If you think online services like Facebook and Google are really free, think again. They come with a price tag–in the form of our personal data, which these companies transform into massive ad revenues. We pay with our privacy and our scattered attention. “If the product is free,” the saying goes, “you are the product.”
Personal data is the “new oil,” in the words of The Economist. And the mining of online data is just the start. Increasingly, the offline world is also a data gold mine. As everything from cars to power plants are added to the internet of things, we’re creating additional petabytes of data-rich resources. Companies can use this data to train algorithms that run new types of services, including traffic directions, automated transport networks, and factories that require only a few humans to operate.
This raises a lot of questions that we’ve only begun to discuss. Will the automation enabled by data capture lead to widespread job losses and increasing income inequality? Will it allow certain data-abundant companies like Alphabet (Google), Amazon, and Facebook to dominate the new economy? Is the economic exchange by which we give over our data fair? Or does it allow those with data advantages to stifle competition, stopping startups from emerging?
A new paper by economists Imanol Arrieta Ibarra, Leonard Goff, Diego Jiménez Hernández, Jaron Lanier, and Glen Weyl argues that we need to re-conceive how we think about our role in the data economy. Instead of acting as mere passive data providers, the economists argue that we need to start thinking of ourselves as the creators of the new data wealth. Instead of being internet users, we need think of ourselves as labor–the workers who are helping companies to build the emerging automated economy.
“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,” the article’s abstract says.
Weyl is a researcher with Microsoft Research, the company’s internal think tank, and coauthor of the soon-to-be published book Radical Markets: Uprooting Capitalism and Democracy for a Just Society. In an interview with Fast Company, he 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. (This point is neatly made by an xkcd cartoon about self-driving cars, which has the punchline: “So much of ‘AI’ is just figuring out ways to offload work onto random strangers.”)
“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.”
Internet companies like Google, Facebook, and Amazon are often criticized for “disrespecting authorship” and trampling on intellectual property rights (think, for instance, about how YouTube posts so much music while paying artists virtually nothing). Silicon Valley has told us that “information wants to be free” except, of course, if you’re talking about the information flowing out of companies like Facebook and Google.
“They say intellectual property rights are bad because they get in the way of the free flow of information, but the exception are the intellectual property rights that protect the dominance of their own platforms,” Weyl says. “We need a regime that’s more balanced where rights are in proportion to the contributions that people are making.”
The paper doesn’t offer concrete suggestions for how to spread data wealth. It’s an opportunity for computer scientists and labor economists to collaborate on new ideas, the report says. There are several big hurdles, including how you value data. Currently, there isn’t a real market to set the price. And there are a number of questions to address: Does data have the same value when it’s traded on an open market as opposed to being exploited by a single company? Does data sitting in a silo command the same dollars as data that builds someone’s algorithm?
There have been early attempts to monetize data on internet users’ behalf, including startups like Meeco and CitizenMe. Blockchain digital ledgers that allow people to control access to their personal data and create online “self-sovereign identities” could create other possibilities (as the app CoverUS, which allows users to sell their health data to lower medical costs, demonstrates). Meanwhile, there are several ideas for reforming antitrust and intellectual property laws. For instance, we could force companies like Facebook to share our data, creating pipelines, or APIs, that third parties could use to create new products and services.
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.