Prompt: Alexander’s first call was to the Tech Workers Coalition (TWC). Much of the technology incorporated into the new streetlights was foreign to him, and he wanted to better understand how it might be used. He also reached out to activists from communities he knew were likely to be targeted by the surveillance—homeless advocates, immigration rights organizers, police abolitionists—and invited them to the next streetlights community forum. At that meeting, held a month later, Alexander and his fellow activists managed to pack the house.

Response: This was the beginning of a two-year grassroots campaign to rein in the Smart Streetlights Program. By connecting surveillance to a wider set of issues than policing alone, the organizers were able to create a coalition wide enough to win. A lynchpin of their success was not only building a traditional coalition of community organizations from around the city, but also bringing in new allies: workers from the companies and research institutions building these technologies. The methods might be a model for other struggles against surveillance and carceral technologies in cities around the country.


Prompt: The New Bacon The infomercial Alexander was shown at the first community forum boasted that the data produced by the Smart Streetlights were “the new bacon”—they went with anything and could serve almost any purpose that agencies with access to the data could imagine. The other one of us, Lilly Irani, an organizer with TWC, listened to the presentation at the second community forum and realized that surveillance was only one part of what the streetlights could be used for.

Response: Community members at the forum immediately raised concerns about the technology’s ability to further criminalize San Diego residents. Black and brown-led organizations worried about heightened racial profiling using video streams. Refugee advocates worried that the streetlights could intensify the criminalization of Muslims by using software to analyze behavior near mosques. Homeless rights groups predicted the city would use the streetlights to more quickly find encampments to sweep. Border activists worried the streetlights could help track and deport people by being integrated with systems such as those developed for the Department of Homeland Security by Palantir.


Prompt: A police officer at the forum assured the crowd that the cameras did not record private property, but a computer engineer from TWC was able to force the officer to clarify that the cameras did record private property, which was then scrubbed from the data by a software program. What the city called the “sensors” on the streetlights also included microphones that could record people’s voices without their knowledge. The officer said the microphones were currently disabled, but admitted that they might be used for gunshot detection in the future. When a community member asked how long the streetlights were going to collect information, a city staffer replied that it was “undetermined”; the officer tried to reassure the crowd that “the answer is probably never.” Activists recognized that what the city and law enforcement said it was doing (and planning to do) with the program was beside the point. San Diego has long been an innovator in police surveillance networks. The county’s Automated Regional Justice Information System, which shares surveillance data between more than sixty-five law enforcement agencies, has been in place since the 1980s. More recently, the county had provided facial recognition devices to law enforcement agencies across the southwestern border region until the state passed a moratorium on such devices and the Electronic Freedom Foundation sued to have the moratorium enforced. For years, the San Diego Police Department shared data from its automated license plate readers with Border Patrol to help the federal agency track, detain, and deport migrants, until the practice was exposed by journalists. When it came to the streetlights, the hard part was already done: more than three thousand units were installed across the city. Expanding what that hardware could help officials do would only be a few software updates away. As the officer admitted, the sensors weren’t even covered by civil codes the way similar technologies, such as automatic license plate readers, were.

Response: And it wasn’t only city and law enforcement agencies that might deploy the technology. All of the data generated by the streetlights would be made publicly available, albeit in an ostensibly anonymized form. A city staffer at the forum explained that this would allow “civic entrepreneurs” to use the data to build businesses to improve the city, including an app to help people find parking downtown. Irani knew this was code for gentrification—the city would give or even sell data harvested from the public, without its consent, to tech companies that would use the data to reshape the city in ways that favored wealthier white communities and pushed Black, brown, and poor people out of San Diego. Irani and Alexander later discovered through a public records request that the city had used Federal Community Development Block Grants, meant for projects that benefit low-income neighborhoods, to fund the streetlights.


Prompt: This range of concerns about how the technology might be used in the future became the basis for the grassroots campaign. Within a month, thirty community and activist groups had joined together in what became the Transparent and Responsible Use of Surveillance Technology San Diego (TRUST SD) Coalition. It grew quickly, in part, because people recognized that the Smart Streetlights surveillance infrastructure spanned the city and could bring anyone into the law enforcement dragnet. The campaign also relied on the working relationships that Alexander had built over years of organizing with different communities.

Response: Tech workers, too, were an essential part of the coalition. They joined because they did not want to build tools of state violence and oppression. In many public contests over technology, experts from industry and the state dominate conversations by wielding technical knowledge that communities cannot counter. In this coalition, however, the technical expertise of tech workers allowed organizers to counter official claims about what the Smart Streetlights technology could or couldn’t do, and helped them understand how the surveillance applications they feared could in fact be built on top of the existing network. The alliance with tech workers neutralized the city’s advantage.


Prompt: Organizing the Lab Rats The coalition decided to focus on three goals. Articulating these was crucial to keeping the various political and ideological factions within the coalition from splintering over other issues. First, it called for an immediate moratorium on streetlight acquisition, installation, and operation. This would end the immediate threats that the streetlights posed while organizers lobbied for more radical changes to public policy.

Response: Those changes to public policy were the coalition’s second goal. Organizers sought public participation in the creation of legally enforceable policies over all surveillance technologies used by the city, not just the streetlights. A wide range of technologies beyond the streetlights—known and unknown—made up the surveillance dragnet of San Diego. Worse, surveillance tech could come to the city through donations to the Police Officer Association or through free trials like those offered by facial recognition company Clearview AI. This meant that the City Council did not always have to approve the technologies and the public had no way to see what was in use, unless someone peppered city departments with scattershot public records requests. Council members had not even discussed the Smart Streetlights Program publicly before they signed off on it; that was two years before communities realized a mass surveillance technology was even on the table. Communities needed a legal infrastructure that would alert them to surveillance technologies before they were approved. Rather than playing whack-a-mole to stop individual technologies, the coalition sought transparency, oversight, and City Council authority over all city surveillance technology, existing and future.


Prompt: Finally, the coalition demanded public records showing how the streetlights had already been used and accessed. As organizers studied these records, they discovered that the city had considered monetizing the data and had even explored providing a livestream to the police. These discoveries informed the coalition’s activism and provided fodder for breaking news stories that added momentum to the campaign.

Response: Because the mayor had championed the program, organizers would need a veto-proof majority of council members to support the moratorium and the policy changes we were fighting for. So the campaign worked to build public pressure on the city council through press conferences, newspaper opinion pieces, public events, and direct lobbying. Organizers broadened their discussion of the issue beyond criminalization to larger concerns about the dangerous power of big tech to engage liberal and conservative elected officials in different ways. In one opinion piece, they argued that San Diego residents had been turned into “lab rats for innovation.” The Mayor’s Office and city officials tried to dismiss the campaign as a small handful of activists with hidden agendas. They also attempted to frame it as ignorant of the technical dimensions of the streetlight program. In November 2019, a tech worker who had experience working on artificial intelligence contracts read the contract the city had signed with GE, and discovered that the city had signed over to the company ownership of the data produced by the streetlights. The data were stored on GE’s servers, and the city merely accessed them through a subscription, which meant the city lacked final say over what the company could do with the data. An anonymous city staffer responded by calling the coalition’s findings “insane lies,” but ultimately the city could not undermine the credibility of tech workers who had built or worked closely on smart cities hardware, artificial intelligence models, and similar technologies.


Prompt: Over the following months, members of the coalition lobbied city council members and found them increasingly at odds with the mayor and the city attorney over the scope and legal framework of the Streetlights Program. In order to channel that frustration into a tactical win, organizers followed a two-pronged approach. First, they expanded their attempts to put public pressure on these elected officials. They held town halls, screenings of the film The Feeling of Being Watched—about government surveillance of Muslim communities in Chicago—and workshops at which we taught community members and activists about the technology and brought them into the organizing efforts. They also did direct outreach to community leaders and journalists.

Response: The second prong was to write a “surveillance technology transparency and oversight” ordinance. The coalition would hand the draft legislation over to a champion on the city council, who could then present it as a “common sense” solution they could claim as a legislative victory. Organizers adapted their ordinance from ones already in place in Oakland and Seattle. It required city departments to create use policies and impact reports to gain Council approval for any new technology with surveillance capabilities. It emphasized oversight over all such technologies, not just those used by the police. The LED streetlights, after all, had been acquired in the name of energy savings and innovation, obscuring the technology’s connections to law enforcement. The ordinance also created a Privacy Advisory Board to support the City Council with recommendations on specific technology acquisition proposals. Board seats were reserved for representatives from “equity-focused organizations” serving communities impacted by surveillance, as well as information technology and civil liberties experts; anyone with financial ties to companies selling surveillance technologies was disqualified.  Organizers wrote the ordinance to appeal to a wide range of constituencies. Fiscal conservatives liked it because they wanted to reduce government spending. (The streetlight program, budgeted at $30 million over a decade, was already seeing cost overruns.) Liberals who believed in deliberative process appreciated that the ordinance created an independent body to advise the city council and included civil rights oversight. More radical organizing communities recognized that they needed the ordinance in order to find out about new technologies if they were to have any chance of organizing against them.


