From Point A to Chaos: The Inversion of Information Economics

If it’s really a revolution, it doesn’t take us from point A to point B, it takes us from point A to chaos.

Clay Shirky, 2005

In 2019, we reel from a series of improbable outcomes. Whether it’s the 2016 US election, Brexit, the resurgence of the theory that the earth is flat, or the decline of vaccination, turns which once seemed unthinkable have arrived in force. Culture war blossoms around developments which some see as progress, and others find threatening and absurd. This coincides with the rise of centralized communication platforms that reward compulsive engagement, indiscriminately amplifying the reach of compelling messages—without regard for accuracy or impact.

Historically, composition and distribution of information took significant effort on the part of the message’s sender. Today, the cost of information transfer has collapsed. As a result, the burden of communication has shifted off the sender and onto the receiver.

Interconnectedness via communications technology is helping to change social norms before our eyes, at a frame rate we can’t adjust to. If we want to understand why we’ve gone from point A to chaos, we need to start by examining what happens when the cost of communicating with each other, in Shirky’s words, “falls through the floor”.

A brief history of one-to-one communication

The year 1787 offers us another moment in time when the communications technology of the day stood to influence the direction of history. The Constitutional Convention was underway, and the former British colonies were voting on whether to adopt the hotly contested new form of government. Keenly aware that news of how each state fell would influence the behavior of those who had yet to cast their votes, Alexander Hamilton assured James Madison, his primary collaborator at the time, that he would pay the cost of fast riders to move letters between New York and Virginia, should either one ratify the Constitution.

The constraints of communications technology back then meant it was possible for an event to occur in one location without people elsewhere hearing of it for days or weeks on end. For this single piece of information to be worth the cost of transit between Hamilton and Madison, nothing less than the future of the new republic had to be at stake.

From a logistical standpoint, moving information from one place to another required paper, ink, wax, a rider, and a horse. Latency was measured in days. Hamilton and Madison’s communications likely benefited from the postal system, which emerged in 1775, to provide convenient, affordable courier service. Latency was still measured in days, but by then it was possible to batch efforts and share labor costs with other citizens.

Around 1830, messages grew faster, if not cheaper, with the advent of the electric telegraph. The telegraph allowed transmission of information across cities and eventually continents, with latency clocking in at a rate of two minutes per character. The sender of a message was charged by the letter, and an operator was needed at each end to transcribe, transmit, receive and deliver the message.

With the telephone, in 1876, it became possible to hold an object to your ear and hear a human voice transmitted in real time. The telephone required an operator to initiate the circuit needed for each conversation, and once they did, back-and-forth could unfold without intermediaries. This dramatic acceleration from letters carried on horseback to the the telephone took place in the space of 89 years. By the early 20th century, phone switching was automated, further reducing the cost of information exchange.

By the 2000’s, mobile phones and the internet enabled email and texting, and instantaneous communication was within reach between anyone in the world who was lucky enough to have access to these technologies in their early days on the consumer market. For these, no additional labor is needed beyond the sender’s composition of the message and the receiver’s consideration of its contents. Automation handles encoding, transmission, relaying, delivery and storage of the whole thing. The time between a message being written and a message being received has been reduced to mere seconds.

Constraints to communication at this phase come to be dictated by access to technology, rather than access to labor.

A brief history of one-to-many communication

While Alexander Hamilton wrote copious personal letters, he also leveraged the mass communications medium of his day, the press, to shape political dialogue. He was responsible for 51 of the 85 essays published in the Federalist Papers. By 1787, publishing had already benefited from the invention of the printing press. The production of written word was no longer rate-limited by the capacity of scribes or clergy, or restricted by the church. Those who were educated enough to write, and connected enough to publish, could do so. Of course, only a select handful of people in the early United States met that criteria.

Samuel Adams was the son of a church deacon, a successful merchant, and a driving force in 1750s Boston politics. Benjamin Franklin apprenticed under his brother, a printer, and eventually went on to take up the trade, running multiple newspapers over his lifetime. In 1765, Samuel Adams falsely painted Thomas Hutchinson as a supporter of the Stamp Act in the press, leading a mob of arsonists to burn down Hutchinson’s house. Meanwhile, Franklin created a counterfeit newspaper claiming the British paid Native Americans to scalp colonists which he then circulated in Europe to further the American cause. It’s not that fake news is a recent phenomenon, it’s that you used to have to have special access to distribute it.

Soon, other media emerged to broadcast ideas. By the 1930’s, radio was a powerful conduit for culture and news, carrying both current events and unique entertainment designed for the specific constraints of an audio-only format. Radio could move over vast distances, and it did so at the speed of light. At the same time, radio required specialist engineers to operate and maintain the expensive equipment needed to transmit its payload. It required more specialists to select and play the content people wanted to hear.

Television emerged using similar technology, with additional overhead. As well as all the work needed for transmission, television required additional specialists and elaborate equipment to capture a moving image.

