The Art of Eyeball Harvesting

Shengwu Li on Online Advertising

A still from Fritz Lang's Metropolis (1927).

We’re told we’re living in an attention economy. Sites and platforms harvest our data, then use it to place targeted ads in our path. But how does this business model actually work? What are the processes and practices taking place behind the scenes that make this lucrative arrangement possible?

We spoke to Shengwu Li, an assistant professor of economics at Harvard, to learn more about the deep machinery of the attention economy.

Can you start by telling us a little bit about your area of expertise?

I work on behavioral economics and game theory, so I study insights from psychology and build them into mathematical models of human behavior. In particular, I’m interested in what we call market design.

For a lot of the history of economics, we've taken as given the way that market institutions work. Market design turns that on its head. It says that instead of taking the rules of the market as given, we should look at how those rules are written.

There are any number of times where the government or a private company needs to set up a market. For example, the Federal Communications Commission (FCC) might be selling the rights for companies to broadcast over a certain band of the wireless spectrum. The agency needs to come up with a set of rules that determines who pays them what for which portion of the spectrum. That's a market design question.

How are big tech companies engaged in market design?

Google and Facebook get most of their revenue from selling advertising. So they’ve had to design a system that enables advertisers to transact with them.

The evolution of that system has been very ad hoc. It started at Google. Early on, the company realized that it needed a way to allocate the different ad slots that appear next to its search results to different advertisers. So it started looking at something called a “second-price auction.” This is a kind of auction that gets invented by William Vickrey in the 1960s.

At the time, there were two standard auction formats: the first-price auction and the ascending auction. The first-price auction is where we all simultaneously submit bids and the highest bidder wins. The ascending auction is the one we generally think of when we picture an auction: there's somebody with a gavel and the price keeps going up and everybody drops out except the highest bidder and that person wins.

Vickrey recognized that both types of auctions have their advantages. One obvious virtue of the first-price auction is that everybody can participate asynchronously at a distance. We don’t all have to be in the room bidding at the same time. Logistically, it’s very efficient.

On the other hand, one virtue of the ascending auction is that it’s easy to know how to bid. You watch the price go up and once it's above your value, you quit. It’s simple: you keep bidding at all prices below your value, and you quit at all prices above your value.

Whereas in a first-price auction, you really need to strategize. You need to say, “Okay, I guess this object is worth $1000 to me, but if I get it for $1000 then I walk away no better off than I was before, so I should put in a bid somewhere below $1000.” But how much below $1000? That depends on what I think the other bidders are going to do—and what the other bidders do depend on what they think I’m going to do. It’s potentially a very complicated calculation.

So in 1961 Vickrey writes a paper where he proposes a new kind of auction that combines the benefits of both formats. In this new kind of auction, we can all submit bids asynchronously and we don’t need to strategize. Here’s how it works: everybody bids, the highest bidder wins, and then the winner pays the second-highest bid. Thus the second-price auction was born.

Why does that solve the problem of strategy? Why don't you have to strategize in a second-price auction?

The trick is to see that there is a neat isomorphism between the price you choose to quit at in an ascending auction and a bid that you place in a second-price auction. Instead of running an ascending auction and having everybody decide dynamically at the time when to quit, you can just ask everybody when they are going to quit in advance and call that their bid. The highest bidder will win and then pay the second-highest bid.

This encourages you to submit a bid at however much you value the object. So if you value the object at $1000, it is better to bid $1000 than to bid any other amount. And that's true regardless of the other players’ behavior.

What happens to Vickrey’s idea?

Mostly it gets ignored. No real auctioneers adopt this way of selling things. Then, about a half-century later, in the early 2000s, Google picks it up and dusts it off as they’re figuring out how to sell ads.

If you’re searching for car insurance on Google, a bunch of companies that sell car insurance want to place their ads next to those search results. Google needs to figure out a way to determine which companies get to put their ads where. Let's say there are three slots for ads on the page with the search results. There is the top slot, which is the most valuable because people see it first. Then there is the second slot below it, which is less valuable, and the third slot even further down, which is the least valuable.

Google decides it’s going to run an auction to determine which advertiser gets which slot. Google knows roughly how many clicks each slot will get. For example, they may know that the top slot gets clicked 300 times for every 10,000 views, the second slot 200, the third slot 100.

When advertisers submit their bids in the auction, they’re submitting their bid per click. They’re saying how much they’re willing to pay Google for each click they get. The highest bidder gets the top slot, the second-highest bidder gets the second, and the third-highest bidder gets the third.

The payment works in the following way. The top slot is worth 300 clicks. If you bid ten and I bid nine, you win the top slot and you’re going to pay my bid—the second-highest bid—times 300 clicks. And if I bid nine and somebody else bids eight, I'm going to pay eight, the third-highest bid, times 200 clicks, which is how many clicks the second slot is worth. And then let's say somebody else bid five. That person, the third-highest bidder, pays the fourth-highest bid times 100 clicks, which is how many clicks the third slot is worth.

So Google implements something that looks a lot like Vickrey's idea.

Do they cite Vickrey?

Their advertising materials for what they called the “generalized second-price auction” claimed that it used “Nobel Prize-winning economic theory to eliminate... that feeling that you’ve paid too much.” So they directly draw a line to Vickrey and his academic credentials as a justification for the format that they're using. Except they get it wrong.

How so?

A defining feature of a Vickrey's auction is the “dominant strategy property.” This means there is a strategy that will always perform the best no matter what any of the other players do. In the case of Vickrey’s auction, the dominant strategy is to bid your value.

Now, there is a correct way to generalize Vickrey's auction to preserve this property. But Google did not do it correctly, at least not at first. The way Google did it, there were times when you should strategize. Sometimes you can benefit by misrepresenting your value per click.

When is that?

Let's say there are a bunch of advertisers who are already in the three slots. You come in as a new advertiser, you submit the highest bid per click, and you take the top slot. Now, Google's auction made you pay for displacing the previous top bidder down to the second slot. But that's not the full effect of your participation. What you've really done is knock everybody below you down one rung of the ladder, but Google’s auction instead charged you as though you knocked the top bidder out entirely. It doesn’t account for this waterfall effect.

The point of Vickrey's auction is that it charges you your externality. It charges you an amount equal to what all the other bidders lose due to your participation. It turns out that there were certain circumstances where Google wasn’t calculating that externality correctly—and advertisers could benefit from bidding slightly less than their value.

Was that miscalculation good for Google?

It's certainly possible that if people misunderstand the auction this way, Google might make more money. But this also gets to an important issue: whether or not people are willing to play in your auction depends on how user-friendly it is. If Google's auction requires players to strategize in order to bid well, it's entirely possible that fewer bidders will be willing to participate.

