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Radical Markets

Uprooting Capitalism and Democracy for a Just Society

by Eric Posner and Glen Weyl

Last tended to January 02, 2021

Chapter 5 - Data as Labour: Valuing Individual Contributions to the Digital Economy

Weyl and Posner were heavily influenced by the ideas Jaron Lanier presented in Who Owns the Future in this chapter.

The text, images and videos we upload to YouTube, Instagram, Twitter, Google and Facebook are all fed into Machine Learning and Artificial Intelligence systems. Systems that allow those companies to create a huge array of profitable services – facial recognition, video editing, and natural language processing. The data we create and freely share leads to clear economic value.

The current Information Economy conceals the fact we're all actively producing data without acknowledging it or compensating us for that labour.

The narrative we tell about Algorithms and Machine Learning is one of genius programmers concocting terribly advanced mathematical calculations to produce intelligent systems. In reality, it's not black Magic at all. Most of the value comes from the enormous data sets they have access to.

"The income from it is distributed to a small number of wealthy savants rather than to the masses, and that many of us have a false fear of AI creating mass unemployment when humans are more necessary than ever to our digital economy" (209)

Weyl and Posner compare Data Labour to other historical forms of invisible labour that have gone uncompensated - domestic work, childcare, elderly care, and slavery. Interestingly, they don't mention other kinds of unpaid labour in the digital realm such as content moderation and community management.

The belief that "information wants to be free" championed by the early internet crowd in the 1990's influenced the decisions made around Internet Infrastructure. To make The Web simpler and more accessible, affordances like Transcopyright, Micropayments and Bi-Directional Links were sidelined.

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Maggie Appleton © 2021