Our economies are messed up. And the cause is the Internet.

Imagine that someone told you that three of the biggest stories of the past few years — the financial crisis, exploding economic inequality, and the National Security Agency spy scandal — weren’t actually different stories at all. Different in detail, yes, but essentially identical in their deeper cause. The cause, they go on to say, wasn’t greed or fear or the age of terrorism or anything else linked to human fallibility, but technology — specifically, computation and its networked manifestation, the Internet. Sound crazy?

Well, it doesn’t if you hear out Jaron Lanier’s full argument. Lanier is a Silicon Valley guru and one of the pioneers of virtual reality technology; he’s helped build today’s technological reality and is anything but a Luddite about technology and its potential for helping people. But he does think the Internet has gone off the rails, that we’re developing it in the wrong way, benefiting technology more than people, and by design driving our economies into the swamp. I’ve come a little late to Lanier’s book of last year — Who Owns the Future? — but I think it’s one of the most important things I’ve read in a decade.

Let’s take things in turn. First, the financial crisis.

I’ve never thought about the financial crisis as being primarily a consequence of technology. We’ve obviously had plenty of banking crises and financial bubbles in the past, even without the Internet. But look a little closer and I think it’s quite sensible to claim that cheap computation and networked information did drive or at least amplify and accelerate the whole thing. It wasn’t just financial engineering that led to the crisis, but computational financial engineering. No bank could have sliced and diced and assembled thousands or millions of questionable mortgages into apparently low-risk portfolios and sold them on to investors around the world without the aid of cheap and ubiquitous computation and access to networked information on a global scale. Computation alone made it possible to keep track of all the details needed to manufacture the deception.

As a writer, Lanier builds his works out of near aphorisms:

Since networking got cheap and computers became enormous, the financial sector has grown fantastically in proportion to the rest of the economy, even though it has done so by putting the rest of the economy at increased risk. This is precisely what happens naturally, without any evil plan, if you have a more effective computer than anyone else in an open network. Your superior calculation ability allows you to choose the least risky options for yourself, leaving riskier options for everyone else.

… Liars have to have the best memories. It’s more work to keep two sets of books than one set of books. The plague of toxic assets and mega-pyramid schemes, and the pointless growth spurt of the financial services sector would all have been impossible without vast computational resources remembering and sorting all the details needed to snooker people. The most egregious modern liars not only need computers, they can be inspired by them… It was only recently that computation became inexpensive enough to be used to hide bad assets.

I think this is a decisive insight, and something that has been mostly overlooked. Economists have treated this recent financial crisis as something more or less similar to those in the past (different, maybe, because of the rise of shadow banking, which economists had mostly ignored). But it was driven by an information advantage created by cheap computation and networking technology. (It’s also obvious, of course, that high-frequency trading, which now dominates most markets, would not exist without computing technology.)

The second great effect Lanier sees issuing directly from network technology is exploding economic inequality and the hollowing out the middle class. This is, in one sense, fairly obvious, especially in developed nations, where manufacturing technology (computing + automation in many forms) has eradicated many low-skill jobs. It’s probably true also that networked information technology has amplified the power differential between businesses and workers. But Lanier argues that another, less obvious dynamic is actually more influential — and is built into the nature of online business in today’s Internet.

Here’s the perverse logic. The Internet generation has grown up championing the value of free information. It sounds great; the idealists haven’t been entirely crushed. We have free file sharing of music and video, free email, free social networking, free online services of as many kinds as you care to find. “Information wants to be free,” expresses a new cultural value of wide appeal. But all this free content, Lanier points out, isn’t actually as free as it seems — it comes with a hidden cost. Several kinds of costs, in fact.

It’s all driven, of course, by advertising. The culture of free information and content implicitly accepts a Faustian bargain with the purveyors and users of Big Data. The vast spying apparatus is one consequence — another is economic inequality and the loss of a broad well-supported middle class. After all, the people who actually produce the value of online services such as Facebook or Google — that is, the users of those services — aren’t the people who ultimately get rewarded for that value, at least not in a financial way. The people producing the data don’t get paid for it; rather, the monetary value accrues to the owners of the big network servers that organize this data and make it usable.

By luring people to give away their personal data for free, digital networking firms can gather vast data at almost no cost. Hence, the biggest profits flow directly toward the biggest servers which dominate information flows on the web, and these servers are often controlled by only a small number of people. The overall result is a diabolical impoverishment of everyone except for a very few, and very little value flowing back to the many who contributed to make it all possible:

It’s magic that you can upload a phrase in Spanish into the cloud services of companies like Google or Microsoft, and a workable, if imperfect, translation to English is returned. It’s as if there’s a polyglot artificial intelligence residing up there in the great cloud server farms.

But that is not how cloud services work. Instead, a multitude of examples of translations made by real human translators are gathered over the Internet. These are correlated with the example you send for translation. It will almost always turn out that multiple previous translations by real human translators had to contend with similar passages, so a collage of those previous translations will yield a usable result.