It's one thing if your only job in Google's auction is to figure out how much a click is worth to you. That's difficult enough because you need to rule out the bots, you have to think about your sales model, and so on. But if on top of all of that you also have to think about how everybody else is bidding—and come up with an optimal strategy given the possible strategies of other bidders—the ensuing complexity will deter a lot of participation.

Anyway, the format that Google starts using in the early 2000s has this problem. And it remains for almost a decade. It's only fairly recently that Google has adopted the correct generalization of Vickrey's auction that accounts for the waterfall effect.

What about Facebook? How do they sell advertising?

In Google you're mostly bidding on keywords. You're placing ads around certain search terms, like “car insurance.”

Facebook is selling a more personal product because Facebook knows a lot about you. It also has expert data scientists who can take everything Facebook knows about you and infer clever things from it.

The result is that advertisers can’t bid on Facebook the way they bid on Google because they don’t know what an ad is worth. They can’t take all that data that Facebook has—your gender, race, age, interests, social graph, online history, and so on—and turn it into, "Here's how much we think it's worth to show this person an ad for a ski holiday." Moreover, there are black-box machine learning algorithms that Facebook uses internally to help calibrate each campaign. It would be difficult to explain them to potential advertisers—and it's not even clear that Facebook can explain them to itself.

So Facebook adopted a different solution to selling ads. Instead of placing a bid, you tell Facebook what kind of ad campaign you want to run and they bid on your behalf. And then there's something like Vickrey's auction running in the background deciding who bids what and at what price.

That doesn’t really sound like a market anymore.

That's the oddness of it. It’s as if you went to a supermarket and rather than the owner saying, “Here are all the prices, please buy what you want,” the owner says, “Why don't you tell me how you're feeling this week and what you have a taste for, and I’ll find the optimal bundle and tell you how much it costs. Don't worry, I know my warehouse much better than you do.”

One of the weaknesses of game theory as a way of thinking about the world is that it assumes we all know the rules of the game we're playing. But when some players have the lion’s share of the information, and when there are black-box algorithms in the middle, it becomes impossible for all of the players to understand the game they’re playing.

Facebook isn’t telling advertisers, “Here's the price you would need to pay to buy Mary’s eyeballs versus Adam’s eyeballs and here's all of the information you would need to make the decision about whose eyeballs you should purchase.” Instead, Facebook is saying, “Tell us about your advertising campaign, and we will figure out what you would have rationally done if you had access to our troves of information.”

Do advertisers not care about that lack of transparency?

Whenever there is a black-box element to a system, that system has to run on trust. When Facebook says they know better than you what kind of advertising you want to be buying, you really have to believe that Facebook has your interests at heart. And in some cases it’s not that Facebook doesn’t want to explain their reasoning—it’s that they can’t explain it, because the machine-learning models they’re using aren’t explainable. So it’s up to Facebook to convince advertisers that they’re not taking advantage of them. That may be difficult to prove when everything is so opaque.

Thinking more broadly about this new kind of advertising, what do you think is most distinctive about it? How does it differ from what came before?

One difference that springs to mind is the sheer individualization of it. There are some auctions where you can even bid for an individual human impression. For example, there’s a startup that will let you target a particular person with an ad campaign.

How does that work?

Maybe you want your partner to stop smoking. This startup will generate a special link for you that looks like it’s an e-commerce site. You send it to your partner and when they click it, they get a cookie secretly loaded into their browser. This cookie enables the company to track your partner across the web. You write up an anti-smoking ad, and the company will ensure that your partner sees that ad everywhere. Now your partner’s entire internet experience is permeated with pressures to stop smoking.

You can design a similar campaign for a coworker you don't like. You can show them ads for job-hunting websites, to encourage them to get another job.

That's pretty funny. I knew about the extent to which Facebook and Google track you around the web, but I hadn’t realized that smaller companies could do it as well.

Most people don't realize how many companies have access to the cookies that are in your browser, and how much information those companies can learn about you from those cookies.

Let's say you go to the New York Times website. Now, at various points in your browsing history, all sorts of cookies have attached to your browser. When you click through to the New York Times, as the page is loading, there is an instantaneous algorithmic auction for the right to show you an ad impression. That auction takes about a tenth of a second. In that tenth of a second, the New York Times passes on all of your cookies to an online auctioneer called a supply-side platform. These auctioneers then send out a query to a whole bunch of bidding companies that exist to help advertisers run online ad campaigns. They'll say, essentially, "At 4:01 pm, from the following IP address in Cambridge, Massachusetts, somebody we think is female, twenty-five to thirty-five years old, is looking at an article about Trump."

Presumably the time and the IP address are logged by the New York Times, but how do they know I’m female and twenty-five to thirty-five years old?

They’re guessing that based on your cookies, which are just strings of text that contain information about your online activity. But the New York Times may not be able to interpret your cookies. So they’ll pass the cookies on to the auctioneer, who passes them on to the bidders, and the bidders will interpret them.

Now maybe the bidders can understand your cookies better than the New York Times. Maybe they can make a pretty good guess that you’ve been looking for a ski holiday or that you've been looking for a divorce lawyer. And from that they'll compute how much they think your eyeballs are worth to them. They'll send their bid back to the auctioneer, who determines the winner and then sends the winning impression back to the New York Times. That's how you get an ad for a ski holiday or a divorce lawyer one tenth of a second later.

And so every time I go to the New York Times it is taking all this information and sending it to third parties who send it along to fourth parties?

Yes. Whenever you're accessing one of the many websites that sells advertising in this way, all of your cookies are being made public in this fashion. I think people don't realize that this is part of their everyday internet experience.

Is there any government oversight of this process? Who's even supposed to be regulating that?

No, there's essentially no oversight. It's the Wild West out there.

This piece appears in Logic's sixth issue, "Play." To order the issue, head on over to our store. To receive future issues, subscribe .

< Back to the Table of Contents

Roleplay, Interplay, Powerplay

Playbor is a neologism that gets us to look at how the boundaries between work and leisure, production and consumption, increasingly overlap. Emerging as a term in media studies about a decade ago, playbor sought to describe phenomena around participatory and interactive media like the social web, riding the crest of a wave whose undertow arrived in the mainstream techlash of the last few years. But while the focus in the mainstream has mostly been on the velocity and veracity of information on social platforms, many of the underlying transformations in interaction and incentivization go beyond that.

The ways value is perceived, created, and circulated is changing. What some have called “attention economies” or “cognitive capitalism” have made the collection, analysis, and operationalization of information more important to the production of value. Playbor sits inside that broader discussion, as a mechanism to incentivize individuals to participate more fully in their interactions. From points for meditation to badges for new skills, gamified reward structures help keep individuals engaged. These reward structures can take many forms, from a benign paternalism to guide better decision-making to collaboratively set goals to all-out extractive dark patterns.