Prompt: The coalition was lucky to find a champion on the Council who was willing to take the ordinance through committees and do the behind-the-scenes work to get it passed. The Councilmember, formerly a civil rights attorney at the ACLU, also had close relationships with people in the coalition. Meanwhile, organizers kept pressure on the city to shut down the streetlights and adopt the ordinance by organizing people to show up at council meetings and the mayor’s office, and led telephone and email campaigns ahead of crucial votes.

Response: The coalition also seized upon Covid-related budget cuts to defund the streetlights. Mid-pandemic, Irani assembled a dystopian hackathon with coalition-aligned students to prototype creepy examples of what the streetlight technology could already do. Irani thought the demos would help persuade the Council of potential harms, but the most important outcome turned out to be the discovery that the streetlights didn’t deliver the promised data for city planning. The coalition alerted an investigative journalist, who broke the story in April 2020. By May, the city was proposing Covid budget cuts. The mayor had put library hours on the chopping block but saved the streetlights. The coalition worked with the progressive Community Budget Alliance to mobilize residents to email and call council members and demand they defund the streetlights. San Diego Climate Action also joined the effort, since the lights, operated under the Sustainability Department budget, had redirected funds to a broken, greenwashing surveillance system. In the end, the Council refused to fund the system.  Tools for Struggle In May 2020, the mayor made a last ditch attempt to hand over control of the surveillance system to the police and fund it using an obscure budget pool that City Council didn’t control. The coalition was able to show through old legal memos that this funding strategy was likely illegal and held a press conference to make the point. The mayor fought organizers for months, but finally, in September, he surprised everyone by announcing that the Smart Streetlight sensors and networks would be turned off until an ordinance was created to oversee the surveillance technologies run by the city.  In November 2020, a year after the campaign began, the Council unanimously approved the oversight ordinance. The ordinance makes visible technologies that usually operate out of public view, mounted on light poles and cop cars, or running in the circuits and servers of hardware, software, and data brokerages. It slows down technology acquisition and gives communities time to learn and organize resistance. It puts community members with negative experiences of surveillance in a role where they can build knowledge about technologies and educate others. Though some argue that such ordinances create legitimacy for surveillance technologies, they also create a mechanism for people to organize refusal where there currently is none.


Prompt: But ordinances like these are not a panacea. They are tools for struggle and refusal, but do not guarantee resistance to surveillance. Without vigilant organizing, including alliances with technologists and elected officials, even community advisory boards may rubber stamp policies and legitimize surveillance technologies. This struggle also shows how cities do not control the technology of companies they contract with. As the coalition in San Diego worked to get the ordinance passed, it put the fear in city council members by explaining how the NYPD lost control of its data to Palantir. Then, the same thing happened to San Diego. With defunding, the city lost access to the streetlights’ surveillance feed. But the cameras continue to record. GE sold off the streetlight network to another company, which sold it to a Florida-based firm called Ubicquia. Ubicquia refuses to stop recording even though the city can no longer access the data. But even this did not stop the police from removing the camera and harddrive in one case to access and share the video.  Paradoxically, it was the process of organizing for the ordinance that strengthened the coalition’s political capacity to challenge emerging surveillance technologies. By political capacity, we mean relationships among community members who trust one another, can teach each other, and can work together; we mean the time that people can spend researching, calling into council, occupying the mayor’s office, strategizing, and running educational forums. More people means more time spent doing these things, and more relationships with people who will get involved in the movement.  In advocating for the ordinance, Irani and Alexander talked to a wide range of people, from anti-racism activists to former soldiers. Each person had different reasons to fear surveillance. People who showed up out of fear of big tech or privacy violations also learned about the criminalization of marginalized San Diegans. Anti-criminalization activists learned a lot about technology and its potential role in further entrenching the carceral state. Many of the people engaged by the coalition took their first steps from awareness to action. But the coalition’s work to resist and refuse mass surveillance doesn’t end with the ordinance. It begins in earnest once the ordinance is in place.

Response: When the Covid-19 pandemic hit, one of the first steps the strip club I worked at took was to have all dancers wear masks. The club also limited the number of patrons who could be in the club at any one time, following rapidly evolving CDC guidelines. But then, on March 16th, Los Angeles County went into lockdown. What we thought would be only a week, soon became months, then an indefinite question mark.  Stripping is a high risk occupation in the middle of an airborne viral pandemic, and it became clear we would be among the last industries to reopen. We weren’t considered essential workers. Many of us weren’t even properly registered as employees, which meant that we were ineligible for government aid. I was hesitant to apply for unemployment because I wasn’t sure if my club had declared me as an employee, and I was afraid of retaliation if I exposed their less-than-above-board financial situation. Erotic laborers were also initially explicitly banned from receiving Paycheck Protection Program loans. I realized I would have to figure out a survival strategy, part of which was moving my work online.


Prompt: Countless sex workers around the country were navigating similar crises. I’m the president of Strippers United, a coalition of strippers working to create safe and equitable workplaces for strippers across the United States and beyond. As states began shutting down strip clubs during the pandemic, our social media page was inundated with strippers who were suddenly out of work and terrified because they didn’t know what to do next. We began providing mutual aid to strippers facing evictions and imminent homelessness, and helping our community members address the numerous challenges of having to move online.

Response: One of the biggest challenges came from large social media platforms. As strippers and other sex workers became increasingly dependent on digital spaces to earn income during the pandemic, we were simultaneously in the midst of one of the largest ever digital crackdowns on sexual content. Beginning in 2018, following the passage of the Stop Enabling Sex Traffickers Act and the Allow States and Victims to Fight Online Sex Trafficking Act, better known as SESTA and FOSTA respectively, apps like Instagram, TikTok, and Twitch initiated major terms of service changes that prohibited even the mention of basic words to describe our labor.  SESTA/FOSTA was purportedly created to prevent human trafficking and curb illegal sex work online, but the legislation was written without consultation from legal sex workers, and has ended up threatening our work as well. Because of the penalties enacted by the laws, tech companies decided the best solution was to police themselves. Thoughtful moderation would have required paying a human labor force to personally screen every account flagged for sexual content to determine whether or not what has been posted is legal and consensual, but tech companies don’t care enough to pay for due diligence. Instead, they began enlisting blunt algorithms that could hardly tell the difference between a Georgia O’Keeffe painting and a human vulva.


Prompt: Not long after SESTA/FOSTA went into effect, numerous sex workers began reporting “technical issues” when we attempted to upload content that included words such as “sex,” “stripper,” or “pornstar”; the issues disappeared when we removed sex-related language. Even when we were careful, we noticed that more and more sex workers seemed to be getting deprioritized by social media algorithms—effectively censoring our content—or worse. Major Instagram influencers with hundreds of thousands of subscribers found their accounts taken down just because they had OnlyFans links in their bios.  Over the course of the pandemic, even legally recognized sex work was increasingly treated as illegal by social media platforms. (Currently, Twitter is the final stronghold when it comes to major social networking platforms that permit explicit content, and while it is popular with many sex workers, it isn’t right for everyone.) I received multiple warnings from Instagram throughout 2020 and into 2021, notifying me that my account was under investigation and might be taken down for “violations of terms of service,” due to the sexual nature of my content. The pictures on my timeline were no more graphic than pictures posted by celebrities like Doja Cat or Miley Cyrus—but unlike them, I was considered disposable.

Response: The problem was far bigger than the ability to post selfies. Sex workers are vulnerable small business owners, and many of us who were not already earning money on the internet were forced by the pandemic to move our work online. When sex workers were removed from social media platforms, they lost their audiences and vital sources of income. Apart from the major social media platforms, there are not many popular places to advertise as a small sex-work business. This is not because the labor these workers are performing is against the law: strippers, cammers, pornstars, and many other sex work professions are legally recognized.


Prompt: Things got worse in early 2021, a year after the pandemic began. In March, Mastercard announced it was going to enforce a radical new payments policy requiring even stricter oversight of adult content providers. One of the effects was that independent porn creators lost hundreds of hours of content overnight. A few months after the announcement, the site OnlyFans—whose explosive growth was built on the backs of adult creators—said it would ban sexually explicit content; it only backtracked after an online uproar from sex workers and media outlets, who lampooned the platform for its critical miscalculation of who was actually driving its success.

Response: As the prospect of being deplatformed at any given moment became more and more likely, many sex workers began to wonder whether we would even be allowed to exist on social media at all. For months, my coworker, Summer Miller, had been trying to sell me on an idea: to build an online platform for us, by us: one entirely owned by the people making the content. Initially, this had seemed to me like a pipe dream because of the high costs of developing a platform, the dangers of federal regulation, and a lack of technical expertise among us. But trying to face the twin crises of the pandemic and SESTA/FOSTA convinced me Summer was right. The only way to really achieve just working conditions was by making sure that content creators had a powerful say in shaping their labor conditions, rather than leaving everything to faceless big-tech teams who are unreachable and unaccountable. To save our industry, to create an equitable workplace, and to protect sex workers, we had to take the industry over from the ground up.


