Slashdot Mirror
What if People Were Paid For Their Data? (economist.com)
Advocates of "data as labour" think users should be paid for using online services. An anonymous reader shares a report: Labour, like data, is a resource that is hard to pin down. Workers were not properly compensated for labour for most of human history. Even once people were free to sell their labour, it took decades for wages to reach liveable levels on average. History won't repeat itself, but chances are that it will rhyme, Glen Weyl, an economist at Yale University, predicts in "Radical Markets," a provocative new book he has co-written with Eric Posner of the University of Chicago. He argues that in the age of artificial intelligence, it makes sense to treat data as a form of labour. To understand why, it helps to keep in mind that "artificial intelligence" is something of a misnomer. Messrs Weyl and Posner call it "collective intelligence": most AI algorithms need to be trained using reams of human-generated examples, in a process called machine learning. Unless they know what the right answers (provided by humans) are meant to be, algorithms cannot translate languages, understand speech or recognise objects in images. Data provided by humans can thus be seen as a form of labour which powers AI.
As the data economy grows up, such data work will take many forms. Much of it will be passive, as people engage in all kinds of activities -- liking social-media posts, listening to music, recommending restaurants -- that generate the data needed to power new services. But some people's data work will be more active, as they make decisions (such as labelling images or steering a car through a busy city) that can be used as the basis for training AI systems. Yet whether such data are generated actively or passively, few people will have the time or inclination to keep track of all the information they generate, or estimate its value. Even those who do will lack the bargaining power to get a good deal from AI firms. But the history of labour offers a hint about how things could evolve: because historically, if wages rose to acceptable levels, it was mostly due to unions. Similarly, Mr Weyl expects to see the rise of what he calls "data-labour unions," organisations that serve as gatekeepers of people's data. Like their predecessors, they will negotiate rates, monitor members' data work and ensure the quality of their digital output, for instance by keeping reputation scores. Unions could funnel specialist data work to their members and even organise strikes, for instance by blocking access to exert influence on a company employing its members' data. Similarly, data unions could be conduits channelling members' data contributions, all while tracking them and billing AI firms that benefit from them.
As the data economy grows up, such data work will take many forms. Much of it will be passive, as people engage in all kinds of activities -- liking social-media posts, listening to music, recommending restaurants -- that generate the data needed to power new services. But some people's data work will be more active, as they make decisions (such as labelling images or steering a car through a busy city) that can be used as the basis for training AI systems. Yet whether such data are generated actively or passively, few people will have the time or inclination to keep track of all the information they generate, or estimate its value. Even those who do will lack the bargaining power to get a good deal from AI firms. But the history of labour offers a hint about how things could evolve: because historically, if wages rose to acceptable levels, it was mostly due to unions. Similarly, Mr Weyl expects to see the rise of what he calls "data-labour unions," organisations that serve as gatekeepers of people's data. Like their predecessors, they will negotiate rates, monitor members' data work and ensure the quality of their digital output, for instance by keeping reputation scores. Unions could funnel specialist data work to their members and even organise strikes, for instance by blocking access to exert influence on a company employing its members' data. Similarly, data unions could be conduits channelling members' data contributions, all while tracking them and billing AI firms that benefit from them.
If no one can sell any of your data then companies will just raise their prices to cover the full costs of their products and services. Like no more free Strava on the iphone or apple watch. If you want a run/biking tracker you'll have to pay per device. Just like the old days.
before facebook there was classmates that charged money for contact info and messaging. and some other service that sold something like a yearbook but with recent contact info.
facebook was free and why people chose it
But it's already in place. Many of these services are free just because of the fact they can sell your data.
I fail to see the problem.
This just let's us get back to actually owning the products we paid for one way or the other.
Bonus points if it gets us back to "still works offline."
You can fuck off about the free bullshit.
It's you property and it has a lot of value which you are not being compensated for, pure and simple. If they want your data bad enough they should be prepared to pay for it.
they've had driving apps with offline access on the iphone for many years. I've used Navigon. It was $20 for the US map collection and different prices for different regions all over the world. worked great in a national park with no cellular service on an old iphone 4.
As for what they "like" or purport to like, that is equally dubious. Apart from the gap between what people say and what they will actually do, once you start paying people for all the "likes" they give you will find they start liking everything. The data becomes worthless.
The point about placing a value on data, as with labour, misses another basic point. Labour adds value - and that is what people are paid for. Not for the act of working X hours a day, but that the product of their labour increases the value of the goods sold: turning raw material into products, turning services into benefits. Unless data from 7 or 8 billion people can be applied to produce something of value, then it is worthless.
politicians are like babies' nappies: they should both be changed regularly and for the same reasons
You can't buy my data, but you can rent it via a subscription model.
The problem is that companies are used to running roughshod over privacy laws. Even the GDPR has not been tested. Since they are used to a privacy gravy train, it will take not just laws, but enforcement (fines, raids, C-levels facing prison time) for companies to actually take privacy seriously.
Even with the GDPR, as it stands now, if a CEO finds out that their firm is in trouble, they short their stock, let the EU find the company into the ground, and laugh all the way to the bank.
This reminds me of stories I've read in many Slashdot comments. You know, the ones that talk about tech people training their (much lower salaried) replacements. This time the 'replacement' is AI, and it's not just tech workers being replaced, it's just about everyone.
Besides, people are already being 'paid' for much of their data, in the form of services that they don't have to open their wallets for. I'm sure Google, Facebook, and the like, consider those services to be fair and sufficient payment. Judging by the vast number of users who keep using the services and don't kick up a fuss, I'd say the majority of people using those services are in agreement. Or they just don't care, which amounts to the same thing.
'The Economy' is a giant Ponzi scheme whose most pitiable suckers are the youngest among us and the yet-unborn.