In this series of speculative ads, we look to the ambiguity of these interactive incentives and their relationships to other changes in the world. Often, change is envisioned as technology-driven, as though a neat separation between it and everything else were possible. But there are only messy entanglements of technology, social relationships, economics, politics, and environmental factors. For instance, as ubiquitous computing and the Internet of things continue to be embedded in our environments, the way we relate to the proliferation of sensors that collect data and actuators that manifest changes is shifting the meaning and experience of being connected. Already, at MIT, researchers are working on sleep interfaces to unlock the possibilities of previously unconnected time, stretching this notion of ubiquity from a spatial to a temporal dimension. How might business models shape the deployment of these technologies, and what are the effects of introducing social elements into a previously private sphere?

In other domains, biotechnologies like the gene-editing tool CRISPR-Cas9 enable precision snipping and insertion of gene sequences, akin to the cut and paste function of a word processor, while DNA-testing startups are collecting and monetizing the genomes of individuals. Could this intersect with the world of media convergence, where interactions and character-forms live across platforms, bringing media into life itself? Or take the models for innovative governance like seasteading proposals for floating city-states, which compete for citizens in ways akin to how companies do for customers. Would the fear of bankruptcy incentivize governance to advertise in new ways, and would we be willing to live with the precarity of losing a round?

Lastly for our series, we look to the impacts of climate change, an entangled issue of overlapping economic, technological, social, and other patterns. As the sustainability of current economic arrangements is put under pressure from irregular and unevenly distributed climate effects, alternatives like the circular economy are reimagining the economy as a system of inputs and outputs in which all waste can be reintegrated back into the loop of production. This model would require large behavioral changes at both individual and collective levels, including a rewriting of the boundaries between work and leisure, or public and private, as responsibility for objects’ lifecycles is extended across multiple actors. But what kinds of structures could incentivize behavioral shifts like the mass repair of goods? Would that experience be paternalistic, tyrannical, optional, or something oblique to our current imagination? Would we need to rethink our notion of work?

The goal of these questions and speculations is to not fall into a dystopic or utopic register, but to sit in an emotionally and intellectually uncertain place before anything—a starting point from which the long-term implications of these decisions can be raised, and the design of these arrangements debated.

— Jemuel Datiles, Laura Dempsey, Jamie L. Ferguson, Valdis Silins

From the Silicon Savannah to Sheba Valley

by Scott Malcomson

Kenyan and Ethiopian entrepreneurs are building homegrown tech scenes—with and without the help of their governments.

iceaddis, a tech incubator and coworking space in Addis Adaba, Ethiopia.
Built out of six shipping containers, the structure was originally designed as an art gallery.
Photograph by Bill Zimmerman.

The Kenyan tech scene was born in pain.

On December 30, 2007, Ory Okolloh was blogging as quickly as she could. A Nairobi-based lawyer and investment adviser, Okolloh was writing about the recent presidential election—which the incumbent, Mwai Kibaki, had just won amid allegations of fraud. The election had been violent. The post-election was going to be worse.

“I can barely breathe,” Okolloh wrote, “I’m so upset at the circumvention of democracy.” A few days later, as clashes continued between the ethnic group aligned with Kibaki and those that opposed him, Okolloh blogged about the deteriorating situation in Nairobi. “I hang out with people on both sides yesterday evening at different times and you cannot have a civil conversation if you’re not on the same side,” she wrote. “It is really very scary... I felt like I was on the set of some bad movie about ethnic cleansing.”

Soon after, Okolloh decided to leave the country and wait out the violence in Johannesburg. The number of murders would rise above a thousand: hacked, shot, burned alive. It was a lasting shock to a generation used to being shocked. Okolloh agonized over leaving Kenya, but felt she had to put her child’s safety first. Still, she wanted to find a way to help. From Johannesburg, she wrote:

Google Earth supposedly shows in great detail where the damage is being done on the ground. It occurs to me that it will be useful to keep a record of this, if one is thinking long-term. For the reconciliation process to occur at the local level the truth of what happened will first have to come out. Guys looking to do something—any techies out there willing to do a mashup of where the violence and destruction is occurring using Google Maps?

Over the weekend of January 5-6, 2008, two software developers teamed up to answer Okolloh’s call. One, Erik Hersman, had been raised in Kenya but was then based in Florida; the other was a Kenyan based in Alabama named David Kobia. Together they built a website called Ushahidi, which means “testimony” in Swahili. Gathering data from Kenyans and NGO workers and anyone else who seemed credible, Hersman and Kobia developed a crowdsourced map of the post-election violence. On January 9, Okolloh introduced it to the world:

Last week, in between nightmares about where my country was going, I was dreaming of a Google Mashup to document incidents of violence, looting etc. that have occurred during the post-election crisis. Today, Ushahidi is born.

Ushahidi went on to become a great success story for Kenyan tech and an inspiration to entrepreneurs across the continent. Its tools for incident reporting have been deployed around the world, often for the purposes of election monitoring, crisis response, and human rights reporting.

Soon after launching the site, the Ushahidi crew started a tech hub in Nairobi called iHub. Within a few years, every major African city seemed to have a tech hub of its own, if not several. These ventures in turn built on the success of M-Pesa, a mobile payments system launched in 2007 by the Kenyan telecom Safaricom. M-Pesa revolutionized African banking and, like Ushahidi, quickly went global.

The Kenyan tech scene, soon dubbed the “Silicon Savannah,” had arrived.

Leapfrogging Politics

The story of Ushahidi illustrates an important point about tech in Kenya, and in much of Africa. Tech is a metaphor as well as a business. It’s a metaphor for a future that is not only prosperous, but also free from politics. African tech promoters often talk about “leapfrogging” to accelerate development: for example, by skipping fixed phone lines and going straight to mobile. The biggest leapfrog of all would be to skip over corrupt states and parasitical elites to a post-political internet where Africa’s large and underemployed youth population might have a shot at escaping poverty.  

But politics has proved hard to avoid. Even as a desire to transcend politics fuels the fascination with tech, politics finds ways to reassert itself. “Technology, especially digital technology, and politics are inseparable,” Nanjala Nyabola tells me. A leading Kenyan public intellectual and author of the Digital Democracy, Analogue Politics: How the Internet Era Is Transforming Kenya, Nyabola says that tech is often seen as something that “can cure the problems of Kenyan politics.” It’s a promise that tech can’t possibly keep, however: “Unless there is a political change, tech won’t fix it. You’ll just end up chasing your tail.”

This dynamic is far older than the Silicon Savannah. Indeed, Kenyan tech has long been shaped by its complex relationship with Kenyan politics.