Prompt: Adult Only, Adult Always Summer and I began fundraising for our platform, which we called V Union, in late 2020. The following January, we received a message from Donia Love, the founder and CEO of PeepMe, another nascent platform for adult creators. The PeepMe team was a mix of people already involved in sex work and sex-work advocacy, along with allies in tech development and cyber security who were willing to put their careers on the line to support the enterprise. Their mission was everything we were aspiring to do: “adult only, adult always.” So V Union decided to partner with PeepMe.

Response: Our aims for the platform are ambitious. In addition to creating a worker-owned cooperative, in which workers have democratic power over the running of the platform and a share in profits, we also want to give individual workers ninety percent of the revenue they generate. Additionally, we intend to donate ten percent of our profits to sex-worker-led community organizations. One caveat we are applying to cooperative ownership is the site cannot be sold off or lose its identity as an adult content platform. We believe this is the only way to create a just alternative to the exploitative business practices of the online adult industry.


Prompt: Launching such a platform has had many challenges. Almost immediately, we were informed by our bank that PeepMe had lost its account because it was the bank’s policy not to serve “prurient” businesses. We have tried to partner with three different software development teams, but each of those collaborations has hit roadblocks due to SESTA/FOSTA and the threat of criminal liability for content hosted on the platform. One way to sidestep liability would be to make a decentralized and open source platform, but that would threaten our efforts to make PeepMe a worker-owned cooperative. Another option would be to use a prefab “white label” platform, but those can come with unknown security risks to sex workers and their financial data, and damaging the trust of sex workers would mean undermining the foundation of what we are hoping to achieve. There are also difficult questions about how to make PeepMe profitable and for whom: Do we sell the business to the community of users at some point, exiting the business for profit? Do we build a cooperative platform and then profit by selling or licensing its model to other cooperative platforms? How can we make the platform financially sustainable while lowering the barriers for sex workers to access sustainable, profitable work themselves? Stigma has also affected the ability for PeepMe to spread via word of mouth. During a small mock-fundraising session consisting of close friends and family, many people expressed enthusiasm for the platform and a willingness to donate, but were hesitant to help spread the word because of the stigma around the work. During a fundraising Zoom call, one prospective donor said, “I cannot shout out you guys on my feed. I just can’t because of the way the world works right now.” It’s one thing to personally believe sex workers deserve rights and their own platform, it’s another to relay that to coworkers without getting accused of sexual harassement and inappropriate conduct.

Response: One thing that hasn’t been hard is finding sex workers who want to join the platform. Using Strippers United’s large Instagram presence and its connections to other sex work advocacy groups across the world, we have had great success doing outreach to adult creators. In particular, we have heard from many people who no longer trust OnlyFans and who understand the importance of a platform built by and for sex workers.


Prompt: Frustratingly, though, we can’t yet serve all the sex workers we want. SESTA/FOSTA constrains us in similar ways to big tech corporations; unlike those companies, we have the appetite but not the capital to litigate our case. This means that, while we can legally host cam models, online strippers, porn stars, and other sex workers whose labor isn’t technically criminalized, we still can’t host full-service sex workers, who are ultimately the most at-risk members of our community. It is a heartbreaking compromise that I hope won’t last forever. For now, we’re aiming to protect who we can, and we hope to provide a sanctuary occupation—one accessible to people regardless of citizenship status, ability, education, race, and gender—for more and more people as our reach and visibility grows.

Response: Currently, PeepMe is a team of about ten people, plus our tech team. Our goal is to raise $650,000 to launch and maintain the platform until it becomes self-supporting. So far, we have received $60,000 in donations, which means we can now afford to continue paying a cybersecurity specialist, a social media manager, and for account services that the founders were once paying out of pocket. We’re slowly succeeding in building something that once felt impossible.  Ultimately, I have a vision of a sex industry that is owned entirely by sex workers. Brick-and-mortar strip clubs, major porn studios, camming and porn-streaming platforms, adult fan sites—they should all belong to us and only us. The sex industry has been controlled for too long by people who make money, hand over fist, from our labor, without taking on any of the social or carceral risk that sex workers take on. They have exploited us, because they are able to due to societal stigma and criminalization. Anti-sex work abolitionists have capitalized on this exploitation to enact laws that have made our labor even less safe. The only way to change the system of exploitation is to put power into the hands of the workers. PeepMe is a bold step in that direction. We still have a long way to go, but we won’t be coded away.


Prompt: If you’re interested in donating to our efforts to create the first ever cooperatively owned adult fan site, please sign up for our newsletter at peep.me. Since the early months of the Covid-19 pandemic, María’s house has been run like a factory. Every day, her family of six synchronizes their routines so two people are always behind a computer. María, her husband Rodrigo, and their children, Daniela (20), Andrés (18), and Camila (13) are among the unknown number of Venezuelans who, after years of political and economic crisis exacerbated by the pandemic, now try to make a living by annotating data through crowdsourcing platforms. Using two Canaima laptops, which the Hugo Chavéz government provided a decade ago for school children, they tag images and videos, transcribe text and audio, search for information online, and send videos and pictures of themselves to developers at companies and research institutions in Europe and North America. The developers use this data to train machine learning algorithms, like the ones that do facial recognition, moderate content, and guide self-driving cars.

Response: The family’s activities all revolve around data production because this is their only source of income and, according to María, they have to “focus on the same objective to survive.” She and Rodrigo do most of the work, although she also takes care of many domestic duties. Camila, Andrés, and Daniela work part time on data annotation while attending high school and university. Only María’s youngest child, Sebastián (7) is able to focus exclusively on school. Although most crowdsourcing platforms’ terms of use state that each account must be run by a single adult, often the only hard requirement to set up an account is for someone to prove that they are at least eighteen years old by taking pictures of an identification card and their face, and praying that a third-party facial recognition verification system called Onfido detects a match.


Prompt: The platform the family works for pays them a few cents per task, in cryptocurrency. They are only allowed to transfer the money to their online wallet once they have made at least the equivalent of ten dollars. After working every day of the week, they usually earn around twice that much, but recently they have barely made the minimum. “Last week, we couldn’t cash in,” Maria told me. “We couldn’t even make five dollars in total.” Her family dreads the day when the tasks will stop coming, the computer breaks, or they will lose access to the internet and electricity. Ofelia, another data annotation worker, who has diabetes, depends entirely on the platform to purchase insulin. “I would die without this income,” she told me. “I would literally die.” Income from data annotation is essential to Ophelia, María’s family, and the other Venezuelans who do this work because hyperinflation has made the official monthly minimum wage in the country worth only a few dollars, which is not enough to afford staple foods to survive even a week. That has rendered most jobs paid in bolivars, the national currency, unsustainable. After years of economic mismanagement due to government corruption and its economic dependency on oil, Venezuela has a goods and services shortage and has inflation levels that are consistently among the highest in the world. This situation, combined with its existing internet infrastructure, has made the country an appealing target of crowdsourcing platforms. In the absence of a robust social safety net, workers often see these platforms as their most reliable source of income in US dollars.  Before the pandemic, María and her family were migrants in neighboring Colombia for a year. María worked at a beauty salon while her husband Rodrigo worked selling coffees in the streets. The children all studied in the public education system. These were difficult but more stable times for the family. When the pandemic hit, María lost her job and, with deserted streets, Rodrigo couldn’t find many clients. With no other choice, they decided to return to Venezuela. “Here we had to look for options, and a friend recommended the platform to us,” Maria said. When the pandemic stopped in-person teaching, it meant that her three eldest children were stuck at home too, and could also perform data annotation work. In dozens of interviews with platform workers in Latin America, many of whom are or were migrants, I have heard similar stories: they were collectivizing platform labor across their household members, with teenage children doing more and more work after the onset of the pandemic.

Response: In these ways, the political and economic crisis in Venezuela, as well as the pandemic and remote schooling, have turned out to be productive for data annotation platforms, their clients, and the venture capitalists that back them. (These crises have also generated profits for companies selling information to carceral states: Onfido, the identity verification company used by electronic wallets, shares the identity and facial recognition data it collects with the United Kingdom police.) The thousands of companies and research institutions that develop artificial intelligence are using platforms to find cheap outsourced labor, especially from low-income economies, for global markets in which data and labor are sold as commodities. One of the results is a race to the bottom in which wages get lower and lower as competition between platforms—and their ability to find pools of ready labor even among people living in refugee camps—goes up.


Prompt: The invisibility of the workers in this process, and the myth of “one user, one account,” which permeates the technology industry, are at the center of many tech companies’ business models; in many cases, they pretend that their products are entirely automated and devoid of human intervention. In fact, the most popular data-annotation platform in the United States and India, Amazon Mechanical Turk, is named after an eighteenth-century automaton that deceived spectators by seeming to play chess autonomously while concealing a human player inside. From the clients’ perspective, workers are just users or, even worse, less than robots: “To be successful at this job, you have to think like a machine,” said one of the platform administrators to Cecilia, a worker I interviewed.

