Prompt: But Casaleggio also had a more calculated side. Since the 1990s, he had sold businesses digital tools for managing employee sentiment. These included web-based forums in which workers could float new ideas and air grievances, all while being monitored by their bosses. Casaleggio would then help employers intervene strategically in the online discussion, promoting certain ideas while tamping down dissent. It was this approach—offering users a sense of community and self-determination while quietly shaping the discourse from above—that Casaleggio later instituted in the realm of electoral politics, first through a wildly popular blog he built for Grillo in the 2000s and later with Rousseau, which launched shortly after his death in 2016.

Response: The 2017 leadership election that rogue0 hacked was a representative instance of Casaleggio’s approach. Five Star initially appeared to many observers to be a left-leaning populist movement—its first policy positions included advocating renewable energy, revitalized public transport, and a universal basic income—that railed against the real and perceived corruptions of Italy’s political establishment. But at heart both Grillo and Casaleggio had more right-wing sympathies. Casaleggio’s son Davide, who took over Casaleggio Associates after his father’s death, shares these sympathies. His and Grillo’s preferred candidate in the 2017 election was Luigi Di Maio, the son of an Italian neo-fascist.  Di Maio was already well known in the movement but, in the weeks leading up to the vote, Casaleggio Associates used Five Star’s blog to praise Di Maio repeatedly. The result was more like a confirmatory ballot than a plebiscite: members were essentially rubber-stamping the decision of the party bosses. “The election of Di Maio can be described as a ‘show election’ in the sense that there was not real competition,” the scholar Paolo Gerbaudo, whose book The Digital Party examines digital democracies around the world, told me. “All the candidates that could have stood a chance did not participate in the election, and the results were widely anticipated.” Far from making the vote more democratic, digital tools helped the party’s leaders engineer their preferred outcome.


Prompt: Business as Usual In the wake of Five Star’s 2017 leadership election, and the hacks by Luigi Gubello and rogue0, the Italian Data Protection Authority conducted an investigation into Casaleggio Associates for breaking data privacy laws. The hacks had revealed that the company was collecting an extraordinary amount of members’ personal data, along with their voting records, and combining this with data gleaned from members’ social media accounts. It’s the sort of information that could potentially be used to create highly targeted messaging for every member of the Five Star party, thus deepening Casaleggio Associates’ centralized control over the ostensibly popular movement.

Response: Around the same time as that investigation was underway, Five Star took legal action against Gubello, whom party leaders now accused of being rogue0. In January 2018, Italian police tracked down Gubello at his girlfriend’s house in Trieste and examined his phone and computer. Meanwhile, Five Star claimed Rousseau’s vulnerabilities had been addressed, and described the platform as a “fortress.” But in February, just a month before the 2018 Italian general election, rogue0 struck again, showing that they could still access the Rousseau database and take control of administrator accounts. In March, Five Star won a plurality of votes in the general election, and formed a coalition government with a nativist right-wing party called Lega, or the League. Di Maio was made the Minister of Labor and Social Policies, the Minister of Economic Development, and the Deputy Prime Minister. (He now serves as the government’s Minister of Foreign Affairs.) Rogue0’s identity has not been revealed, though the journalist Jacopo Iacoboni has perhaps come closest to discovering it. He has had a handful of conversations with the hacker via direct messages on Twitter. Iacoboni says it was rogue0 who reached out to him. “I never knew his real identity,” Iacoboni told me, assuming the hacker was one person, and a man. “But he seemed to me someone who knew people at Casaleggio Associates very well—this was my impression after our Q&A.” Today, Rousseau’s Movable Type content management system is gone. User passwords are now allowed to be longer than the previous requirement of just eight characters. “In fact, following orders by our [Data] Protection Authority, the Rousseau website was practically rewritten from scratch,” noted security expert Fabrizio Carimati. But it’s not clear exactly what’s replaced Five Star’s old systems. “Casaleggio now claims that the platform has been completely redone,” Iacoboni said, before noting that this is impossible to verify.   But the vulnerabilities go deeper than software. Luigi Gubello believes that for voters to put their faith in digital democracy, the systems being used need to be transparent. Yet algorithms, coding, cryptography—the building blocks behind a digital democracy—require expertise to fully grasp. “People must be able to trust the election process,” Gubello insists. “Can you trust it if you cannot understand and really check it?”


