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Lunchtime BABLing with Dr. Shea Brown

Babl AI, Jeffery Recker, Shea Brown
Lunchtime BABLing with Dr. Shea Brown
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  • AI and Scheduling Optimization with Leon Ingelse
    From lesson-planning to long-haul trucking, good schedules make the world run—literally. In this episode, BABL AI CEO Dr. Shea Brown sits down with Leon Ingelse, writer-researcher at Croatian optimization studio Dots & Lines, to unpack the hidden math, ethics, and human stories behind modern scheduling and routing. 🔑 What we cover Hard vs. soft constraints – why “can’t” and “prefer not to” need different math Digital twins – building a virtual copy of a business before you touch the real one Fairness & “karma” scheduling – balancing preferences over weeks, months, years Transparency & compliance – explaining a timetable (and the laws baked into it) Human-in-the-loop vs. full automation – when you still want a person pressing “publish” Optimization ≠ LLMs – where stochastic AI falls short and formal models shine The future of Dots & Lines and why bespoke solutions often beat off-the-shelf productsCheck out the babl.ai website for more stuff on AI Governance and Responsible AI!
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  • How to Break Into AI Governance?
    Ever wondered how to start a career in AI Governance, Responsible AI, or AI Risk Management? In this episode of Lunchtime BABLing, BABL AI CEO Dr. Shea Brown is joined by COO Jeffery Recker and CSO Bryan Ilg for a no-nonsense, practical conversation about how to actually break in to this fast-growing, high-demand field. 🌟 What you'll learn in this episode ✅ What AI governance really is (and why it matters in every business using AI) ✅ The 3 main career paths into AI governance: Dedicated governance roles Expanding your current role to include AI oversight Building something new as an entrepreneur/intrapreneur ✅ Do you need to be technical? How much? ✅ The real skills hiring managers want ✅ How to transition from zero experience to credible candidate ✅ Why governance is essential for scaling AI safely and responsibly 🧭 Key themes Hands-on learning: You have to use AI to govern AI Systems thinking: Understanding how decisions get made at scale Risk awareness: The #1 thing employers want Building your profile: Projects, credentials, volunteering, networking Niche strategy: Why specializing beats general buzzwords Marathon mindset: This is not a quick certification cash-inCheck out the babl.ai website for more stuff on AI Governance and Responsible AI!
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  • AI Ethicist Reacts to Different Uses of AI
    In this fun and thought-provoking episode of Lunchtime BABLing, BABL AI CEO and AI ethicist Dr. Shea Brown is joined by COO Jeffery Recker and CSO Bryan Ilg for a rapid-fire discussion on some of the most surprising, bizarre, and controversial uses of AI circulating online. From jailbreaking legal loopholes with ChatGPT, to AI-generated testimony from the deceased, to digital therapy bots and AI relationships—no use case is off-limits. The trio explores the ethical, legal, and emotional implications of everyday AI encounters, reacting in real-time with humor, insight, and a healthy dose of skepticism. 🎧 Topics include: Can AI help someone get out of jail? Is it ethical to use AI-generated avatars in court? Talking to an AI version of a dead loved one—grief or avoidance? Should AI replace your therapist? Professors using ChatGPT to grade student essays AI as your relationship coach (or third wheel) Confirmation bias and the future of learning in the AI age 💬 This episode steps away from regulation and compliance to explore how AI is quietly reshaping human behavior—and whether we’re ready for it.Check out the babl.ai website for more stuff on AI Governance and Responsible AI!
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  • What is ISO 42001?
    In this episode of Lunchtime BABLing, BABL AI CEO Dr. Shea Brown is joined by COO Jeffery Recker to break down ISO/IEC 42001 — the first international standard for AI management systems. Whether you're leading an AI team, navigating AI risk, or just starting your Responsible AI journey, this high-level introduction will help you understand: What ISO 42001 is and why it matters How it fits into global AI governance (including the EU AI Act and U.S. regulations) Key components of the standard — from leadership, risk assessments, and operations to monitoring and continual improvement Common challenges organizations face when adopting it Practical first steps for implementation, even for startups and resource-limited teams 💡 ISO 42001 is quickly becoming the North Star for organizations aiming to demonstrate trustworthy and responsible AI practices — especially in today’s fast-moving regulatory environment.Check out the babl.ai website for more stuff on AI Governance and Responsible AI!
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  • A New Framework to Assess the Business VALUE of AI
    In this episode of Lunchtime BABLing, BABL AI CEO Dr. Shea Brown unveils a powerful new framework to assess business value when implementing AI—shifting the conversation from “Which tool should I use?” to “What value do I want to create?” Joined by CSO Bryan Ilg and COO Jeffery Recker, the trio dives into the origin, design, and real-world application of the AI VALUE Framework: - Visualize your operations - Ask the right questions - Link to AI capabilities - Understand feasibility & risk - Experiment & evaluate This episode is packed with insights for business leaders, innovation teams, and AI professionals navigating the hype, risk, and opportunity of artificial intelligence. The framework—originally developed for BABL AI’s upcoming certification for business professionals—is meant to reduce AI project failure and help organizations do it right, not fast. 💡 Key topics: - The difference between asking about tools vs. asking about value - Why most AI projects fail—and how to avoid it - How AI governance can create value, not just mitigate risk - The importance of metrics, pilot testing, and customer focus - Why being proactive beats being reactive in AI implementationCheck out the babl.ai website for more stuff on AI Governance and Responsible AI!
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About Lunchtime BABLing with Dr. Shea Brown

Presented by Babl AI, this podcast discusses all issues related to algorithmic bias, algorithmic auditing, algorithmic governance, and the ethics of artificial intelligence and autonomous systems.
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