The Squeezed Middle
AI makes it easy for beginners to do basic tasks and helps top experts work even faster, but it removes the 'middle' jobs where people usually learn the skills needed to become experts in the first place, effectively breaking the career ladder.
The 'Squeezed Middle' describes a structural shift where AI flattens the learning curve by automating entry-level tasks and augmenting high-level output, inadvertently eliminating the journeyman roles that serve as the essential training ground for future mastery.
The barbell effect of AI (equalised floor + conditionally supercharged ceiling) bypasses mid-level practitioners; but the middle is where substrate is forged (the 70-20-10 rung), so automating the journeyman's work removes the pipeline that renews experts. A universal structural law (job polarization generalised to the developmental pipeline); self-undermining. (C4AIL, Whitepaper II §1.8.)