A California group proposes taxing data companies on their “data dependency.”
It’s obvious that data companies make profits by using their customers’ data without paying for it. What’s not obvious is how to get them to cough up. Ten cents for every dog or cat picture you post on Facebook? Five dollars a month for your searches on Google?
A new white paper from an ad hoc group of scholars says paying individuals based on their usage is the wrong way to go about it. Customer data becomes valuable when billions of bits of it are aggregated and analyzed. So governments should tax data companies based on their dependence on user data, and then, rather than parceling out cash to individuals, they should spend the revenue on projects that serve the general public, the scholars say.
“The value of your data is only unlocked when it is combined with data from others,” says the 39-page white paper. “To design a data dividend,” it says elsewhere, “we must think in terms of ‘our data,’ not ‘my data.’”
The white paper is being published by the Berggruen Institute, a Los Angeles-based nonprofit dedicated to reshaping political and social institutions. I was given an advance copy. Data companies and their shareholders won’t like the scholars’ recipe. “Taxation is a tool to transform platform companies from private monopolies to regulated utilities in a manner similar to the way other natural monopolies such as electricity and water have been regulated since the early twentieth century,” they write.
Their paper also envisions the creation of a Data Relations Board, which would function like an environmental protection agency but for data, and a series of “public data trusts” that would contain data for public use. Companies that contributed their data to public data trusts would get a break on their data taxes.
Yakov Feygin, an economist who is associate director of Berggruen’s Future of Capitalism program, coordinated the research project. The other authors are Matthew Prewitt, a lawyer who is president of the RadicalxChange Foundation; Brent Hecht, a computer scientist at Northwestern University; a pair of Ph.D. students at Northwestern, Hanlin Li and Nicholas Vincent; Chirag Lala, a Ph.D. student at the University of Massachusetts; and Luisa Scarcella, a postdoctoral researcher at UAntwerpen DigiTax Center in Belgium.
The scholars admit that they can’t perfectly measure a company’s data dependency. They propose going by its number of users as a proxy for now, with an eye toward other approaches when better measurement technology is available, such as measuring the quantity of user data a company stores or uses.
The white paper is directed mainly to the state government of California. Feygin says in an interview that he got interested in the topic after Governor Gavin Newsom came out in favor of a “data dividend” in his State of the State speech in February 2019, without fleshing out the concept. “We kind of answered the call,” Feygin says. “We wrote it in a California context because the idea came up here first,” but it could be adopted by other states and nations, he adds. He says it’s an improvement on the digital services taxes that several nations have adopted to capture tax revenue from the American tech giants because it’s based on companies’ data dependence rather than revenue.
“This is a long process. There are still a lot of questions that need to be worked out,” Feygin says. “Our focus is on a decade, not the next year.”