Response: Once we see through the single-user facade, we can begin to appreciate the ways in which workers and their networks have gamed data annotation platforms and collaborated to mitigate the crises they face. These survival tactics can be important resources for other workers and communities facing similar exploitation. At the same time, though, these tactics indirectly serve to prop up the neocolonial labor practices of the platforms, their clients, and venture capital. In order to challenge these larger forces, we not only need to hold companies and research institutions accountable for the value they extract from “indivisibilized” workers. More importantly, we need to support emerging community-based alternatives to data annotation platforms—alternatives built by the people actually subject to this highly extractive form of work.


Prompt: Survival Tactics In the suburbs of Valencia, in Carabobo State, data-annotation workers like Alfredo must increasingly rely on their own efforts to survive. “Our water comes from a pump,” Alfredo told me recently. “Every block of houses has a well, and every day the community designates someone to operate the pump to fill those wells.” The country’s ongoing economic and political crisis has caused the state and traditional businesses to become less present and effective in peoples’ lives; with little support from their local institutions or from employers, workers have increasingly had to rely on families and local communities for survival. Many of these communities manage water and waste disposal locally as common goods and services. These community-based services are necessary so workers can be ready for work, but not always robust or safe; for example, workers in communities that have had to resort to private waste incineration have been poisoned by smoke pollution.  Community support is also critical online, where workers share resources and organize with others through social media platforms like Facebook and Discord. Originally, the data-annotation platforms themselves created internal online groups to communicate with workers; however, these groups were heavily policed by moderators from the platforms. On one occasion, Roberto, a Black Venezuelan, wondered why Onfido’s AI could not manage to match his face and ID to validate his account. The moderators responded by expelling him from the online group. “I was astonished,” he told me. “I was expelled for asking a question!”  This kind of policing prompted many workers to form their own groups. Through my interviews, I found groups where workers would seek help learning how to complete tasks, complain about the platforms, and, on one occasion, organize a strike: members of a major Facebook group for data-annotation workers in Venezuela tried to convince their peers not to work for a few days, inspired by colleagues in the Philippines who, according to the organizers, successfully improved their wages by refusing to work. Despite the organizers’ efforts, most workers and their families were so dependent on the platform income that they couldn’t join the strike.

Response: Through my interviews, I also found that some workers are part of smaller, closed groups on text-based apps like Telegram. These groups have a few dozen members with fees of a few dollars per month. (It was through Rogelio, the administrator of one of these groups, that I interviewed María and her family.) These sort of online professional associations were built for workers to help each other, to generate trust, and to access currency traders, who exchange virtual dollars and cryptocurrency for bolivars. In these groups, workers share resources, like bots that alert them when tasks are available, and guides that explain how to solve tasks more efficiently. I was told that one group pooled their savings to pay a programmer in Spain to code one of these bots for them.  Workers also use the groups to buy and sell accounts on the data-annotation platforms. New platform workers are not allowed by the platforms to perform many annotation tasks, and it takes a great investment of time to gain access to the best work. As a result, there is an informal market for the highest, “level 3” accounts, which are sometimes sold individually for roughly ten US dollars, or in packages of at least as many as ten.


Prompt: Online worker groups can also transcend the virtual—for example, when a fellow member cannot work from home and needs a place to go, or when a member tries to take advantage of another one. A worker named Rodolfo told me about a colleague who refused to pay after receiving login details for ten platform accounts. “Hopefully, the moderators have personal information of every single member, including addresses,” he told me. “They contacted the seller physically and realized that she had lost access to electricity and couldn’t complete the transaction.” Trust in his fellow workers is essential in a context where online scams are common.

Response: These forms of community support are vital to workers, but they also put the onus on workers to make the data platforms’ business models sustainable. But even then, workers are disposable: when a platform can no longer drive down wages in a particular country, they can simply look to other places and other crises.


Prompt: Beyond the Visible Since platforms are not usually physically and administratively present in the countries where workers are located, they can relocate quickly. I have conducted quantitative research on the web traffic of ninety-three crowdsourcing platforms and shown that some of those present in Venezuela are now targeting workers in Kenya. This repeats the same model used by non-data-annotation gig work apps, such as Uber, which launch in a country with incentives that make workers dependent on the platform and then remove those incentives once they create dependency.  Making workers and their communities more visible may be one way to demand these platforms change their business models. But pointing out the collective exploitation at the heart of data annotation should also be used to pressure the platforms’ clients, including developers, management, and individual researchers, as well as investors, shareholders, and university administrators. In order to do this, we need more efforts to document the origins of datasets, third-party audits on AI models to assess their compliance with local and international labor standards, and assessments of the working conditions of platforms.

Response: However, as the scholar Noopur Raval argues, making workers and their communities visible is not enough. Since the economic incentives for platforms and their clients will remain, major actors in the data-annotation pipeline need to be directed to change their practices through regulation. In addition, in the place of exploitative multinational gig work platforms, companies and research institutions that require annotation need to support local initiatives from unionization to cooperative ownership of locally created platforms.


Prompt: In fact, there is a burgeoning ecosystem of platform companies owned and managed by workers. These companies have the potential to be more sustainable alternatives to the mainstream gig economy platforms. The Platform Cooperative Consortium lists 506 co-op projects in thirty-three countries. Many have emerged in sectors like ride-hailing and delivery, but the market for cooperative data annotation remains untapped. It is also worth mentioning that local impact sourcing companies, where data annotation occurs on-site by employed workers, could represent a more reliable alternative, in terms of data quality and labor conditions, than many platforms currently in the market. Ultimately, only solutions that recognize the communal nature of work and economic justice can have transformative effects on the lives of workers like María and her family. Inequality in platform labor is not an issue of individual workers, but networks of people who resist the paradox of a technology that innovates for some by exploiting others.

Response: The first time that I borrowed someone else’s voice I was six years old. After surviving two years in care-less foster homes, I had recently moved in with a family I loved and hoped to be a part of permanently. But, I worried, would I really get to stay? At the time, with no other recognizable means to communicate, I used the trailer for the film Angels in the Outfield to ask my most pressing question: “Dad, when are we gonna be a family?” I knew exactly when the kid popped the question, and when I saw him turn to face his dad, I’d hit STOP on the VCR. It took a number of tries before my parents learned to hear me, but eventually they did and began reassuring me that I was there to stay.


Prompt: We soon began creating a number of tools to communicate with each other. Cameras became our main translators. My parents took pictures of everything: activities, places, people, foods. They used the photos to make sure I understood them and to teach me how to make choices by picking photos of what I wanted. I could escape a plate of cauliflower by bringing them a logo for KFC. Each photograph was labelled with the printed word, so I could learn sight words and begin to understand what they were saying. Still, not everything could be captured in a photo. I needed other means of communication to say “stop” when my dad tickled me and I needed to catch my breath, and a way to say “bathroom,” when I needed to pee NOW. And so we developed a basic sign language to convey essential messages. Instead of insisting I join their speaking world, my parents learned these new languages with me.

Response: When it was time to start regular kindergarten at my neighborhood school, I brought my languages with me. Before long, my classmates and I were all using photos and learning to spell with our fingers. But participating in school also required new technologies. I started using a simple voice-output device like the single-switch BIGmack and Cheap Talk 8 that allowed me to play pre-recorded messages in either my mom’s or dad’s voice to answer questions during class. Because I had learned to communicate in these ways, I was taught to read and write, first with laminated sight words and later with a seventeen dollar label maker from Staples.


Prompt: By the time I entered middle school in 2003, written English had become my dominant mode of communication, and I began to develop a public voice. As my language got more sophisticated, so did my devices. The Gemini—a large laptop device with a touchscreen that was a quarter of my weight—allowed me to create a countless number of expressions with any degree of sophistication. In ninth grade, I got the Dynavox, a smaller but similarly heavy equivalent to the Gemini, with a clearer mechanical voice. It had a hard drive prepopulated with thousands of phrases, but they didn’t sound like me. With one finger, I laboriously programmed in as many of my own phrases as I could.  For more private conversations, I far preferred the silence of written words. I brought my labeler with me everywhere, using it to converse with friends and process trauma with my therapist. It wasn’t until the tenth grade, when I got my first laptop with text-to-speech software, that I had one lightweight device that allowed me to communicate silently or speak with a digital or recorded voice.  These are only some of the different technologies and modes of communication that I have used over the past two decades to gain entry—and be heard—in speech-based society. Speech-generating computers and augmentative and alternative communication (AAC) devices, like the Gemini and Dynavox, have allowed me to contribute to discussions about my people, as well as the world around us. Because they are easy for hearing-based communities to comprehend and sophisticated enough for us to convey complicated ideas in an apparently timely and efficient manner, communication technologies have given me and other alternatively communicating people a voice to be heard by large groups of people over space and time. But those technologies have also worked to define—and confine—us through their economics, their software, and the ways in which they reinforce ableist culture and notions of how communication ought to be structured.

