Users' time on zero‑price digital interfaces can be modeled as uncompensated cognitive labor that contributes directly to AI capital formation. Calibrating this 'Dark GDP' (the paper cites a ~$1.3 trillion estimate) reveals a measurable, previously invisible slice of value that may explain part of the falling labor share and suggests new targets for taxation or compensation.
— If correct, this reframes platform regulation, labor policy, and national accounting — making unpaid data extraction a public‑policy issue rather than just a privacy or tech question.
Tyler Cowen
2026.04.14
100% relevant
Nav Vaidhyanathan’s paper (reported by Tyler Cowen) proposes 'Dark GDP' and estimates its size at about $1.3 trillion and recommends policies like an Algorithmic Monopsony Standard and a Pigouvian Algorithmic Severance Tax.
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