Perspective 06 · Institutions & rights · Core 1.0 Core 1.0 snapshot

Ownership of AI productivity

Who should own the marginal capability created through years of human teaching?

Working outlineQuestions before conclusionsNot part of CoreFrozen snapshot
Core releaseCore 1.0
Perspective stateFrozen release snapshot
Published19 August 2026
Starting question

Starting question

A worker may spend years correcting, contextualizing and developing a +. The model treats some resulting capability as personally accumulated productive capital.

Possible connection

Possible connection

Ownership can align incentives: the worker has reason to teach deeply if legitimate portable capability remains theirs.

Tension to explore

Tension to explore

Models, employer data, platform infrastructure, human know-how and generated artifacts may all contribute to capability, making clean ownership difficult.

Evidence needed

Evidence needed

Define technically separable learning artifacts and test legal treatment under employment, IP, trade-secret and data-protection regimes.

Next pass

What should we add here?

ArgumentWhat is the strongest case that Human Capital .+ changes this topic?
CounterargumentWhat would a serious critic say we are overlooking?
Institutional consequenceWhich law, contract, organization or public system would have to change?
MeasurementWhat real-world evidence would make this perspective more than speculation?