Response: AAC devices have been around for over seventy years, yet most nonspeaking people in the US still experience widespread segregation in school and throughout their lives. I am one of only two alternatively communicating autistics to be fully mainstreamed from kindergarten through college graduation. One of the problems is accessibility. In our society, the Gemini and the Dynavox cost $12,000 and $9,000, respectively. Even at $500, an iPad with text-to-speech software is still unattainable for many disabled adults on social security, who receive $770 per month to cover all of their living expenses.  Even for the relatively small number of us who can access these technologies, we are too often left to rely on prerecorded, preordained messages—to speak only the devices’ language. In our speech-centric, hearing-privileged society, speakers are unquestioningly assumed to be able-bodied, self-reliant individuals whose vocal cords effortlessly produce spoken words and whose ears naturally decode spoken language. AAC devices have been designed to mimic this narrow “ideal.” According to research, 90 percent of what a person says in a given day is made up of repetitive, automatic phrases. AAC devices are populated only with these generic messages.  This ableist design assumes speakers know best what others should say and limits the kinds of relationships nontraditional communicators can form. The technology also renders invisible how much effort and time it takes to communicate this way, and it requires nothing of the speaking, hearing world. When we choose not to use AAC devices—with their stiff, generic, confining, and inauthentic prerecorded messages—society usually stops offering us other ways to connect and instead declares us “uneducable,” “untrainable,” “asocial,” “unempathetic” and “willingly walled off from the world.” I have come to think of ableism as the cultivated garden of a speech-based society. Many assistive technologies assume the disabled are outsiders, striving to inhabit that cultivated garden. These technologies don’t change the world we live in; they just allow a few of us to climb up and over the garden wall, helping us pass or pose as independent, able-bodied, speakers. Once in the garden, we are seen as validating the status quo, further fortifying the very walls that many of us hope to dismantle with other technologies, other modes of communicating, other ways of being.


Prompt: Hearing in Red We do not have a ready word for the kind of flexible communication that I practice. Instead of calling someone who uses this kind of flexible communication a “multimodal communicator,” as I choose to do, people like me are labelled “nonspeaking.” People use the verbal/nonverbal binary to render nonspeakers unheard and therefore invisible. In a speech-centric, hearing-privileged world, we are always seen as disabled, lacking. “Success stories,” maybe; “inspirations,” perhaps—but always on others’ terms. What would it mean to build technologies that create opportunities for more multimodal communication and the dense interpersonal connections such communication offers? For the past five years, I have been working through a combination of art and activism to imagine what these other modes of communication might be. My starting points are the modes of communication that I used as a child. There was an interdependent flourishing that formed around the technologies my classmates and I used in my early school years. These technologies were more multisensory, more communal, and in a sense more democratic; in pictures, sign language, and tangible sight words, my parents, teachers, friends, and I were all learners, all teachers. Using these alternative, communal languages, others in our classroom considered “at-risk for school failure” found their own pathways to literacy: some learned to spell with their fingers, others learning English as a second language used photographs as helpful translators, and visual learners found that pictures grounded in meaning what fleeting, spoken words could not.  A decade and a half later, I had another insight into multimodal communication. In 2016, I was late into my undergraduate thesis in Anthropology, before I realized I was writing an autoethnographic study that completely left out the contributions of people who prefer nonalphabetic languages and that remained largely inaccessible to the majority of nontraditional communicators, who are never taught to read. A high achiever in mainstream education from kindergarten through college, I had come to communicate almost entirely in written English. What, I wondered, might I have lost in the process? I began engaging with the visual artwork of various autistics, eventually compelled by the drawings, paintings, and sculptures of seven artists to write a poetic series. By the last poem, modes of communication had begun to blur as I proudly tell five-year-old impressionist artist Iris Grace that “I’m no longer visual exactly; nor am I verbal. When I type, my fingers speak / with an accent.”

Response: Around the same time I was finishing my thesis, production was also wrapping up on Deej: Inclusion Shouldn’t be a Lottery, a documentary about my life, which I co-produced and narrated. In the first four minutes of the film, I use a myriad of technologies—my laptop and Dynavox, trees, walls, backpack, other people’s bodies and voices, film, literacy, and a combination of spoken poetry and animation—to maneuver my way past communication and physical barriers at my high school. That opening sequence is something of a model for what I imagine communication might be like in a world that doesn’t privilege speech over other, more interdependent, modes of communication.


Prompt: The strongest example of this multimodal way of communicating are the parts of the film when my poetry and the oil-paint animations of the British artist Em Cooper converse with each other. In Cooper’s constantly flowing work, no image is static. Figures emerge briefly and then merge into the background, before re-forming into other figures; everything blurs into everything else. In a dynamic that seemed to reproduce the differences between speech-dominant cultures and more multimodal ways of connecting, other animators who were approached to work on the film took my words too literally, pairing the lines “The ear that hears the cardinal hears in red” with a cartoon cardinal and “The eye that spots the salmon sees in wet” with an animated salmon. Cooper’s brushstrokes, by contrast, were full of color, motion, and texture, occasionally offering a fleeting trace of vines, volcanoes, waves, or flags—metaphors I had used elsewhere in my writing to describe myself or challenge the world we lived in.  Cooper and I never thought we were taking everyone in the audience to the same destination; instead, we offered people multiple pathways into a world in which everything is interwoven, where motion, rhythm, pattern, color, sound, and texture freely interact, offering endlessly unfolding possibilities. I recognized, however, that this was a rarefied means of communicating; not something that could always be open to me, let alone anyone else. Four years later, at the outset of the pandemic, I began to ask myself how technology might allow us to create new communities in which diverse bodies, voices, and language might come together, as they had in my collaboration with Cooper, and thrive, much like we all had in kindergarten.  Cut off and segregated in my own home, I turned again to poetry and technology to create some alternative pathways: co-teaching multigenerational, global, and intersectional poetry writing courses for beginning poets, and collaborating with three fellow poets based on the artwork of the artist Malcolm Corley, who is also autistic. In both the courses and the collaboration, speakers and alternative communicators came together to make work that challenged the supremacy of speech-based culture. Traces of our entanglements live on in a chapbook, Studies in Brotherly Love. In the introduction, poet Claretta Holsey describes our modes of communication this way: “We crafted poems that speak to us and to our causes: awareness of performative utterances, as communication can and does happen outside of written text, outside of simple speech; embrace of Black vernacular, its rhythm and blues; recognition of the Black family as a model of resilience; respect for nature, which awes and overwhelms; respect for the body, made vulnerable by want.”

Response: Imagining that technology alone can liberate us is a bit shortsighted and, in some ways, disabling. But, if we imagine the cultivated garden of a speech-based society is the only way of being, then the communication technologies we build will continue to keep us stuck in an inclusion/exclusion binary, in which some beings are seen as disposable and others not.


Prompt: Ontology of God Big Mike says I read that dogs don’t have a sense of time       a minute  is like an hour an hour like a day              a day like a minute. The continuity is skewed & time is placed without thought into various boxes. I think  what it must be like to be a dog because                 yes       I be  with my dogs in this massive cage              trying to exhaust every thread of thought surrounding time. Maybe that’s why we say things like Oh, [name]?  Yeah that’s my dog & use dog as a placeholder for when we secret the names of those involved              in the robbery stabbing         extortion.                We want to shake off the slough of our numbered bodies            hieroglyphs                in our skin sluiced onto the floor.  We want to live in a space free of calendars & clocks & the minutes              we must share              but the high fruits are not ready to fall from this life. Not yet. Ciph & Civ claim God body & who am I to tell them otherwise                when we all want to claim master                            key to lock                    silo to grain & again own the con- tents of our own dufflebags & spoken languages without restraint. Still when I call Doc he says What’s good God? & tells me about my god- daughter           her mews & her small body taking hold of the world around              her. When I buried my faith I didn’t dig deep                        no           I didn’t & from the dirt sprung forth a woman I asked her                      I said What is your name? & she just smiled past me      which left me confused. When I woke up I went to commune with the poodle down the hall who quietly trotted  around while her master played cards.

Response: Bodies of Water There are no empty vessels when everything has proper weight.  — James Wood Sitting in the substance abuse class we talk about moderation                     the therapist                 Elissa loosening the clenched jaws each man has labored for years to claim as his own                            opening the floor to the stories we  claim. The watch-words are criminal thinking & this is commonplace. This is everyday  in the joint                       correction. That’s what this is               correction                           correction in the depart- ment of closely governed boxes.                  Bodies  of water are different                 no longer  signified in themselves                     but              these            bursting symbols                       overflowing with money &  drugs & the women we see in photo-  copied porn. They become our desires transposed amongst the pasts we had assumed  to be ours                       stories we lived in real-time               yet are read fast by this institution as empty glasses                         vessels to be filled  & tossed long into whatever ocean  borders the nation with the most bullets & the most mechanisms to keep us  from loading those bullets. We are thirsty  for any other ocean                 for bodies of water                      not                       weighted with the remnants of these floating cages                            of correction              of anything unseen                               but still policed.


