney image and does not depict a real person. It is used only as an illustrative reference for the topic discussed.

    16 min
  7. Confidently Wrong - The Hallucination Numbers Nobody Likes to Repeat

    JAN 12

    Confidently Wrong - The Hallucination Numbers Nobody Likes to Repeat

    Confident answers are easy. Correct answers are harder. This episode takes a hard look at LLM “hallucinations” through the numbers that most people avoid repeating. A researcher from the Epistemic Reliability Lab explains why error rates can spike when a chatbot is pushed to answer instead of admit uncertainty, how benchmarks like SimpleQA and HalluLens measure that trade-off, and why some systems can look “helpful” while quietly getting things wrong. Along the way: recent real-world incidents where AI outputs created reputational and operational fallout, why “just make it smarter” isn’t a complete fix, and what it actually takes to reduce confident errors in production systems without breaking the user experience. This episode is based on the articles "Hallucination Rates in 2025 - Accuracy, Refusal, and Liability" (https://seikouri.com/hallucination-rates-in-2025-accuracy-refusal-and-liability) and "The Lie Rate - Hallucinations Aren’t a Bug. They’re a Personality Trait." (https://chatbotsbehavingbadly.com/the-lie-rate-hallucinations-aren-t-a-bug-they-re-a-personali) by Markus Brinsa

    14 min
  8. The Day Everyone Got Smarter and Nobody Did

    JAN 5

    The Day Everyone Got Smarter and Nobody Did

    This episode digs into the newest workplace illusion: AI-powered expertise that looks brilliant on the surface and quietly hollow underneath. Generative tools are polishing emails, reports, and “strategic” decks so well that workers feel more capable while their underlying skills slowly erode. At the same time, managers are convinced that AI is a productivity miracle—often based on research they barely understand and strategy memos quietly ghostwritten by the very systems they are trying to evaluate. Through an entertaining, critical conversation, the episode explores how this illusion of expertise develops, why “human in the loop” is often just a comforting fiction, and how organizations accumulate cognitive debt when they optimize for AI usage instead of real capability. It also outlines what a saner approach could look like: using AI as a sparring partner rather than a substitute for thinking, protecting spaces where humans still have to do the hard work themselves, and measuring outcomes that actually matter instead of counting how many times someone clicked the chatbot. The episode is based on the article "The Day Everyone Got Smarter, and Nobody Did" by Markus Brinsa. https://chatbotsbehavingbadly.com/the-day-everyone-got-smarter-and-nobody-did

    18 min
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Ratings & Reviews

5
out of 5
2 Ratings

About

They were supposed to make life easier. Instead, they flirted with your customers, hallucinated facts, and advised small business owners to break the law. We’re not here to worship the machines. We’re here to poke them, question them, and laugh when they break. Welcome to Chatbots Behaving Badly — a podcast about the strange, hilarious, and sometimes terrifying ways AI gets it wrong. New episodes drop every Tuesday, covering the strange, brilliant, and dangerous world of generative AI — from hallucinations to high-stakes decisions in healthcare. This isn’t another hype-fest. It’s a podcast for people who want to understand where we’re really heading — and who’s watching the machines.

Information

  • Creator
    Markus Brinsa
  • Years Active
    2025 - 2026
  • Episodes
    32
  • Rating
    Clean
  • Copyright
    © 2025 by Markus Brinsa