Glen Weyl Says We Need to Re-Think Our Role in the Data Economy

By TAP Staff Blogger

Posted on February 1, 2018


In “Should We Treat Data as Labor? Moving Beyond 'Free’,” Glen Weyl and his colleagues argue that we need to re-conceive how we think about our role in the data economy. Machine learning and automation relies on enormous quantities of data input. This data is provided by people going about their lives – their actions and interactions with systems, products, and apps. Weyl asks, given that our input is what enables technologists to build AI systems, can we create an open marketplace that rewards our contributions?


Weyl discussed his new paper in an interview with Fast Company. Below are a few excerpts from “Can Big Tech Companies Find a Way to Reward Users for Their Data?


[Weyl] says we tend to misunderstand the nature of artificial intelligence. It is not machines replacing humans. It is systems that take human input and repurpose it to drive other systems, he says. An automated car would be the stupidest thing in the world without all the human-derived data helping it to recognize lampposts, street signs, and cyclists. In a sense, we, the users, create these systems, yet all the economic value falls to the people who own the systems.


“We need a society that recognizes that [exchange] and gives credit to the people who are actually producing those [systems],” Weyl says. “That way, the economic rewards flow to those people so they do the best job they can. We can have a fair income distribution and not have everything concentrated in a few owners of big companies.”


Weyl says creating a real, transparent data market could help everyone, even today’s big data titans. If we can make money from our interactions with machines, we might all feel better about the automated future. We might even want to participate in building such systems if we knew the gains were going to everyone, and not just a few people.


Read the full article on Fast Company: “Can Big Tech Companies Find a Way to Reward Users for Their Data?


Abstract for “Should We Treat Data as Labor? Moving Beyond 'Free’
Written by E. Glen Weyl, Imanol Arrieta Ibarra, Leonard Goff, Diego Jiménez Hernández, and Jaron Lanier
American Economic Association Papers & Proceedings, Vol. 1, No. 1, Forthcoming


In the digital economy, user data is typically treated as capital created by corporations observing willing individuals. This neglects users' role in creating data, reducing incentives for users, distributing the gains from the data economy unequally and stoking fears of automation. Instead treating data (at least partially) as labor could help resolve these issues and restore a functioning market for user contributions, but may run against the near-term interests of dominant data monopsonists who have benefited from data being treated as 'free'. Countervailing power, in the form of competition, a data labor movement and/or thoughtful regulation could help restore balance.


Glen Weyl is a Senior Researcher at Microsoft Research and visiting at Yale University's Economics department and Law School as a Senior Research Scholar and Lecturer.