In early 1994, three young Kenyans—two at MIT, one at Harvard—started Africa Online, which would become the leading internet service provider (ISP) on the continent. Initially, the Kenyan government opposed the internet altogether. The state-owned telecom monopoly took out a full-page advertisement in 1995 warning entrepreneurs that offering internet access amounted to resale of services and was therefore illegal. It targeted the internet partly to protect its turf, partly to control political speech in an unstable country, and partly because it could hardly keep up with the demand for fixed voice lines, let alone internet service.

Yet the Kenyan state’s hostility to the internet didn’t kill Kenyan tech. In fact, it may have served as a catalyst. As the Kenyan consultant Muriuki Mureithi wrote in 2016, Kenya’s digital success was shaped by “government-imposed barriers that spawned innovations.”

For example, in 2000 several Kenyan ISPs formed an internet exchange point (IXP) in order to connect their networks. The state telecom considered this move illegal. A week later, the state regulatory agency sent officers to literally unplug the IXP. Yet over the following year, the ISPs built relationships with the regulators. The state telecom was struggling to maintain its fixed lines: if it couldn’t provide adequate service, the ISPs argued, then it shouldn’t have the power to prevent other companies from offering alternatives.

This point of view started to make sense to the regulators, who began to explore undermining the state telecom’s monopoly status. By 2002, the ISPs had won. They got their IXP licensed, just in time for the arrival of General Packet Radio Service (GPRS) technology, the first system that enabled mobile internet access. Because access to mobile internet ran through the ISPs, they gained serious leverage over the state telecom. The internet came to Kenya through cell phones: today, Kenyans get online mostly through mobile devices.

Kenya’s leapfrog to mobile internet was driven not just by technology, but politics. It wouldn’t have happened if Kenyan ISPs hadn’t skillfully exploited a power struggle within the state brought on by the hopelessness of existing telecom services.

Today, the Kenyan state has officially embraced its tech sector. The Silicon Savannah is good for the government brand: it makes the state seem youthful and forward-looking. Even Ushahidi and iHub, born in revulsion at election-related violence, now receive government funding. The government also fuels the hope that tech will somehow provide, through the magic of internet entrepreneurship, some significant portion of the jobs that Kenyan young people need.

Uber for Ambulances

If an earlier generation of Kenyan technologists was forced to circumvent the state, the new generation is being asked to do the state’s job.

I saw this dynamic at Nairobi Innovation Week, an annual tech conference. It took place in the gleaming new Chandaria Centre for Performing Arts—financed by the industrialist Chandaria family, of Gujarati descent—in the equally gleaming, equally new University of Nairobi Towers. A crowd of young entrepreneurs made their pitches to a room of investors, as the government’s cabinet secretary for information and communications technologies, Joseph Mucheru, looked on.

One pitch was for a company that would help girls understand menstruation and have access to pads. (The cofounder talked about a 25-year-old woman “who didn’t know menstruation was normal. She thought it was just her family.”) Another was for an SMS system to circulate study aids by phone, given that schoolkids can remain illiterate even after several years of attending public school. The founder hoped that telecoms might subsidize the rates so the service cost could be held at $1 per month. Another startup would provide help with “soft skills” like mastering email in order to boost employment. Then there was an “Uber for ambulances” so people might avoid having to take taxis to the emergency room. The seed money being sought was usually in the $10,000 range.

I began to hope the minister might simply get up and apologize for a government that was looking to penniless young entrepreneurs to provide, some day, basic social services. It wasn’t clear that even these tiny projects would be getting any funding—or that the government would take anything more than a spectator’s interest.

Much of the funding for Kenyan tech comes from non-Kenyan sources. Kenyan tech draws heavily from philanthropists and so-called “impact investing” funds. Ushahidi and iHub, for instance, were financed mainly by American philanthropists. And the design for M-Pesa came from a project financed by the UK’s Department for International Development, as the mobile payments system was seen as a way to provide the advantages of banking to the unbanked and to enable microfinance.  

The founders who attract investment are often not African themselves. A 2017 study by Village Capital found that 72% of startup investment in 2015-16 in East Africa went to three companies: M-Kopa (a solar power company cofounded by the same Nick Hughes who pioneered M-Pesa), Off-Grid Electric (founded by three Westerners, two with Oxford MBAs, who had an interest in social entrepreneurship), and Angaza (a solar company based in San Francisco with an office in Nairobi). The report found that “investors are only investing in founders from the US or Europe or who attended a prestigious university.”  

Anywhere in the world, investors usually invest in founders who look like them, which tends to perpetuate inequalities. But it isn’t as though that 72% of startup investment is crowding out other capital. There are African venture capitalists, but African investors have more lucrative and safer options in a capital-poor region — investing in urban real estate is the main one, a sector with high profits and relatively weak foreign competition. For African tech to grow, African capital might need to rearrange its priorities a bit.  

The state can help, whether with tax incentives, educational initiatives, infrastructure investment, or simply by staying out of the way. Kenya, like Nigeria and other major African states, is now officially pro-tech and pro-internet, not least because tech provides hope for the young and the prospect of outsourcing some (already missing) public services to the private sector. But state commitments to tech are very thin, and states’ willingness to keep from interfering in internet speech is getting weaker.

Welcome to Sheba Valley

Driving between downtown Nairobi and the airport, you see occasional flashes of white light. You are being photographed. Terrorism is a very real danger in Kenya and the state and its partners—Safaricom again—have been happy to work with both China and the United States to use advanced technology to improve surveillance in the city. Counterterrorism, for now, is that rare area where the two tech superpowers can agree that spending large amounts of money in the poor world on up-to-date technology is a good thing. For once, worries about technology transfer don’t arise.

Upon arrival in Addis Ababa, the capital of Ethiopia, the pace slows a bit. A visa costs $50 in cash. Ethiopian birr are not convertible, and the country faces a grave shortage of hard currency. Once I had paid, the customs official looked awkwardly away. “I can give you a receipt,” she said, “but I don’t have a pen.”

Ethiopia and Kenya are the giants of East Africa and the Horn but in many ways are opposites: an authoritarian, vestigially Marxist state isolated from global markets versus a multiparty democracy with a relatively light-touch state and strong foreign investment. Yet both have robust tech scenes and ambitions. If tech is going to transform East Africa it will have to do so in both places, as dissimilar as they may be.

In some ways traveling from Kenya to Ethiopia is like going from the West to China circa 1995. With 100 million people, Ethiopia has more than twice the population of Kenya. The government recently embarked on reform after decades of stifling political speech, jailing opponents, and making its biggest decisions in secret. Blue Soviet-era Lada taxis still cruise the streets. With a development policy based on cheap labor and low-value-added manufacturing for export, the economy, fueled by government spending based on debt, has been among the fastest-growing emerging markets, if from a very low starting point. (Kenya’s GDP per capita is about twice that of Ethiopia.) Addis’s tin-roofed center is ringed by acres of new, quickly built apartment blocks.