Prompt: This is part of the paradox that seems to be at the core of all digital democracy movements: the same technologies that are supposedly meant to empower members can instead provide vectors of control for party elites. Even Podemos in Spain, with its populist politics and sophisticated digital transparency measures, mainly holds confirmatory ballots approving decisions already made by the leadership, as Paulo Gerbaudo notes.  Both Five Star and its Rousseau platform are less celebrated than they once were. The party has crumbled in opinion polls and in January 2020, Luigi Di Maio resigned as leader amid infighting and defections. For the time being, he has been replaced by a caretaker leader. Di Maio’s resignation raises the possibility of another leadership contest conducted on Rousseau in the coming months. But the shine has gone from the party’s digital democracy ambitions. “We hear little of Rousseau now, it’s no longer really news,” Carimati said. “That’s because Five Star is one big crisis. And Rousseau is seen as increasingly irrelevant.” On a rectangle of land the size of a baseball field three hours northwest of London, a project called Hands Free Hectare plants and harvests wheat with almost no human intervention. For the last three seasons, an autonomous tractor has worked its way up and down the plot, sowing the wheat and spraying it with liquid fertilizer, herbicides, and fungicides. A small robot collects soil samples and a drone takes thermal photos of the crop from above to monitor for inconsistencies. When researchers determine that the time is right, they send an unmanned combine harvester to mow the wheat and shoot it into the back of a grain tractor that drives itself alongside the combine.

Response: Hands Free Hectare is just one of many examples of model farm projects that aim to demonstrate the promise of automated, autonomous agriculture on a large scale. In the US, the Microsoft-backed Grand Farm outside of Fargo, North Dakota is building a farm complex to experiment with robotic planting and irrigation; the University of California, Davis’ Smart Farm initiative is building “an Agricultural Innovation Hub to develop smart machines with industry collaborators.” Fully autonomous agricultural machinery is not yet commonly used, or even functional outside of very constrained environments. But the GPS-controlled machinery and drones that make that vision possible to imagine and fund today have already been widely adopted by agricultural operations all over the world.  The adoption of technologies to automate and generate data about farming operations is known in the industry and in academia as “precision agriculture.” The cheerleaders of this approach frame it as the optimization we need—“each plant gets just the right amount of water and fertiliser for maximum yield,” as the Financial Times put it in 2017—to feed the world’s billions of mouths and conserve resources in the face of climate change. Precision agriculture is heralded by development agencies and funders as a solution to food insecurity. Under the banner of “feeding the world” the digitization and datafication of agriculture have gathered so much momentum that their continued development and adoption seems inevitable.


Prompt: But the most promising takes on precision agriculture rarely mention the numerous threats that accompany it. All of that efficiency often requires not just sensors, but coordination among the sensors, routing of the data that those sensors collect back to a central data store, and ongoing monitoring to ensure that batteries haven’t died and connections haven’t dropped along the way. The proliferation in agriculture of systems that are supposed to run themselves has created a massive surface area of weak links, delicately strung together.

Response: Threats to food supplies have always come in many shapes and forms: famine, war, and sabotage have wreaked havoc on societies throughout human history. Now, those of us whose access to food is mediated by digitized agricultural production systems face a double threat: the rapidly expanding mesh of insecure devices that control how our food is planted, watered, monitored, harvested, and transported; and, at the same time, the shifting balance of power away from farmers, towards the governments, corporations, and investors that wield massive amounts of capital.


Prompt: Making Hay In its purest form, the goal of precision agriculture is to guide or control every part of the food production system: what type of seed to use, how much fertilizer to apply, when to plant and harvest. The approach has its origins in the Geographic Information Systems (GIS) that was introduced on farms in the 1960s and 1970s to plot the locations of soil samples on a map, and in GPS receivers and mobile tools to monitor yields and soil composition, introduced in the 1990s. More recently, the rise of precision agriculture has been enabled by the explosion in internet connectivity that the world has experienced over the past ten years.