Radio and television both operated over electromagnetic spectrum which was prone to interference if not carefully managed. By necessity spectrum is regulated, which creates scarcity, making the owners of broadcast companies powerful arbiters of the collective narrative.

So between print, radio and television, a handful of corporations determined what was true, what would be shared with the masses, and who was allowed to be part of the process.

Force multipliers in communication

Eventually, innovations in the technologies above began to cannibalize and build off of one another, helping the already declining cost of information transfer fall even faster.

By the late 1800’s, typewriters allowed faster composition of the written word and clearer interpretation for the recipient. By the late 1970’s, the electronic word processor used integrated circuits and electromechanical components to provide a digital display, allowing on-the-fly editing of text before it was printed.

Then, the 1980’s saw the rise of the personal computer, which absorbed the single use device of the word processor, folding it in and making it just another software application. For the first time, the written word was now a stream of instantly visible, digital text, making the storage and transmission of thoughts and ideas easier than ever.

Alongside the PC, the emergence of packet-switched networks opened the door to fully-automated computer communications. This formed the backbone of the early internet, and services ranging from chat to newsgroups to the web.

The arrival of the open source software revolution around the year 2000 enabled unprecedented productivity for software teams. By making the building blocks of web software applications free and modifiable to anyone, small teams could move quickly from concept to execution without having to sink time into the basic infrastructure common to any site. For example, in 2004, Facebook was built in a dorm room using Linux as the server operating system, Apache as its web server, MySQL for its database, and php as its server-side programming language. Facebook helped usher in the current era of centralized, corporate-controlled, modern social software, and it was built on the back of open source.

The pattern seen in the evolution from printing press to home PC is repeated and supercharged when we encounter the smartphone. By 2010, smartphones paired the ability to record audio and video with a constant internet connection. Thanks to the combination of smartphones and social software, everyday consumers were granted the ability to capture, edit and distribute media with the same global reach as CNN circa 1990. This had meaningful impact during the protests against police violence in Ferguson, Missouri, in 2014. Local residents and citizen journalists streamed real-time, uncut video of events as they unfolded—without having to consult any television executives.

In the end, this is a story of labor savings. Today, benefits from compounding automation and non-scarce information technology resources, like open source code, have collapsed the amount of human labor needed to reach mass audiences. An individual can compose and transmit content to an audience of millions in an instant.

This leverage for communication does not have a historical precedent.

Dissolving norms

As the cost of information transfer grows rapidly cheaper, structures and dynamics which once seemed solid have become vertiginously fluid.

In the pre-internet age, you had producers and you had consumers. Today, large-scale social platforms are simultaneously media channel and watering hole, and power users may shift between being both producer and consumer in a single session. The distinction between one-to-one and one-to-many communication has also become far less clear. A broadcast-style message may result in a public response from a passerby which catalyzes an interaction between the passerby and the original poster, with lurkers silently watching the exchange unfold. Later, the conversation may be resurfaced and re-broadcast out by a third party.

The intent of our communications also aren’t always fully known to us when we enact them, and the results can be disorienting. We’ve become increasingly accustomed to mumbling into a megaphone, and people may face lasting consequences for things they say online. Ease of distribution has also blurred the lines between public and private communication. In the past, even the act of writing a letter to a single individual involved significant costs and planning. Today, the effort required for writing a letter and writing an essay seen by millions is functionally identical—and basically free.

Meanwhile, professional broadcast networks are no longer the final arbiters of our collective narrative. Journalism used to be the answer to the question “How will society be informed”? In a world of television, radio and newspaper, those who controlled the exclusive organs of media decided what the audience would see, and therefore what it meant to be informed.  Defining our shared narratives is now a collaborative process, and the question of what is relevant has billions of judges able to weigh in. Today we have shifted, according to An Xiao Mina, from “broadcast consensus to digital dissensus”.

Uncharted waters

In 2019, we face an inversion of the economics of information. When the ability to send a message is a scarce resource, as it was in 1787, you’re less likely to use those mechanisms to transmit trivial updates. Today, the extreme ease of information transfer invites casualness which begets the inconsequential. Swimming in these waters is leaving us open to far more noise masquerading as signal than in eras past.

Many of us can attest that the time between considering what we want to say and getting to say it has shrunk to minutes or seconds, and the messages we send are increasingly frequent and bite-sized, thought out on-the-fly. When this dynamic compounds over time and spreads across the human culture, with both individuals and institutions taking part, we find ourselves experiencing the cognitive equivalent of a distributed denial-of-service attack through an endless torrent of “news,” opinion, analysis and comment. Just ask the Macedonian teenagers making bank churning out fake news articles.

To make sense of this, we’ll need design patterns, technologies, narratives, and maybe even whole disciplines which don’t exist yet. The decline of broadcast consensus brings an enormous, painful loss of clarity about our world, but it simultaneously creates opportunities for voices who were missing in eras past. We’ve sailed off the side of the map, into waters not yet charted. Now, we’re called on to relearn how to navigate, even as our instruments are rendered useless. And we need all the help we can get.