Prompt: Intro I don’t know how I ended up         here       yeah actually I  know. I called it              I made myself a dumb prophet & cuffed my own  wrists like a God who creates  & creates         & creates         too many worlds to wave his hand                     or  whatever he believes he’s doing               over & grant the prayers of his reckless children. He gets  mad because he gets shown up.           He  fails at the feet of his creations. I know how  I got here.         When I first came  down    they tested my criminal- ity by sitting me down  in a small room                        an office             giving me a battery of statements like If my fam-  ily gets hurt I feel the urge  to retaliate & some people deserve to be pun-  ished (that one I laughed at). I was  to answer with agreement                      or strong denial. I must have  passed                             my report read Low Prob-  ability of Reoffense but a sentence is a sentence              & now it’s almost a decade  with more to go & all my files in a drawer full of other  men’s histories                      so many  histories. Do you know the stories       Do you know who  I am       Do you understand  what I am           Can I tell you I’ll try to sing this broken  song    & summon my tribe      ones  who will one day carry me home    & damn            damn       I know  it’s a moonshot but        maybe  you’ll come find me before I lose myself in this jungle.

Response: 1/ What’s in a cloud?  Writers have long used clouds as metaphors for metaphor-making. In Hamlet, Hamlet messes with his girlfriend’s dad, the courtier Polonius, by pointing out the different shapes he sees:  H: Do you see yonder cloud that’s almost in the shape of a camel?P: By th’ mass, and ’tis like a camel indeed.H: Methinks it is like a weasel.P: It is backed like a weasel.H: Or like a whale?P: Very like a whale.


Prompt: As always, the play is playing with perception. Can a person ever know what’s real? Is that a reasonable thing to even care about? The point is also that Polonius cannot be trusted; he is a sycophant. Hamlet will stab him dead two scenes later. 2/ Clouds are ambiguous. Liquid solid. Ethereal material. As Shakespeare’s Mark Antony says, their most striking images “mock our eyes with air.” The writers in this issue think about clouds of various shapes. Several address the cloud—that is, the global archipelago of warehouses that collectively coordinate the world’s computing power.   Today, the press tends to talk about the cloud in imperial terms. It is the Valhalla of Amazon, Microsoft, Google, Alibaba; it is strongman leaders demanding data sovereignty for their country of a billion plus people. But those who have worked in data centers for decades tell a different story. The cloud, they point out, came into many firms from the bottom up, at the behest of engineers, not management. Yet even those who were there on the ground floor, who worked with “bare metal” and knew what it felt like to cut your fingers on the rails that held racks of servers in place (“a badge of honor”), could not anticipate the new forms of power that the cloud would bring.  The advent of the cloud did not only create the conditions for the concentration of unprecedented amounts of wealth and information in the hands of a few firms. It also changed how rank-and-file engineers worked. The so-called Agile revolution started before the cloud took off. But it gained speed with it. Like previous developments in the computing industry, Agile combined counterculture and cyberculture; it was ostensibly rebellious, but committed rebels to sprinting toward corporate goals.   Other writers in this issue take, literally, to the sky. Aloft, clouds remain difficult to assess. Even as political consensus in favor of trying to reach “net zero” grows, climate scientists will struggle to measure emissions and to compute what it would take to offset them. One trick of the cloud metaphor is to suggest that recording and computation are everywhere, and yet hazy points remain.

Response: Obscurities remain on clear days. Taking sprawling aerial surveillance programs in their sights, other contributors argue that the obscurity of individuals and organizations who have amassed the power to see everything must be dispelled. They share strategies for gaining information about government and corporate plans. Transparency is always a struggle.


Prompt: Clouds are part of the weather, and another sense of weather is the Romance language one: le temps, el tiempo, il tempo. Time itself. This issue explores other temporalities, and the bodies they are tied to. One writer celebrates “crip time” as an alternative to “flow,” which is not about fulfilling work discipline, but rather about learning to be stuck. Another writer imagines other times altogether. This issue contains the first speculative fiction we have published.

Response: 3/ Throughout human history, clouds have acted as omens. Aeromancy is the art of divining the future from the sky. This issue considers possible futures, without being too predictive; the sky is a complex canvas, and its patterns shift quickly with the wind. I first encountered Agile when I got a job in a library. I’d been hired to help get a new digital scholarship center off the ground and sometimes worked with the library’s software development team to build tools to support our projects. There were about six members of this team, and I noticed right away that they did things differently from the non-technical staff. At meetings, they didn’t talk about product features, but “user stories”—tiny narratives that described features—to which they assigned “story points” that measured the effort involved in completing the associated tasks. They met every morning for “standup,” a meeting literally conducted standing up, the better to enforce brevity. A whiteboard had pride of place in their workspace, and I watched the developers move Post-it notes across the board to signify their state of completion. They worked in “sprints,” two-week stretches devoted to particular tasks.


Prompt: At meetings with the rest of us on the library staff, the head of the development team reported on progress using software that included a dashboard indicating the state of every project. The manager could also show us a graph of the team’s “velocity,” the rate at which the developers finished their tasks, complete with historical comparisons and projections.  This was Agile, I learned, a method for managing software development that had achieved enormous popularity in technical workplaces of all kinds—and, increasingly, even non-technical workplaces (including, as one TED speaker would have it, the family home). Honestly, I was impressed. In my own work, I often felt as though I was flailing around, never quite sure if I was making progress or doing anything of real value. The developers, in contrast, seemed to know exactly what they were doing. If they ran into a roadblock, it was no big deal; they just dealt with it. They expected requirements to change as they progressed, and the two-week time horizons allowed them to substitute one feature for another, or adopt a new framework, without starting all over from scratch.

Response: That’s the beauty of Agile: designed for ultimate flexibility and speed, it requires developers to break every task down into the smallest possible unit. The emphasis is on getting releases out fast and taking frequent stock, changing directions as necessary. I was intrigued; Agile was different from anything I’d experienced before. Where had it come from, and why? I began to explore the history of Agile. What I discovered was a long-running wrestling match between what managers want software development to be and what it really is, as practiced by the workers who write the code. Time and again, organizations have sought to contain software’s most troublesome tendencies—its habit of sprawling beyond timelines and measurable goals—by introducing new management styles. And for a time, it looked as though companies had found in Agile the solution to keeping developers happily on task while also working at a feverish pace. Recently, though, some signs are emerging that Agile’s power may be fading. A new moment of reckoning is in the making, one that may end up knocking Agile off its perch.


Prompt: Turning Weirdos into Engineers Software development was in crisis even before the word “software” was coined. At a 1954 conference convened by leaders in industry, government, and academia at Wayne State University in Detroit, experts warned of an imminent shortage of trained programmers. The use of the term “software” to mean application programming first appeared in print in an article by statistician John W. Tukey four years later. By the mid-1960s, at least a hundred thousand people worked as programmers in the United States, but commentators estimated an immediate demand for fifty thousand more.

Response: In the first decades of the programming profession, most experts assumed that formulating computer-readable directions would be a relatively trivial job. After all, the system analysts—the experts who specify the high-level architecture—had already done the hard intellectual work of designing the program and hardware. The job of the coder was simply to translate that design into something a computer could work with. It was a surprise, then, when it turned out that this process of translation was in fact quite intellectually demanding.  The nature of these intellectual demands, along with the larger question of what kind of work software development actually is, continues to baffle managers today. In the computer’s early years, it seemed to some people that coding was, or should be, a matter of pure logic; after all, machines just do what you tell them to do. There was, self-evidently, a formally correct way to do things, and the coder’s job was simply to find it.  And yet, the actual experience of programming suggested that coding was as much art as science. Some of the most advanced programming, as Clive Thompson notes in his 2019 book Coders, was pushed forward by long-haired weirdos who hung around university labs after hours, hackers who considered themselves as much artisans as logicians. The fact that one couldn’t physically touch a piece of software—its storage media, perhaps, but not the software itself—made software development more abstract, more mysterious than other engineering fields. Where other fields could be expected to obey the laws of physics, the ground seemed to be constantly shifting under software’s feet. Hardware was perpetually changing its parameters and capabilities.  Nevertheless, the field of electronic data processing—the automation of office functions, like time cards and payroll—was growing rapidly. The hulking machines designed for the purpose, leased from IBM, quickly became the hallmark of the technologically forward-thinking operation. But they required teams of operators to design the programs, prepare the punch cards, and feed data into the system. Established managers resented the specialized expertise and professional eccentricity of the growing ranks of “computer boys.” They resented, too, that software projects seemed to defy any estimation of cost and complexity. The famed computer scientist Frederick Brooks compared software projects to werewolves: they start out with puppy-like innocence, but, more often than not, they metamorphose into “a monster of missed schedules, blown budgets, and flawed products.” You could say, then, that by the late 1960s, software development was facing three crises: a crying need for more programmers; an imperative to wrangle development into something more predictable; and, as businesses saw it, a managerial necessity to get developers to stop acting so weird.


