Natalie Monbiot has worked where people and AI meet since 2019. She founded Virtual Human Economy and co-founded Artists in the Machine. We brought her back to test an approach to AI that puts human agency first, automation second and judgment on the human side whenever the stakes are real.
Natalie’s thesis is that meaning can’t be encoded. AI can judge on pattern. It cannot understand the implications of a decision, because implications require stakes, and stakes belong to people.
Trust and the future of work
We talk about what changed in AI over the past year, why AI agents feel freeing when they remove tedious work, and why trust is becoming the thing that sets platforms apart. We cover fears of job loss, vibe coding and the shrinking need for white-collar mechanics. Then we come back to one question: once the machine can do more, what should we keep for ourselves on purpose?
The illusion of certainty
AI can reason and recommend, and it does not live with the consequences. That gap creates an illusion of certainty that leads people to outsource decisions they later regret. As I see it, that means outsourcing orientation, the center of John Boyd’s real OODA loop. We also get into AI parrots and work slop, and why writing loses its authenticity when you do not own the thesis. The conversation connects this to Marx’s warning about the worker as an appendage to the machine.
Digital twins and artists
Natalie explains what changes inside a company when a digital twin makes communication low-risk and always available. We use Marshall McLuhan’s ideas about the properties of a medium to look at AI as a filter on communication. We close on the Artists in the Machine summit and what AI is changing for artists, filmmakers and writers, including faster production, new mediums and shifts in ownership. Grimes comes up as a case study.
Which task are you ready to hand off next, and which will you keep?
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Written by Ponch Rivera with AI assistance in production. The full conversation is in the player below.