Facebook Moderation and the Unforeseen Consequences of Scale

Parable of the Radium Girls

In 1917, a factory owned by United States Radium in Orange, New Jersey hired workers to paint watchfaces with self-luminescent radium paint for military-issue, glow-in-the-dark watches. Two other factories soon followed in Ottawa, Illinois and Waterbury, Connecticut. The workers, mostly women, were instructed to point the tip of their paint brushes by licking them. They were paid by the watchface, and told by their supervisors the paint was safe.

Evidence suggested otherwise. As employees began facing illness and death, US Radium initially rejected claims that radium exposure might have been more damaging than they’d first led workers to believe. A decade-long legal battle ensued, and US Radium eventually paid damages to their former employees and their families.

The Radium Girls’ story offers us a glimpse into a scenario where a technological innovation promised significant economic return, but its effects on the people who came into daily contact with it were unknown. In the course of pursuing the economic opportunity at hand, the humans doing the line work to produce value wound up doubling as lab rats in an unplanned experiment.

Today, regulations would prohibit a workplace that exposed workers to these hazards.

The unforeseen consequences of unplanned experiments

This week, the Verge’s Casey Newton published an article examining the lives of Facebook moderators, highlighting the toll taken on people whose job it is to handle disturbing content rapid-fire, on a daily basis. The employees at Cognizant, a company contracted by Facebook to scale the giant social network’s moderation workforce, make $15/hour and are expected to make decisions for 400 posts each day at a rate of 95% accuracy. A drop in numbers calls a mod’s job into question. They have 9 minutes/day of carefully monitored break time. The pay is even lower for Arabic-speaking moderators in other countries, who make less than six dollars per day.

Facebook has 2.3 billion global users. This means, by sheer size of the net being cast, moderators will encounter acts of graphic violence, hate speech, and conspiracy theories. Cognizant knows this, and early training for employees involves efforts to harden the individual to what the job entails. After training, they’re off to the races.

Over time, exposure is reported to cause a distorted sense of reality. Moderators begin developing PTSD-like symptoms. They describe trouble context-switching between the social norms of the workplace and the rest of their lives. They are legally enjoined from talking about the nature of their work with friends or loved ones. Some employees begin espousing the viewpoints of the conspiracy theories they’ve been hired to moderate. Coping mechanisms take the shape of dark humor, including jokes about suicide and racism, drugs, and risky sex with coworkers. There are mental health counselors available on-site, however, their input boils down to making sure the employee can continue doing the job, rather than concern for their well-being beyond the scope of the bottom line.

“Works as intended”

When Facebook first started building, they weren’t thinking about these problems. Today, the effects of global connectivity through a single, centralized platform, populated with billions of users, with an algorithm dictating what those users see, is something we have no precedent for understanding. However, as we begin the work of trying to contend with the effects of technology-mediated communication at unprecedented scale, it’s important to identify a key factor in Facebook’s stewardship of their own platform: the system is working as intended. I’ve long noted that if scale is a priority, having garbage to clean up in an online network is a sign of success, because it means there are enough people to make garbage in the first place.

The very reality that human moderators need to do this work at such magnitude means Facebook is working extraordinarily well, for Facebook.

Let’s explore this for a moment. The platform’s primary mode has long been to assemble as many people as possible in one place, and keep them there as long as possible. The company makes money by selling ads, so number of users and quantity of time on the site is their true north. The more people there are on the site, and the longer they spend there, the more opportunities for ad impressions, resulting in more money. They are incentivized to pursue this as thoroughly as possible, and under these strict parameters, any measure which results in more users and more engagement is a good one.

Strong emotional reactions tend to increase engagement. The case study of the network’s role in the spreading of rumors which led to mob violence in Sri Lanka provides a potent look at how the company’s algorithms can exacerbate existing tensions. “The germs are ours, but Facebook is the wind,” said one person interviewed. So on the one hand, Facebook is incentivized to get as many users as possible and get them as riled up as possible, because that drives engagement, and thus profit. Some of the time, that will produce content like that which moderators at Cognizant need to clean up. To keep this machine running, human minds need to be used as filters for psychologically toxic sludge.

Facebook could make structural platform shifts which would reduce the likelihood of disturbing content showing up in the first place. They could create different corners of the site where users go specifically to engage in certain activities (share their latest accomplishment, post cooking photos), rather than everyone swimming in the same amorphous soup. They could go back to affiliations with offline institutions, like universities, and make your experience within these tribes be the default experience of the site. Or they could get more selective about who they accept money from, or whom they allow to be targeted for ads. But I’m sure any one of these moves would damage their revenues at numbers that would boggle our minds. Facebook’s ambition for scale, and their need to maintain it now that they have it, is working against creating healthier experiences.

Like the Radium Girls, Facebook moderators are coming into daily contact with a barely-understood new form of technology so that others may profit. As we begin to see the second order effects and human costs of these practices and incentive systems, now is a good time for scale to be questioned as an inherent good in the business of the internet.