Should We Treat Data as Labor?

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Moving Beyond “Free”. Competition Conference 2018. Boston University School of Law. July 23, 2018. E. Glen Weyl. Microsoft and Princeton. Imanol Arrieta Ibarra. Stanford. Diego Jiménez Hernández. ID: 754152 Download Presentation

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Should We Treat Data as Labor?

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Should We Treat Data as Labor?Moving Beyond “Free”

Competition Conference 2018Boston University School of LawJuly 23, 2018

E. Glen Weyl

Microsoft and Princeton

Imanol Arrieta Ibarra


Diego Jiménez Hernández


Leonard Goff


Jaron Lanier




Free Services for Free DataThe digital economy encompasses many of the most popular products ever. It creates surplus for end users and tech companies.





The High Cost of Free DataDespite these advances, there has been backlash against tech companies.



An Anxious Time For Labor

(Autor et al. 2017)

Fears about future of AI and job displacement

Growing inequality


AI and ProductivityThe “free-data” model has failed to induce the “AI-revolution” in productivity.



The High Cost of Free Data


The High Cost of Free DataRoot of all of these problems is that returns to data are being treated as payments to capital rather than to labor.


Data as Capital vs. Data as Labor

Data is exhaust

to be picked up by whoever is smart enough to make usefulAI success mostly driven by algorithms, computational power, brilliant programmers

AI will flourish if there are big payoffs to entrepreneurs and innovators

AI will displace workers, so either they will work in other areas or we will give them a basic income now that they are uselessPeople will have to

find meaning in areas of life other than work and “get over themselves”Individuals are happy to consent to

surveillance in exchange for “free stuff”, so companies deserve to use their data

Data created by user actions and efforts, so fruits

belong first to individual contributors

AI is really collective human intelligence

, driven by innate knowledge/data in ordinary people

AI will flourish if the

individual contributors who make it possible

have a real economic stake

AI is just another production technology that

raises individual productivit


by allowing people to amplify the value of their data

The value of data will support sense of

meaning and “digital dignity”

Individuals on their own have little bargaining power in face of digital monopolies,

must be protected by countervailing power

(competition, unions or governments)


How Did We Get Here?Current status quo comes from a mix of:Prejudice (weight of precedent created by historical accidents)

Privilege (entrenched interests that derive rents from the inefficient equilibrium)The “internet” business-model: convince users to give their data for free in exchange of a digital service.Users grew accustomed to this model.Few users are even aware of the productive value of their data or the role they play in enabling ML to target advertise them. Recent evidence suggests significant monopsony power in online task labor markets (Dube et al (2018)).



Sources of Countervailing PowerThere are three main channels to balance out the scale:



Data Labor Union

Government Action


Recent policy developments11

GDPR came into effect

First Data Labor Union in Holland

Merkel considers data tax



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