Data as Labor

Overview

Data as Labor is the proposal that the data individual users generate by using digital platforms should be treated, and paid for, as a form of labor contributed to production rather than as free raw material the platform simply harvests. The idea was developed by Jaron Lanier together with Imanol Arrieta-Ibarra, Leonard Goff, Diego Jiménez-Hernández and E. Glen Weyl in "Should We Treat Data as Labor? Moving Beyond 'Free'" (AEA Papers and Proceedings 108, 2018, pp. 38–42), and popularized for a general audience as Chapter 5 of Eric Posner and Glen Weyl's Radical Markets (2018).[1] The argument is that because a handful of platforms are the dominant buyers of user data, they hold monopsony power: they can set the terms on which data is supplied and pay users nothing beyond access to the service, capturing the surplus value users' data creates as an unpriced input.[1]

The Proposal

The authors' remedy is to build a genuine, priced labor market for data: platforms would compensate users for the data they contribute, ideally through collective bargaining structures — "data labor unions" — that give users leverage comparable to what organized workers have over wages, rather than relying on take-it-or-leave-it terms-of-service.[1] On this reading, part of the profit dominant platforms earn is a rent extracted from an uncompensated contribution, and pricing that contribution turns an extracted rent into a paid factor of production — a market-design fix rather than a tax.

Relationship to the Wiki's Platform-Rent Case

Data as Labor is one of two main capture instruments the wiki carries for platform and data rents, the other being direct levies on platforms distributed as a citizen's dividend. It sits on the contested frontier of the wiki's rent gradient: whether platform profits are rent at all — as opposed to the return to genuinely valuable network effects and intangible capital — is disputed, and even among those who accept the rent framing, valuing an individual user's data contribution and building functioning "data unions" at scale remain unresolved design problems with no working large-scale precedent.

See Also

• Arrieta-Ibarra et al. (2018) — Should We Treat Data as Labor? — the AEA Papers and Proceedings paper that formalizes this concept's central monopsony argument
• Jaron Lanier — the computer scientist and VR pioneer who originated the data-as-labor and 'siren servers' concepts this proposal formalizes
• Platform and Data Rents — the broader concept page this proposal is one instrument for
• Radical Markets (concept) — the book's fuller five-proposal program, including Data as Labor as Ch. 5
• Radical Markets (book scan) — the full book source
• Citizen's Dividend — the alternative distribution mechanism for captured platform rent
• Intellectual-Property Rents — the sibling contested frontier

Sources

1. Imanol Arrieta-Ibarra, Leonard Goff, Diego Jiménez-Hernández, Jaron Lanier & E. Glen Weyl (2018), "Should We Treat Data as Labor? Moving Beyond 'Free'," AEA Papers and Proceedings 108: 38–42 — used for the data-as-labor argument, the data-monopsony diagnosis, and the data-labor-union remedy. AEA · PDF
2. Eric Posner & E. Glen Weyl (2018), Radical Markets: Uprooting Capitalism and Democracy for a Just Society, Princeton University Press, Ch. 5 — used for the popularized book-length statement of the proposal. Publisher · wiki book scan