A giant act of statistics is made practically free because of Moore’s Law, but at core the act of translation is based on the real work of people.

Alas, the human translators are anonymous and off the books. The act of cloud-based translation shrinks the economy by pretending the translators who provided the examples don’t exist. With each so-called automatic translation, the humans who were the sources of the data are inched away from the world of compensation and employment. At the end of the day, even the magic of machine translation is like Facebook, a way of taking free contributions from people and regurgitating them as bait for advertisers or others who hope to take advantage of being close to a top server.

Think about it. The most successful companies yesteryear, say Kodak or IBM, typically employed tens of thousands of people; today we have companies like Instagram employing only 13 while being worth more than a billion dollars (and maybe five times that much). Facebook has more employees, around 7,000, but that’s still a pretty small number. This trend, Lanier suggests, is simply a consequence of digital networking and the dominance of whichever server becomes the biggest.

And we should expect, he suggests, a lot more of the same unless the Internet changes in a radical way. Digital technology is not going to get any weaker or less capable. It’s going to start erasing jobs moving right up the ladder of human skills:

Making information free is survivable so long as only limited numbers of people are disenfranchised. As much as it pains me to say so, we can survive if we only destroy the middle classes of musicians, journalists, and photographers. What is not survivable is the additional destruction of the middle classes in transportation, manufacturing, energy, office work, education, and health care. And all that destruction will come surely enough if the dominant idea of an information economy isn’t improved.

OK. Enough diagnosis of the problem. Lanier doesn’t stop there, but makes a broad if necessarily somewhat vague proposal for how the Internet could be changed to work better for everyone. The nub is that information shouldn’t actually be free, however enticing this may seem. What we gain from free services at first, we more than pay for through long-term damage to our economic lives — as well as to democratic freedom. A better and healthier Internet, Lanier suggests, has to be based on the principle that when people create value, however they do it, that value should be properly accounted for — they should be paid for it.

I’ve often been critical of economists fetish of putting a price on everything and believing that the price mechanism is a miraculous device capable of solving any problem. They vastly overstate the case. However, I think Lanier is right in this instance. He suggests that a broad middle class capable of supporting a vibrant capitalist economy can only be nurtured if all the people who actually create the value of the Internet get paid for the information they currently supply for free. Digital networking technology is more than sophisticated enough to track value creation across all the world’s users, so as to provide the information required for a system of micropayments — people who create value, no matter where and when it was ultimately used, would get paid for it. Here’s Lanier’s description:

My goal is to portray an alternate future in which people are treated appropriately as being special. How? … Pay people for information gleaned from them if that information turns out to be valuable. If observation of you yields data that makes it easier for a robot to seem like a natural conversationalist, or for a political campaign to target voters with its message, then you ought to be owed money for the use of that valuable data. It wouldn’t exist without you, after all. This is such a simple starting point that I find it credible, and I hope to persuade you about that as well.

The idea that mankind’s information should be made free is idealistic, and understandably popular, but information wouldn’t need to be free if no one were impoverished. As software and networks become more and more important, we can either be moving toward free information in the midst of insecurity for almost everyone, or toward paid information with a stronger middle class than ever before. The former might seem more ideal in the abstract, but the latter is the more realistic path to lasting democracy and dignity.

An amazing number of people offer an amazing amount of value over networks. But the lion’s share of wealth now flows to those who aggregate and route those offerings, rather than those who provide the ‘raw materials.’ A new kind of middle class, and a more genuine, growing information economy, could come about if we could break out of the ‘free information’ idea and into a universal micropayment system. We might even be able to strengthen individual liberty and self-determination even when the machines get very good.

… In a world of digital dignity, each individual will be the commercial owner of any data that can be measured from that person’s state or behavior. Treating information as a mask behind which real people are invariably hiding means that digital data will be treated as being consistently valuable, rather than inconsistently valuable. In the event that something a person says or does contributes even minutely to a database that allows, say, a machine language translation algorithm, or a market prediction algorithm, to perform a task, then a nanopayment, proportional both to the degree of contribution and the resultant value, will be due to the person.

These nanopayments will add up, and lead to a new social contract in which people are motivated to contribute to an information economy in ever more substantial ways. This is an idea that takes capitalism more seriously than it has been taken before. A market economy should not just be about ‘businesses,’ but about everyone who contributes value.

Lanier’s book is eye opening and, I think, profound. I’ll never see the Internet in quite the same way again. I know some economists have speculated that technology is somehow driving increasing inequality, but they usually put it down to some imbalance in education — those with high tech skills get ahead relative to others. Lanier’s take is deeper and I think makes more sense — the basic game plan of the Internet is messing up our economies, and driving increasing inequality in what we might well call an algorithmic way. Meanwhile we’ve helped create the infrastructure for a vast surveillance society — and we’re giving them our personal data for free!

“The strange way we’ve built our networks,” as Lanier puts it, “has backfired.”

I think he’s right.