Response: Farmers historically have been early adopters of sophisticated agricultural technologies, driven as much by incentive as by need. Governments often provide subsidies to digitize agricultural equipment and methods. Today, almost every piece of agricultural machinery sold by international corporations like Kinze, Deere, and Case IH has navigation systems and a variety of sensors pre-installed on it by the equipment manufacturers. Farmers can supplement these preinstalled systems with additional receivers on equipment like sprayers and combines, as well as ground sensors and drones that collect data points on moisture levels, mineral levels, and crop growth. Even smallholders—those farming on less than ten hectares, or a 1/25th of a square mile—are using these technologies in places like Nigeria, Colombia, and Indonesia.


Prompt: McKinsey & Company considers agriculture to be a “massive opportunity” and an area “ripe for disruption.” Goldman Sachs expects the market to soon be worth $240 billion. Despite questionable returns, agriculture has become a darling of VC; according to the VC fund AgFunder, agricultural technology startups secured nearly $17 billion in funding in 2018, up 43 percent from 2017.  Academic institutions, too, have turned their prowess towards fostering the development of new agricultural technology through startup accelerators and enhancing technologies of established corporations. Indeed, according to food systems expert Kevin Walker, academics in the US are becoming subcontractors of large multinational corporations, driven by the need to find funding for research that has “immediate and marketable benefits.” The US government and military are also invested in the research and development of precision agriculture tools. The US Navy has invested in agricultural robotic swarm technology. Many of the startups developing drones for commercial agriculture are run by military veterans or former defense contractors. Even economic development sector initiatives rely upon defense contractors.

Response: These types of funding streams yield specific results. The demand by VCs and universities for exponential returns in a short time frame means that security is, as with many non-agricultural venture-backed software startups, an afterthought. Hardware is adapted from other sectors and software outsourced, with no plan for service, repair, or maintenance, leaving pieces of equipment perpetually vulnerable to exploitation when it reaches end-of-life. And, even if they wanted to, private companies trying to translate government research and development into consumer agricultural products don’t have the billion-dollar budgets to prioritize security in the same way that DARPA might.  Breach Party Many of the same security vulnerabilities that plague battery-powered, cloud-connected devices in general affect farmers adopting precision agriculture. In an interview with precision agriculture expert Marc Window, a professor associated with Hands Free Hectare said of the project’s approach to security, “As with most of our ag robot developments we use technology that has been developed outside the ag area and migrate it over as and when needed. Security has not been a hot topic at all recently as we are still getting the fundamental systems working. Mostly we just use Wi-Fi.” This approach to (not) securing connected agricultural machinery is the norm, and it means that, in the same way that corporations can remotely brick a piece of machinery, malicious actors could hypothetically do the same, bringing a fleet of tractors down at once. One can imagine a scenario in which a piece of code is deployed to disrupt the harvest of entire nations. Or a scenario in which chicken farmers who use web-based software to remotely control the temperature of their hatcheries find their cooling systems manipulated, killing their animals.  These are not purely hypothetical. China’s environmental efforts are being thwarted by companies doctoring surveillance camera footage and remotely altering or deleting undesirable information in automatic monitoring systems in order to appear more environmentally friendly than they are. A smart irrigation system in Israel has reportedly been hacked by the Syrian Electronic Army, a hacker group. Smart irrigation systems in general can be manipulated to empty entire water reservoirs or apply the wrong amounts of fertilizer and chemicals.


Prompt: Drones are being heralded as revolutionary in agriculture, but they have many known vulnerabilities since their security is essentially unregulated. They can be hijacked, remotely tampered with to return false data, or piloted to infiltrate remote Wi-Fi networks. The US Department of the Interior also sees espionage risks in the fact that its own drone fleets are manufactured by a Chinese company.