Prompt: It was in this spirit of professionalization that industry leaders encouraged programmers to embrace the mantle of “software engineer,” a development that many historians trace to the NATO Conference on Software Engineering of 1968. Computer work was sprawling, difficult to organize, and notoriously hard to manage, the organizers pointed out. Why not, then, borrow a set of methods (and a title) from the established fields of engineering? That way, programming could become firmly a science, with all the order, influence, and established methodologies that comes with it. It would also, the organizers hoped, become easier for industry to manage: software engineers might better conform to corporate culture, following the model of engineers from other disciplines. “In the interest of efficient software manufacturing,” writes historian Nathan Ensmenger, “the black art of programming had to make way for the science of software engineering.” Chasing Waterfalls And it worked—sort of. The “software engineering” appellation caught on, rising in prominence alongside the institutional prestige of the people who wrote software. University departments adopted the term, encouraging students to practice sound engineering methodologies, like using mathematical proofs, as they learned to program. The techniques, claimed the computer scientist Tony Hoare, would “transform the arcane and error-prone craft of computer programming to meet the highest standards of the engineering profession.”  Managers approached with gusto the task of organizing the newly intelligible software labor force, leading to a number of different organization methods. One approach, the Chief Programmer Team (CPT) framework instituted at IBM, put a single “chief programmer” at the head of a hierarchy, overseeing a cadre of specialists whose interactions he oversaw. Another popular approach placed programmers beneath many layers of administrators, who made decisions and assigned work to the programmers under them.

Response: With these new techniques came a set of ideas for managing development labor, a management philosophy that has come to be called (mostly pejoratively) the “waterfall method.” Waterfall made sense in theory: someone set a goal for a software product and broke its production up into a series of steps, each of which had to be completed and tested before moving on to the next task. In other words, developers followed a script laid out for them by management.  The term “waterfall,” ironically, made its first appearance in an article indicting the method as unrealistic, but the name and the philosophy caught on nevertheless. Waterfall irresistibly matched the hierarchical corporate structure that administered it. And it appealed to managers because, as Nathan Ensmenger writes, “The essence of the software-engineering movement was control: control over complexity, control over budgets and scheduling, and, perhaps most significantly, control over a recalcitrant workforce.” This was precisely the kind of professional that waterfall development was designed to accommodate.


Prompt: But before long, software development was again in crisis—or crises. Part of the problem was keeping up with the need for new computer scientists. Universities in 1980 couldn’t fill the faculty positions necessary to train the huge number of students with ambitions to become software engineers. “This situation seriously threatens the ability of Computer Science departments to continue developing the skilled people needed both by our information processing industry and by an increasingly technological society,” warned the Association for Computing Machinery.  The industry’s dearth of qualified developers wasn’t its only problem. Software development itself seemed to be struggling. Waterfall’s promise of tightly controlled management was a mirage. No amount of documentation, process, or procedure seemed capable of wrestling development into predictability. Software projects were big, expensive, and they seemed to be spiraling out of control—huge initiatives foundered unfinished as requirements changed and warring project teams bickered about details. Despite managers’ efforts to make software development reliable and predictable, it seemed, if anything, to have only grown more unwieldy. As the computer scientist Jeff Offutt put it, “In the 1960s, programmers built ‘tiny log cabins,’” while “in the 1980s, teams of programmers were building office buildings”—and by the 1990s, skyscrapers. Yet teams of technologists seemed unable to coordinate their work. Peter Varhol, a technology industry consultant, estimates that in the early 1990s, the average application took three years to develop, from idea to finished product. Technology was supposed to make American business smarter, faster, and more profitable, and yet the most respected corporations couldn’t seem to get their projects off the ground.

Response: The designation of “engineer,” the administrative hierarchies, the careful planning and documentation: all of this had been intended to bring order and control to the emerging field of software development. But it seemed to have backfired. Rather than clearing the way for software developers to build, waterfall gummed up the works with binders of paperwork and endless meetings.  For their parts, engineers complained of feeling constrained by heavy-handed management techniques. They just wanted to build software. Why were they hamstrung by paperwork? The typical picture of corporate programming in the 1990s is of the existentially bored twenty-somethings in Douglas Coupland’s novel Microserfs, or the desperate developers in Mike Judge’s movie Office Space, whose rage lurks just below the surface.


Prompt: Khakis and Dad Jeans Enter what may be the world’s most unlikely group of rock stars: seventeen middle-aged white guys, dressed in khakis and dad jeans, all obsessed with management. The now-legendary authors of what came to be called the Agile Manifesto gathered at Utah’s Snowbird ski resort in February 2001 to hammer out a new vision for the software development process. This wasn’t their first meeting; they’d been gathering in various configurations to discuss software development for some time, though, until the 2001 meeting, they hadn’t come up with much to show for it. This time was different. Scrawled on a whiteboard was the Agile Manifesto, a set of values that, in the following years, would become nearly ubiquitous in the management of programmers, from fledgling startups to huge corporations. It’s pleasantly concise: We are uncovering better ways of developing software by doing it and helping others do it.Through this work we have come to value:Individuals and interactions over processes and toolsWorking software over comprehensive documentationCustomer collaboration over contract negotiationResponding to change over following a planThat is, while there is value in the items on the right, we value the items on the left more.

Response: The manifesto, supplemented by twelve additional principles, targeted the professional frustrations that engineers described. Waterfall assumed that a software application’s requirements would be stable, and that slowdowns and logjams were the result of deviating from management’s careful plan. Agile tossed out these high-level roadmaps, emphasizing instead the need to make decisions on the fly. This way, software developers themselves could change their approach as requirements or technology changed. They could focus on building software, rather than on paperwork and documentation. And they could eliminate the need for endless meetings.  It’s an interesting document. Given the shortage of qualified developers, technology professionals might have been expected to demand concessions of more immediate material benefit—say, a union, or ownership of their intellectual property. Instead, they demanded a workplace configuration that would allow them to do better, more efficient work. Indeed, as writer Michael Eby points out, this revolt against management is distinct from some preceding expressions of workplace discontent: rather than demand material improvements, tech workers created “a new ‘spirit,’ based on cultures, principles, assumptions, hierarchies, and ethics that absorbed the complaints of the artistic critique.” That is, the manifesto directly attacked the bureaucracy, infantilization, and sense of futility that developers deplored. Developers weren’t demanding better pay; they were demanding to be treated as different people.


Prompt: Organizational Anarchists It seems likely that changes in opinions about the nature of software development didn’t take place in 2001 exactly, but in the decade leading up to the authorship of the Agile Manifesto. Consensus was growing—among developers, but also among managers—that software development couldn’t be made to fit the flow-charts and worksheets in which analysts had placed so much hope. Software, as the historian Stuart Shapiro wrote in 1997, is complex in a particularly complex way: the problems are “fuzzy, variable, and multifaceted, and thus rarely proved amenable to any one approach; instead, they demanded hybrid and adaptive solutions.” Not, then, forms and timecards. Moreover, as the workforce of programmers grew by leaps and bounds in the 1990s, companies hired, of necessity, people without formal computer science training. These younger workers likely had less invested in the drive of the 1970s and 1980s to turn software development into a science. The manifesto wasn’t really a shot across the bow: it was more of a punctuation mark, emphasizing years of discontent with prevailing models of corporate management.

Response: Nevertheless, while Agile had a devoted following, its mandate—the removal of top-down planning and administrative hierarchy—was a risk. It meant management ceding control, at least to some extent, to developers themselves. And most large companies weren’t willing to do that, at least not until the 2010s. Between 2012 and 2015, though, according to the Agile consultancy Planview, more than 50 percent of practicing development teams characterized themselves as “Agile.”  Doubtless, some of this popularity had to do with the growth of high-speed internet connections, which drastically altered the way software got released. Before, it wasn’t unusual for software to be updated once a year, or at even longer intervals. The fact that updates had to be distributed on physical media like CD-ROMs and floppy disks limited the speed of new releases. But high-speed internet made it possible to push out fixes and features as often as a company wanted, even multiple times a day. Agile made a lot of sense in this environment.


Prompt: Facebook’s famous former motto, “Move fast and break things,” captured the spirit of the new era well. It was an era that rewarded audacity, in software development as much as in CEOs. Venture capital firms, on the hunt for “unicorns,” poured record amounts into the technology sector during the 2010s, and they wanted to see results quickly. Competing with startups required the ability to change on a dime, to release constantly, and to develop at breakneck speed. The risk calculus shifted: it now seemed dangerous to stick with waterfall, when Agile promised so much speed.