Addis is bustling but it’s a hollow, rattling bustle. Many of Ethiopia’s universities barely function. The sole, state-run telecom struggles to address its backlog of phone-line requests. The internet cable is poorly maintained, and only businesses or the wealthy can afford to bring a line in and pay the high rates. Internet access for everyone else is through cell phones, but that too is iffy. When the government worried about political unrest in 2016-17, it cut off mobile access to the internet—and even, for a while, the fixed lines. When it worried about kids using the internet to cheat on exams, it cut it off for a week. When I was there, the prime minister had resigned so another state of emergency was declared and the internet got cut off.

This can make tech entrepreneurship difficult. Still, a tech startup scene has taken root in Addis, known as “Sheba Valley.” An Ethiopian expat coined the phrase, as a reference to the Queen of Sheba mentioned in ancient sources from the Torah to the Koran. The Ethiopian royal family claims descent from her, and her name functions as a kind of mega-brand: for example, Ethiopian Airlines calls its frequent-flyer program ShebaMiles.

Keeping the Power On

To reach the offices of Apposit, one of Sheba Valley’s leading startups, I made my way along Addis’s main thoroughfares to a cafe which was said to be next to the building that housed the company’s offices. The cafe reference was important because, to the limited degree that Addis has street numbers at all, no one seems to know them. After dozens of conversations and an exploration of two other buildings, I found the air-conditioned, buzzing offices of Apposit.

“We started just less than ten years ago,” Eric Chijioke, Apposit’s head of technology services, told me in his glass-walled office. “The three founding partners, myself, Adam [Abate] and Simon [Solomon], we had all worked in Ethiopia on a project the Kennedy School was running, building out the government’s financial systems.” Chijioke and Abate had gone to school together at Brown; Chijioke got a bachelor’s in mechanical and electrical engineering, while Abate’s degree was in economics and development studies. Harvard’s Kennedy School was executing the project for Ethiopia’s government on behalf of Western government funders.

More than half of the enterprise-level work in Ethiopia, according to Chijioke and three other Ethiopian tech people I interviewed, is governmental. The government finds it hard to run its own IT systems, so it farms the work out to contractors. But there are neither enough vendors nor enough work to sustain a competitive market, so the government in effect sets the prices. One of the many challenges of building tech for the government, says Chijioke, is the extreme variability of state infrastructure:

The systems that we built, and that still run, they needed to take account of the fact that it’s a distributed platform that’s supposed to run right down to the local government area level. But at the local government area, the actual functioning of the infrastructure is at a highly variable level, from nothing—you know, paper and pen—to computers that might run a few times a day to a few times a week, to some offices that might be highly automated and have satellite connectivity. You have to build for this: everything from zero to high-spec, everywhere in between.

Apposit’s leading project isn’t government-related, however. It’s in mobile finance. Apposit’s main client is Pagatech, a company that aims to build an M-Pesa-style mobile payments system for Nigeria. Pagatech is Chijioke’s responsibility. He got involved with the company early on: “I knew the founder — a gentleman named Tayo Oviosu. He’s an impressive guy — he went to business school with my younger brother, at Stanford, and he was thinking of starting up the business and he needed some technical advice.”

Apposit started out serving Pagatech when the company was still small. They did such a good job that Pagatech was willing to grow its developer team in Ethiopia rather than start a new one in Nigeria. “All of the developers and database engineers are based here,” Chijioke said. “On that particular team we have close to 30 people, and this is high-skilled jobs. Everyone on the team is Ethiopian except myself and one junior architectural engineer. The biggest problem is sometimes, for political reasons, the internet might be disconnected.”

Feleg Tsegaye, who runs Deliver Addis, Ethiopia’s largest e-commerce startup, also works at the mercy of an insecure, sclerotic, and capricious state. When the first internet shutdown came, Deliver Addis had to reconfigure its entire business to work offline, via text messaging. During another emergency, it had to configure its own email service. “Most people here don’t use the internet on a regular basis, besides Facebook and social media,” Tsegaye said. “There is not an impression that actual commerce is done via the internet, so the government doesn’t expect blocking it to have a great impact on businesses.”

To press their case with the government, Ethiopian tech companies have formed lobby groups—one for hardware, another for software—and startups have organized themselves around a handful of small institutions, all of which receive some funding from governments abroad, including RENEW, an American impact investing firm that backs Deliver Addis. The last time the government shut down the internet, beginning in October 2016, some 200 tech businesspeople met with the communications ministry to argue that technology, and the internet in particular, might actually have something to offer for the Ethiopian economy.

It promises to be a long battle. For now the government has placed its bets on manufacturing parks, complete with tax breaks and special immigration offices. Foreign companies, mainly Asian-owned, take advantage of low wages and the tariff-free access that manufacturers from Ethiopia, as a less-developed country, have to Western markets. But the inputs, such as those needed for making textiles, are often not from Ethiopia, and neither is most of the intellectual, manufacturing, or financial capital. Not even all of the labor is Ethiopian; managers and supervisors are usually Asian.  

Still, even though the Ethiopian government has prioritized manufacturing, it hasn’t entirely neglected tech. Around 2002, the government announced it would be building an industrial park for tech companies. Sixteen years later, it is just opening—and there hasn’t been much take-up. Kenya built something similar, with roughly similar results.

The real flagship for Ethiopian tech startups is iceaddis. Like Nairobi’s iHub but about one-twentieth the size, it has an open workspace with young people working on laptops, whiteboards, a tiny kitchen, and a purposeful hum. When I was there a group of Seattle high-schoolers were visiting. I met with iceaddis’s energetic head, Markos Lemma, born and raised in Addis, who had learned his English, he said, “from Hollywood movies.”

Lemma had just come from a long meeting with a government minister. “My argument is always that you can’t really have sustainable development without encouraging innovative and high-risk businesses, because those are how you compete in the future,” he told me. “How much capacity you have for producing technology is the best way to measure countries’ potential to grow. When I talk to ministers now they also understand there is a need for entrepreneurship.” And yet: “They don’t see the internet as the main accelerator of growth; it’s more like a threat, because it connects people.”

Running With It

All of Africa’s governments are facing a demographic explosion that they don’t know how to handle. “The internet” is a way to offer a bright future that would otherwise be hard to promise.

At the same time, states find censorship and surveillance hard to forego. Ethiopia is a good example. Its new government under Abiy Ahmed has encouraged the tech sector but, faced in August 2018 with unrest in the east, resorted to blocking the internet. Such a move inflicts a high economic cost: the Brookings Institution estimates that internet shutdowns in Africa cost $7.4 million per day.

