CONCEPT
The Capability Gap
The divide — sharper and more durable than the gap in tool access — between those who can convert AI tools into human functioning and those who cannot, mediated by education, infrastructure, health, and institutional support.
The capability gap is the analytical contribution that Angus Deaton's framework, drawing on Amartya Sen's capability approach, brings to the AI distributional question. Sen distinguished between commodities — things — and capabilities — the functionings that a person can achieve. The relationship between the two is mediated by conversion factors: personal, social, and environmental conditions that determine whether a commodity translates into a genuine expansion of human functioning. Applied to AI, the distinction reveals why declining cost curves alone cannot produce democratization. A computer in the hands of a trained engineer with reliable electricity, connectivity, domain expertise, and institutional support translates into dramatic productive capability. The same computer in other hands does not. The commodity is identical. The capability it enables is radically different.
In The You On AI Field Guide
The capability gap produces what Deaton's analysis identifies as the amplification paradox: AI tools amplify existing capability, which means they benefit