Big Tech is being challenged by a new strain of thought: that it should pay people for their data. The current arrangement — data for free search and friendship services — is insufficient, the new thinking goes.

Why it matters: If adopted, the argument — pressed by tech thinkers, economists and a new book — could erode billions of dollars of profit from companies like Google and Facebook, along with China's Alibaba and Tencent. Meanwhile, an undetermined amount of money, though probably just a few dollars to start, would go into the pockets of ordinary people around the world.

What they're saying: The argument is that data is actually labor — the result of stuff that everyone does in their daily lives. Therefore, if a company is using it for commercial purposes, it should pay the source of the data — you.

In the Weekend FT, tech thinker Jaron Lanier laments that “gargantuan, global data monopsonies” have taken over, retaining the entirety of the economic reward while creating much risk for everyone else.

tech thinker Jaron Lanier laments that “gargantuan, global data monopsonies” have taken over, retaining the entirety of the economic reward while creating much risk for everyone else. In Radical Markets, a book published earlier this year, economist Glen Weyl and law professor Eric Posner predict the rise of data platforms representing ordinary people. They call them "data-labor unions."

a book published earlier this year, economist Glen Weyl and law professor Eric Posner predict the rise of data platforms representing ordinary people. They call them "data-labor unions." The current Economist writes that a mechanism by which the wealth is shared might not actually turn out so bad for Big Tech. "Tech giants’ profit margins are likely to get squeezed, but their overall business may get bigger," the magazine says.

Speaking to Axios, Brookings' Mark Muro says this convergence of thought is legitimate. "It makes total sense that the exploitation of people for their data will lead to new forms of organization for recouping its value, or at least for extracting greater return," he says.

But, but, but: No one thinks it will be easy to devise the compensatory system. Nor, of course, that Big Tech will easily surrender to a new data marketplace.