The bright side is that today’s tech entrepreneurs know that they have to engage in politics in order to not be destroyed by it. African tech entrepreneurs are tough. As Nanjala Nyabola says, “We’ve managed to build exciting lives despite the challenges, and when you look at the tech space it is really evidence of a society that refuses to give up on itself. Give us a little space and we will run with it. Because we are so used to having no space at all.”

Scott Malcomson is director of special projects at Strategic Insight Group and the author, most recently, of Splinternet: How Geopolitics and Commerce Are Fragmenting the World Wide Web.

This piece appears in Logic's sixth issue, "Play." To order the issue, head on over to our store. To receive future issues, subscribe .

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Mainframe, Interrupted

Joan Greenbaum on the Early Days of Tech Worker Organizing

Joan Greenbuam at the NYSUT Health and Safety Conference in 2013.

In 1969, a collective called Computer People for Peace (CPP) petitioned the Association for Computing Machinery (ACM) to adopt the following proposals as part of its national policy:

We oppose the war in Vietnam, U.S. military presence throughout the world, and economic and political subversion of other nations. We oppose discrimination as practiced in the computer field. We oppose the establishment of mass data banks which pose a threat to our privacy.

Everything old is new again. Joan Greenbaum was a member of the CPP steering committee and rotating co-editor of its newsletter, Interrupt.

Joan has worked with, and written about, technology since getting hooked on programming in the early mainframe computer days with IBM. She is the author of Windows on the Workplace, Design at Work, and In the Name of Efficiency, and is Professor Emerita at City University of New York (CUNY), where she is on the faculty of Environmental Psychology.

In the conversation below, Joan recounts tactics, projects, and relationships built over fifty years of organizing. For those of us fumbling forward on what feel like new paths in the tech industry, her recollections furnish new (old?) possibilities and serve as heartening signs that our efforts have a history—and a long future.

This interview was conducted by Jen Kagan, who writes words for humans and computers. She is currently a tech fellow at

How did you first get involved with Computer People for Peace (CPP)?

In the 1960s, I was working at IBM, which was a marvelous job for me because I was a single mother with a kid. Programming was the only thing that paid a woman a living wage. And they trained me, so that was wonderful.

Around 1968, I joined CPP. We had a steering committee of six to eight people, which I served on. We were working for different companies, mostly doing programming. It was mainframe-based. We had a lot of demonstrations in New York because it was the 1960s. It was the war that started us out—that’s why we put peace in our name.

I remember you saying something at one point about a commune. Were you all living together?

It was only a small part of CPP, but yes. In 1971, seven of us who met through the collective started a commune in Brooklyn. Our commune was in an amazing old brownstone with original oak panelling and a big kitchen on the lower level.
We reasoned that it would only take three people working at any one time to support the house and buy all the food and everything, and then the others could be doing movement work—anti-war work or what I got into, which was trying to organize a computer workers’ union.

You tried to organize a computer workers’ union at IBM?

No, this was during the year I took off. We each took six months to a year off to do movement work.

CPP had the idea that if we could organize mainframe programmers and mainframe operators, then we could shut down everything. I worked on implementing that vision, but it was very difficult. The only inroads I remember making were at NYU and a city agency. It was difficult because the workers were well-paid and thought of themselves as professionals.

One of the things that the mainframe era did was to enable women and working-class people to walk into a professional job and earn a decent living. It just required a college education. My division of IBM had a lot of working-class young men who got draft deferments for working there. It was a leg on the rung of the middle class.

Were these programmers receptive to the idea of unionizing?

Programmers were not really interested, but the operators were. Operators were the guys—and 99.9% of them were guys—who worked in the machine room, the mainframe room. They could shut anything down. And being an operator didn’t require a college education. There were a lot of African-Americans who hadn’t been to college and whose consciousness had been raised in the 1960s and 1970s.

But we had this idealistic vision of programmers and operators, together. Today it’d be like a union of… I don’t know what the job titles are now.

Software engineers?

I’m kind of confused by everyone being called an engineer now. In my day, an engineer was somebody who had an engineering degree, like a civil or mechanical engineer. But programmers or systems analysts weren’t that. Do software engineers have engineering degrees?

They might have computer science degrees. My sense is that “engineer” is an umbrella word for people who may be doing a bunch of things: developing front-end applications, programming how interfaces work and connect to a database, people working on servers and maintaining infrastructure…

Yeah, but there are a lot of class divisions within that work, and those are really important for organizing. I’ve been trying to follow the changes and crunch the numbers that the Bureau of Labor Statistics puts out to understand what’s increasing and what’s decreasing. What I’m looking for is the numbers of people in the field—and what is the field?

In 1973, when I started teaching, young people were told to go study data processing. “That’s the wave of the future!” And, of course, it wasn’t. It never was. For a while, you could get jobs in it just walking in the door if you were white. But there were never that many jobs.

Tell me more about your work with CPP.

I edited and wrote for the CPP newsletter, Interrupt. “Interrupt” was a signal. You could program an interrupt to the mainframe. We meant it in a political way.


A glimpse of Interrupt, as digitized by Eli Naeher and Jen Kagan.
Several issues of Interrupt are available at Naeher's website.

The CPP steering committee had a lot of interesting tactics. We would meet regularly and come up with ideas like going to an Association for Computing Machinery (ACM) convention to distribute antiwar literature.

The people at ACM were just dumbfounded by us. But there were others who came out of the woodwork and said, “I really think the war is a bad thing. What do you have?” And they’d get on our mailing list. Back then there was no email.

We had what we thought of as privileged jobs because we were making decent income and we had Xerox machines. That was the key to the movement: Xerox machines. In those days, most people had to crank out leaflets on mimeograph machines with this blue ink. It was a big drum and you had to roll it around. Xerox machines were much better. We would sneak in when no one was looking and make copies.

You had access to Xerox machines through the computing jobs you had?

Yeah, we thought that was the main criteria for a job. Earn a decent wage and have a Xerox machine.

We also raised bail for one of the Panther 21. His name was Clark Squire and he’s still in prison. Do you know about the Panther 21?


The Panther 21 was a group of Black Panthers arrested in New York in 1969. The trial went on for a long time and they were all acquitted. One of them was a programmer named Clark Squire.

One of our members said: “Look, Clark Squire is a programmer. If we raise bail, it will raise consciousness among programmers not just about the war but about what’s happening to black people in America today.” So we went to ACM one year and raised a lot of money. People were aware that something really bad was happening to black people in America. Did we raise consciousness among a lot of computer workers? No. But enough of them ponied up money.

