Expertise pipeline

People still become experts, so someone can check AI work later.

Facts

Lane: Interfaces and society
Wave: 8 of 12 (build order, not a date)
Needs: 9 boxes all the way back through hard links
Unlocks: 0 boxes downstream through hard links
Leverage: None
Cluster: Assistants and the public

Evidence as of October 2026

If entry-level hiring keeps falling in AI-exposed jobs, fewer people build the expertise that oversight depends on. Nobody measures this directly yet.

01Stanford Digital Economy Lab: Canaries update, August 2026

Around it

Needs · 1

AI tutoring at scalestage · Emerging

Unlocks · 1

Scalable oversightcapability · Emerging · helps, not required

Brakes

Works against this box

Sycophancybrake · Built today
Deskilling from AI usebrake · Emerging

Loops and off-ramps

Expertise pipelineharmful loop
Capex pullbackoff-ramp · cut off
Taiwan chip disruptionoff-ramp · cut off
Power shortfalloff-ramp · cut off
Training data ruled outoff-ramp · slowed
Misuse catastropheoff-ramp · cut off

Openings researchers' judgement, October 2026 scouting

Startup room 49/100 · rank 38 of 124 Research room 66/100 · rank 16 of 124

Crowding1 Lab overlap2 Small-team fit4 Buyer today2 Research openness5

Depth: light
Players: Anthropic RCT (Shen and Tamkin); Nature Medicine perspective; NeurIPS position paper; almost no products
Wedge: Training designs that preserve skill formation while juniors use AI, sold to employers; strong fresh evidence of never-skilling, little product activity. research