Vivienne Ming argues that AI will soon strip high-skill professions of their exclusivity, pushing many tasks in law, medicine and finance into lower-paid roles. She calls this trend “deprofessionalization” and says our current schools and hiring systems aren’t ready. Instead of dumping facts into students’ heads, Ming wants us to teach capacities—resilience, pattern recognition, creative problem-solving—skills that machines can’t copy. She even recommends parents shift “from a model of knowledge transmission to one of capacity building.” In Robot-Proof, Ming draws on her work as a neuroscientist and entrepreneur to show how data and AI can reshape education and recruitment. She’s already built tools that measure traits like curiosity and perseverance through game-style tasks—and she argues companies should use similar “capability assessments” rather than rely on grades or resumes. That, she says, would widen access for candidates from non-traditional backgrounds and help firms spot genuine talent instead of applicants who just know how to play the grades game. Ming points to real-world pilots: a finance firm using her AI-driven challenges to hire entry-level analysts, and schools that tailor lessons in real time based on individual students’ cognitive profiles. Those examples, she claims, prove you can both prepare young people for a fast-changing job market and give employers the confidence they need in new hires. She stresses that capacity-based hiring isn’t a neat techno-fix, but a necessary overhaul if humans are to stay ahead of the machines.