We got the money together but the judge wouldn’t take it. They kept all the Panthers in jail. They got out in 1971. I’m not sure what we did with the money, except then I went to work for the Women’s Bail Fund, which was an organization that included some Panther women. So we applied some of that money to women who were in prison.

Clark Squire is now known as Sundiata Acoli. He’s still in prison, on a different charge. He’s eighty-one years old. I write to him sometimes. He remembers everything about those days, things that I forget.

I’m curious about what you said about raising money but not consciousness. Sometimes I wonder whether tech workers who are speaking out now see themselves as part of larger movements and whether they’ll stick around for longer-term organizing that’s not directly tech-related. Did you ever worry about that?

I believe everything starts with a single issue. You start with a single issue, and my issue was working conditions. You start with a single issue and people start to say, “Oh, it’s not me. It’s not my fault. I didn’t do that. It’s happening to other people.” And then it can go anyplace.

The people I worked with then and now came in at different points and on different issues, but could all see the larger picture.

So when you think about your work today, it’s not as if Interrupt stopped and now you’re doing other things.

No, it’s a total continuum.

When did Interrupt stop publishing?

1973, I think. By then the energy wasn’t all in one basket anymore. The Panther trial made me very aware. It was also partly because we each took turns leaving our jobs to do movement work, and coming back was never easy.

In my case, coming back was particularly hard. In 1970, protesters had occupied the  Courant Institute, the computer center at NYU where I had tried to organize a union, and threatened to destroy some very expensive equipment there. So I had gone back to look for work and a woman who was a headhunter—this was totally new in the industry, that there were headhunters and that it would be a woman—sent me out on one or two interviews. Then—this is a wacky story but it’s true—she said, “Meet me at the public library on 42nd Street and don’t look like you know me. I’ll be wearing a big hat.”

She was dressed amazingly. She saw me and said, “Walk this way.” She said, “The FBI is after you. I can’t send you on any other interviews.”

I was wondering because the two I’d gone on, I knew the people who were interviewing me. And they were chilly. They did not move or change expression.

She said, “You can’t get a job. You’ve got to change your name.”

It was scary. I straightened my hair. I changed my name. I wore contact lenses.

The job I ended up getting in 1973 was at LaGuardia Community College, which was just starting. They were mainly hiring political activists. It was an absolutely wonderful environment for cooperative learning and working. The two guys who hired me, one had been associated with the Panthers and knew my work with Clark Squire and the other had been my manager at IBM. He had later left to start a small consulting firm—we would now call it a “startup”—and hired me away from IBM. Then I tried to organize a union there and he fired me!

But anyway, I was hired to teach. I was very lucky. LaGuardia Community College was a tribe that I loved.

In one of the issues of Interrupt, there were transcripts of “security hearings” in which workers who were being interviewed for government security clearances were asked about their associations with CPP. That must’ve scared people in the collective.

I was freaked.

We always knew that there was an informer in the group. All of our meetings were announced and anyone could come. There was one rather heavyset man who never said anything and turned up most of the time.

When I got married, he was the first one to come to my wedding party at the commune. Then, when I put in a Freedom of Information Act request several years later, the files showed our menu for the wedding, but almost everything else was redacted!

COINTELPRO was very active then. It could have been our work with the Panthers. It could have been my work with the union. I don’t know, but it was scary.

And you continued doing technical work?

Yeah. In those days it was called the data processing department. I taught programming and systems analysis and design for thirty-five years. That’s what I really liked: looking at the big picture. That’s what I got into at IBM and the skills were useful for CPP.

How do you connect the dots? How do you find the information? It was exciting. I think it was the beginning of my love of research and going on to get a PhD.

Is there anything else I didn’t ask that you wanted to talk about?

We didn’t have a model, we didn’t know what we were doing, but we became a collective that, well, we had a lot of arguments—if you look at any organization, you’ll find arguments—but we’d reach a consensus on the issues that we worked on in Interrupt.

I think it takes a physical presence. I was just on a Skype call with collaborators in Belgium for a participatory design conference. You can do certain things that way, of course. But I think you need the tribe.

I’ve been organizing in different groups for fifty or sixty years. Whether it was CPP or the CUNY union, it’s been a lot of work. But you have an evolving belief system together. And some naivete! I mean, I thought in 1971, “Organizing computer workers, oh yeah, this needs to be done! Operators and programmers together, yeah!” I had no idea what the structure of unions was. I had no idea National Labor Relations Board classifications can keep workers at the same workplace from forming a union together.

If you slice and dice workers, you don’t have a union. You have mashed potatoes. Some battles we fought. Some we lost.

This piece appears in Logic's sixth issue, "Play." To order the issue, head on over to our store. To receive future issues, subscribe .

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The Antisocial Network

by Liz Pelly

Facebook claims to bring people closer together. In fact, it’s helping derail and destroy some of the few remaining places that actually do.

The Silent Barn, a now-closed DIY space in Brooklyn, as seen in Google Maps.

The term “DIY” is contested within music communities. But “DIY space” generally refers to a self-organized venue run by artists, often on a formal or informal collective basis, to house non-commercial music, art, and community organizing projects.

These spaces typically aspire towards ideals of accessibility and inclusivity, and are open to all ages. They have low ticket prices, and give most of the money made at the door to the artists. They are places where new bands can play their first shows, and where people can learn how to book and run events collaboratively. Above all, they foster participation. In an increasingly isolated culture, music remains a medium that can still get people into a room together. DIY venues offer real social spaces in an era when the concept of being “social” has been hollowed out by Silicon Valley.

In 2014, I moved into the Silent Barn, a three-story DIY space in Bushwick, Brooklyn. There were art galleries, a recording studio, a barber shop, murals on every surface, and shows every night. On one of my first nights living there, I came home to a kitchen filled with dozens of collective members, sitting on chairs and the floor, holding a meeting. It reminded me of an Occupy general assembly, but with the purpose of running an all-ages music and art venue. For four years, I stayed involved as a resident, collective member, and co-facilitator of programming.

These days, however, DIY spaces like the Silent Barn are under threat. The Silent Barn shut its doors in May 2018, about one year after the shuttering of another local, long-running DIY venue, Shea Stadium. Beloved Brooklyn spaces like Death by Audio and Palisades have also shuttered in recent years.

The closing of DIY spaces is nothing new. Their reliance on volunteer labor makes them vulnerable to collective burnout, while their shoestring finances make them vulnerable to bankruptcy. Moreover, one of their defining characteristics is often their semi-legal status, which exposes them to pressure from the authorities. For these reasons, the announcement of another closure never comes as too much of a surprise. Still, it seems that DIY venues in big cities face more challenges than in previous generations: namely the rising price of urban real estate, and the complex relationship that exists between art spaces and gentrification.