Response: Equally, it seems, what it meant to be a software developer had changed. In the 1970s and 1980s, experts held up the systems-minded, logic-loving scientist as the ideal software worker. But over the years, this ideal had failed to take root. The programmers of the 1990s read Wired, not Datamation. If their characteristics can be intuited from the Agile Manifesto, they were intently committed to the highest standards, working quickly and confidently because managers “trust them to get the job done.” They refused to do things just because they’ve always been done that way, turning their minds to “continuous attention to technical excellence.” They weren’t thrown by fluid, fast-moving requirements; instead, they embraced them as an opportunity to “harness change for the customer’s competitive advantage.”  The image of the free-thinking nonconformist fits the philosophy of Agile. The manifesto’s authors may have looked like textbook engineers, in button-downs with cell-phone holsters, but “a bigger group of organizational anarchists would be hard to find,” according to Jim Highsmith, one of their number. Particularly in the early days, there was a lot of talk about the challenge Agile posed to the traditional management paradigm. Agile’s proponents were proud of this nonconformity: the framework “scares the bejeebers out of traditionalists,” wrote Highsmith in 2001. “Agile was openly, militantly, anti-management in the beginning,” writes the software developer and consultant Al Tenhundfeld. “For example, Ken Schwaber [a manifesto author] was vocal and explicit about his goal to get rid of all project managers.”  Anti-management, maybe, but not anti-corporate, not really. It’s tempting to see the archetypal Agile developer as a revival of the long-haired countercultural weirdo who lurked around the punch card machines of the late 1960s. But the two personas differ in important respects. The eccentrics of computing’s early years wanted to program for the sheer thrill of putting this new technology to work. The coder of Agile’s imagination is committed, above all, to the project. He hates administrative intrusion because it gets in the way of his greatest aspiration, which is to do his job at the highest level of professional performance. Like the developers in Aaron Sorkin’s The Social Network, he wants most of all to be in “the zone”: headphones on, distractions eliminated, in a state of pure communion with his labor.


Prompt: Management’s Revenge Back at my library job, I kept an eye on the developers, admiring their teamwork and pragmatism. As time went by, though, I couldn’t help but notice some cracks in the team’s veneer. Despite the velocity chart and the disciplined feature-tracking, the developers didn’t seem to be making all that much progress. They were all working hard, that was clear, but there was a fatal flaw: no one really knew what the project was ultimately supposed to look like, or exactly what purpose it was supposed to serve. The team members could develop features, but it wasn’t clear what all these features were being tacked on to. Maybe that problem came from my workplace’s own dysfunction, which was considerable. Still, I began to wonder whether the Agile methodology had some limitations.

Response: And, in fact, anyone with any proximity to software development has likely heard rumblings about Agile. For all the promise of the manifesto, one starts to get the sense when talking to people who work in technology that laboring under Agile may not be the liberatory experience it’s billed as. Indeed, software development is in crisis again—but, this time, it’s an Agile crisis. On the web, everyone from regular developers to some of the original manifesto authors is raising concerns about Agile practices. They talk about the “Agile-industrial complex,” the network of consultants, speakers, and coaches who charge large fees to fine-tune Agile processes. And almost everyone complains that Agile has taken a wrong turn: somewhere in the last two decades, Agile has veered from the original manifesto’s vision, becoming something more restrictive, taxing, and stressful than it was meant to be.  Part of the issue is Agile’s flexibility. Jan Wischweh, a freelance developer, calls this the “no true Scotsman” problem. Any Agile practice someone doesn’t like is not Agile at all, it inevitably turns out. The construction of the manifesto makes this almost inescapable: because the manifesto doesn’t prescribe any specific activities, one must gauge the spirit of the methods in place, which all depends on the person experiencing them. Because it insists on its status as a “mindset,” not a methodology, Agile seems destined to take on some of the characteristics of any organization that adopts it. And it is remarkably immune to criticism, since it can’t be reduced to a specific set of methods. “If you do one thing wrong and it’s not working for you, people will assume it’s because you’re doing it wrong,” one product manager told me. “Not because there’s anything wrong with the framework.” Despite this flexibility in its definition, many developers have lost faith in the idea of Agile. Wischweh himself encountered a turning point while describing a standup meeting to an aunt, a lawyer. She was incredulous. The notion that a competent professional would need to justify his work every day, in tiny units, was absurd to her. Wischweh began to think about the ways in which Agile encourages developers to see themselves as cogs in a machine. They may not be buried under layers of managers, as they were in the waterfall model, but they nevertheless have internalized the business’s priorities as their own. “As developers, IT professionals, we like to think of ourselves as knowledge workers, whose work can’t be rationalized or commodified. But I think Agile tries to accomplish the exact opposite approach,” said Wischweh.


Prompt: Al Tenhundfeld points out that the authors of the Agile Manifesto were working developers, and that the manifesto’s initial uptake was among self-organizing teams of coders. Now, however, plenty of people specialize in helping to implement Agile, and Agile conferences notoriously tend to be dominated by managers, not developers. The ubiquity of Agile means that it is just as likely to be imposed from above as demanded from below. And Agile project managers, who are generally embedded in the team as the “product owner,” find themselves pulled in two directions: what’s best for the developers on the one hand, and what they’ve promised to deliver to management on the other.  Even as the team is pulled in multiple directions, it’s asked to move projects forward at an ever-accelerating pace. “Sprinting,” after all, is fast by definition. And indeed, the prospect of burnout loomed large for many of the tech workers I spoke to. “You’re trying to define what’s reasonable in that period of time,” said technical writer Sarah Moir. “And then run to the finish line and then do it again. And then on to that finish line, and on and on. That can be kind of exhausting if you’re committing 100 percent of your capacity.” Moreover, daily standups, billed as lightweight, low key check-ins, have become, for some workers, exercises in surveillance. Particularly when work is decomposed into small parts, workers feel an obligation to enumerate every task they’ve accomplished. There’s also pressure for every worker to justify their worth; they are, after all, employees, who need to be perceived as earning their salaries.  “Story points”—the abstraction that teams use to measure the effort involved in particular development tasks—have also lost some of their allure. They began as a way to give engineers some control over the amount and substance of their work. And yet, in practice, they often serve as a way to assess engineers’ performance. “Once you’ve put something in a digital tool, the amount of oversight that people want goes up, right?” said Yvonne Lam, a software engineer based in Seattle.

Response: The problem isn’t just with surveillance, but with the way the points calcify into a timeline. John Burns, an engineer at a platform company, recalled a former workplace that simply multiplied story points by a common coefficient, in order to get a rough estimate of how long a project would take. Despite the points’ avowed status as an informal, internal measure, managers used them as a planning device.  The Next Crisis Underlying these complaints is a deeper skepticism about the freedom that Agile promises. Agile’s values celebrate developers’ ingenuity and idiosyncratic ways of working. But there are distinct limits to the kinds of creativity workers feel authorized to exercise under Agile, particularly because problems tend to be broken down into such small pieces. “It is clear that Agile dissolves many of the more visible features of hierarchical managerial control,” writes Michael Eby. “But it does so only to recontain them in subtle and nuanced ways.” Yvonne Lam notes that autonomy under Agile has distinct parameters. “People say you have the autonomy to decide how you’re going to do the work. And it’s like, yeah, but sometimes what you want is the autonomy to say, this is the wrong work.” There are so many choices to be made in the course of any software development project—about languages, frameworks, structure—that it’s possible to lose sight of the fact that developers often don’t get to weigh in on the bigger questions.  And, in the last few years, those bigger questions have taken on greater importance and urgency. We’ve seen numerous examples of tech workers organizing to change the direction of their companies’ business strategies: Google developers agitating to kill an AI contract with the Department of Defense, game developers agitating to end sexual harassment. These demands go beyond Agile’s remit, since they aim not to create conditions for workers to do a better job, but to change the nature of that job altogether.  It’s also worth considering how Agile might have played a role in creating a work culture that is increasingly revealed to be toxic for women, people of color, and members of gender minority groups. It’s an inescapable fact that the authors of the Agile Manifesto were a very specific group of people: white men who, whatever their varying experiences, have probably not spent much time in workplaces where they composed the minority. The working group has since acknowledged the deficit in the team’s diversity and vowed to incorporate a larger set of voices in the Agile Alliance, a nonprofit associated with the manifesto.


Prompt: But when you survey a list of Agile-affiliated methodologies, alarm bells might go off if you’re the kind of person who’s faced discrimination or harassment at work. Many people testify to the utility of “pair programming,” for example, but the practice—in which two developers code together, each taking turns looking over the other’s shoulder—assumes that the two coders are comfortable with each other. Similarly, the warts-and-all breakdown of Agile “retrospectives” seems healthy, but I’ve watched them descend into a structureless series of accusations; everything depends on who’s leading the team. And Coraline Ada Ehmke, former community safety manager at GitHub, has described how fellow developers used the code review—ideally a low-stakes way for developers to check each other’s work—as an instrument of harassment. We’ve long known that eliminating bureaucracy, hierarchy, and documentation feels great, until you’re the person who needs rules for protection.

Response: Could Agile even have played a role in some of the more infamous failures of the tech industry? The thought occurred to me as I watched Frances Haugen, the former Facebook manager turned whistleblower, testifying before Congress in October 2021. If a company sets a goal of boosting user engagement, Agile is designed to get developers working single-mindedly toward that goal—not arguing with managers about whether, for example, it’s a good idea to show people content that inflames their prejudices. Such ethical arguments are incompatible with Agile’s avowed dedication to keeping developers working feverishly on the project, whatever it might be.