Burn The Map: Don’t Mistake AI Fluency for Understanding w/ Dr. Anastassia Lauterbach
In This Episode:
We talk to Dr. Anastassia Lauterbach about what it actually takes to think clearly about AI when everyone else is either panicking, posturing, or treating it like magic. She brings a rare mix of operator experience, board-level governance perspective, and deep curiosity about how AI will reshape business, education, and society. We get into why AI literacy matters more than hype, what leaders keep getting wrong about adoption, and why understanding the limits of these systems is just as important as understanding their potential. If there’s a throughline here, it’s this: the future belongs to people who can engage with AI seriously, not just loudly.
What We Cover:
- Why AI literacy matters more than shallow tool fluency.
- How business leaders should think about AI governance, risk, and real adoption.
- The gap between AI hype and what these systems can actually do.
- Why education, critical thinking, and human judgment still matter more than ever.
- How Anastassia thinks about the long game for AI, business, and society.
Guest Bio:
Dr. Anastassia Lauterbach is a technology strategist, founder, author, and board director focused on artificial intelligence, cybersecurity, and corporate governance. She is the founder and CEO of AI Edutainment and has served in senior leadership and board roles across global technology and business organizations, including Qualcomm, Deutsche Telekom, easyJet, and Dun & Bradstreet. She is the author of The Artificial Intelligence Imperative and has taught and spoken widely on AI, innovation, and responsible technology.
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Selected Links From This Episode:
- Romy & Roby on Amazon
- AI Edutainment: https://www.aiedutainment.ai
- AI Snacks with Romy and Roby
- Wrench.ai: https://wrench.ai
People and Organizations Mentioned:
- Andrew Ng
- Yann LeCun
- Jürgen Schmidhuber
- Judea Pearl
- Stephen Wolfram
- Sam Altman
- DeepMind
- Anthropic
- OpenAI
- Meta
- Deutsche Telekom
- House of Lords
Show Notes & Timestamps:
- 01:01 — Anastassia’s path: computational linguistics, immigration, big tech, and education
- 03:35 — Why AI hype exploded—and why most companies still don’t understand the fundamentals
- 05:32 — AI literacy vs. AI fluency, and the House of Lords initiative
- 06:20 — What people get wrong about LLMs, reasoning, and consciousness
- 08:00 — Causality, counterfactuals, and why today’s AI still falls short
- 10:05 — World models, human learning, and what machines still can’t do well
- 11:43 — Theory of mind, chimpanzees, and the alignment problem
- 14:43 — Chinese open-weight models, cost advantages, and practical business use cases
- 18:10 — What Anastassia thinks Europe got wrong with the AI Act
- 21:47 — Synthetic data, bias, and copies of copies of copies
- 24:16 — Why “unbiased AI” is a fantasy
- 25:10 — AI as electricity—and why people still need to understand how it works
- 28:29 — Hallucinations, legal risk, and why narrow use cases matter
- 31:09 — Will AI widen the gap between the excellent and the passive?
- 34:34 — Why students want AI leadership and teachers often don’t provide it
- 38:59 — Agentic workflows, governance, and the need for auditability
- 42:14 — GPU compute, CAPEX risk, and the hidden economics of AI infrastructure
- 49:14 — Personalized learning, education infrastructure, and what AI should actually improve
- 52:21 — What kids need most: applied math, writing, and disciplined skill-building
- 01:00:04 — Romy & Roby, where to find Anastassia, and what she’s building next