But there’s another factor fueling the crisis of DIY: Facebook. To be involved in a local music community today means maintaining an inextricable reliance on Facebook events, and Facebook-owned Instagram, for promotion. Further, some DIY spaces have become dependent on Facebook groups for everything from connecting with the public to hosting internal organizing conversations. Across the music world, digital platforms are reshaping the ways that community forms around music—and, in the case of Facebook, exacerbating the significant obstacles that DIY spaces already face. A platform that claims to bring people closer together is helping derail and destroy some of the few remaining places that actually do.

Communications Theater

The original Silent Barn organizers were wary of underground arts organizing leaning too hard on “gigantic, panoptic” digital platforms, as one of the Barn’s cofounders G. Lucas Crane puts it. But eventually they came to rely on digital tools. As a non-funded arts organization perennially strapped for time and money, Crane explains, digital tools like Facebook offered the perception of convenience, but ultimately proved to be just that: a perception. Starting to use a Facebook group for internal organizing “ate away at the togetherness,” Crane says. “It just kind of makes you lazy. You get subsumed in the thing that Facebook wants you to do, which is to argue a lot with no actual outcome.”

“You think you’re getting something done. You think you’re communicating,” Crane says. “But you’re actually just performing communication. It’s communications theater. It doesn’t actually provide consensus.” Further, he noticed the nature of conversations on Facebook seeping their way into in-person meetings, “rotting away the ancient strategy” of getting people into a room to work things out because everyone had preconceived notions of one another from social media.

In Arcata, California, an all-ages, collective-run DIY venue called Outer Space balances similar concerns about online versus in-person decision making. They rely on a Google Group for communication, but also hold a weekly, recurring meeting. “Sometimes we have long, hard conversations where we don't always agree about how to move forward,” says Alex Norquidst, a member of the core collective that works with a larger volunteer base. “These kinds of conversations are really hard to have via text or email threads because people’s tone, body language, and the ability to take time out and check in with everyone goes away.”

DIY Space for London (DSFL), a venue that opened in 2015, does not use Facebook for internal discussions. “People often need to take a break from social media, or aren’t on it altogether, so if we were to use Facebook to organize, we’d be excluding a lot of people,” explains collective member Amy. Another member, Ben, adds that many members of the space do not use Facebook or Google “due to their power/practices.” Instead, their primary all-collective organizing tool is Loomio, a free app specifically designed for collaboration, which they supplement with a WhatsApp group for emergency communications. DSFL members note Loomio’s usefulness for fair discussions, time polls, and decision-making. Its notifications system also seems to be built to prevent burnout—something Facebook seems to make worse.

On Facebook, there’s a feeling that the platform is actually creating more organizing labor rather than less. During my time at Silent Barn, being part of the booking team involved responding to daily emails and DMs regarding date requests, lineups, follow-ups, announcements, promotion, production needs, and liaising with staff. Other digital labor included making Facebook events, writing promo copy, sourcing artwork, adding listings to our site, and trying to spread the word online without getting algorithmically buried. As a Barn booker, I found promotion on Facebook, something that was supposed to make our jobs easier, actually just created more work—it made our jobs harder.

Digital Monocultures

The rampant reliance on Facebook also complicates the long-held anti-commercial politics of DIY, which exists in opposition to the mainstream music industry. DIY spaces are in theory built on an ethos of valuing art over profit—sliding scale, suggested donation, and “NOTAFLOF” (or “no-one-turned-away-for-lack-of-funds”) shows are common. The use of Facebook weaves corporate infrastructure into the fabric of ethos-driven spaces.

It is a given today that engaging with corporate digital structures is a necessary compromise required to connect to communities. Facebook is a particularly murky environment: it positions itself as a social network, but is actually an advertising platform. Thus the interactions of socially motivated DIY organizers on Facebook are shaped by its advertising mechanisms. Facebook will naturally promote whatever has been paid for, or whatever will generate the most clicks in the attention economy.

This means that the kinds of small shows being pushed by DIY promoters are likely to get algorithmically buried, especially if they don’t pay for sponsored posts. Meanwhile, DIY venues and independent bookers are expected to use the same tactics as more established commercial venues that partner with corporate ticketing platforms like Eventbrite and Ticketfly, which in turn have deals to integrate more seamlessly with Facebook.

It’s hard to publicize unpopular artists on platforms that prioritize what’s popular. Indeed, the reliance on Facebook means DIY culture is becoming more closely aligned with the platform’s digital monoculture. The logic of social media platforms, of instant gratification and optimized “content,” requires pages (and spaces) to absorb streamlined “brand identities”—a logic that cultivates a more passive, consumerist approach to music that is inimical to scrappy, under-resourced DIY spaces.

While different DIY spaces have different approaches to navigating Facebook, generally the lack of resources means that DIY venues have difficulty maintaining a constant social media presence due to a shortage of volunteers. This in turn makes Facebook less likely to surface their content—for instance, by promoting their events with automated notifications that say, “We found concerts and other music events happening near you.”

The first time I received such a notification, I couldn’t help but think that “music events” sounded like something an undercover cop might say. Relatedly, there is a history of undercover police using Facebook to snoop on DIY shows. In 2013, when Boston police officers busted up popular DIY show spaces, they bragged about the fake Facebook accounts they used to find addresses for gigs. Here is another ongoing complication of social media and DIY: the way it makes spaces vulnerable to surveillance from authorities that see these spaces as nuisances and shut them down.    

Social Webs

Digital tools haven’t always played such a destructive role for DIY. In fact, the early social web facilitated interactions that hugely benefited self-organized music culture. Think message boards, the sprawling landscape of independently run MP3 blogs, and even Tumblr communities where weird micro-genres and home-recorders could thrive. The MySpace era in particular is widely seen as a golden age for DIY: much has been written about how MySpace offered the ideal music site, perhaps for the simplicity of its interface or the highly customizable quality of its pages.

By contrast, the consolidated social web embodied by Facebook is damaging DIY by providing an illusion of convenience that reshapes communities in the image of Facebook’s preferred norms. Criticism of platforms is essential as they continue to take a stronger hold on the ways that we form community. There is still much to be thought through by DIY organizers when it comes to examining how platforms play into building DIY spaces.

We need to fight against the trappings of convenience, and make sure that it’s us using the digital tools and not the digital tools using us. Perhaps there is something to be gleaned from what DIY spaces are already learning about Facebook: as an advertising platform, it may have some utility, but as a tool for building community, it’s probably best to go somewhere else.

Liz Pelly writes about music, culture, streaming, and the internet. She is a contributing editor at The Baffler, where she writes a column about how the world of music is being reshaped by the platform economy.

This piece appears in Logic's sixth issue, "Play." To order the issue, head on over to our store. To receive future issues, subscribe.

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