Response: The tools of precision agriculture generate valuable datasets, and the value of those datasets corresponds to their size. To give a sense: the largest dairy farm in the world occupies more than 22 million acres and the largest field operation sits on more than 500,000 acres. Data from these operations can move markets. The US Department of Homeland Security has reported that at least one company has been approached by commodity brokers with an offer to buy the company’s data. But insider trading threats aside, the integrity of large operations’ data can be undermined by weaknesses in any number of factors that make precision agriculture work—IoT devices, software, or physical hardware. Although such market sabotage doesn’t appear to have happened yet, agricultural data breaches have: the security industry’s annual data breach compilation identified eleven data breaches among agricultural companies in 2019.


Prompt: Even as US government agencies propel the adoption of precision agriculture, they recognize the new security threats that it poses. In 2016, the FBI released a joint memo with the USDA warning farmers that they were increasingly at risk of having their data held for ransom or of bulk data theft. In 2017, the US Navy conducted war games designed to train servicemen to protect key sectors, including food and agriculture, against malicious state and extremist actors. Soldiers were trained to mitigate attacks like remote tampering of temperature readings at a vegetable canning facility and ransomware targeting an agricultural company’s financial data.  Roll Your Own Milk Sensor Backup But war games won’t help farmers whom precision agriculture has made increasingly dependent on complex systems beyond their control: on the software that runs farming equipment, which can require paid subscriptions and constant updates; on the creditors who own the equipment, often worth hundreds of thousands of dollars, and to whom farmers must make regular payments; on manufacturers who have access to the data the equipment generates; and on the guarded knowledge of licensed repair technicians who are the only ones able to diagnose problems with proprietary systems.  Take the relationship between farmers and John Deere, the largest manufacturer of agricultural machinery in the world. For years, John Deere has put proprietary software and hardware in its tractors, but now those tractors are increasingly connected to John Deere’s servers as well. According to an executive with the company’s innovation arm, “Our large equipment now has 4G LTE modems, with Wi-Fi and Bluetooth, and that does two-way communication so it collects data off your farm and sends it to the cloud.” As a result, the company can see all the data collected by the machinery they manufactured and can also remotely lock down, or “brick,” equipment if they suspect that farmers are trying to repair the equipment in unsanctioned ways. Farmers have responded with the Right to Repair movement on the basis that they shouldn’t have to fear having their own tractors remotely bricked for any reason, much less formaking repairs.

Response: Or consider Emiel Stam, a Dutch dairy farmer who used AgroVision robotics to milk his cows. He claimed in Dutch court that one of the robot’s sensors malfunctioned, infecting his cows and forcing him to cull his cattle. To make his case, Stam needed a historical record of the offending sensor’s readings—in this case, the milk flow sensor.


Prompt: Stam had backups of those sensor readings through the machinery’s software interface, but they had been remotely wiped by the robotics company, which had access to the readings through a maintenance contract. Luckily, and very unusually, Stam had additional independent backups. He used his own data to correlate the milk sensor readings with the onset of his cows’ illness, prove the robotics company’s liability, and win damages for his losses. But he is the exception that proves the rule.

Response: Beyond 2FA Now that food systems globally are increasingly vulnerable to digital manipulation, farmers need to protect themselves. The FBI’s 2016 joint memo with the USDA encourages both small and large-scale agriculture operations to implement standard digital security measures: using secure passwords, setting up two-factor authentication, accessing networks via VPNs, and having company-specific email accounts for employees.  But perhaps adding more technology to the technology problem is not the solution. One issue that extends well beyond agriculture is that there is no clear line of liability for the security of equipment and devices. To help demarcate where the responsibility lies, venture funds, development agencies, and government procurers could implement something like the US Department of Justice’s new policy on drone use. It requires partners and grantees to conduct a mandatory cybersecurity risk assessment and honor a data retention policy. Imposing such requirements on small organizations would be a financial burden, but perhaps such a cost is worth paying to protect farmers and food supplies.  While these steps are necessary, they are not sufficient. We have a globally connected food system, and ameliorating harm requires systems thinking. Hacks are inevitable when we use connected technologies; the more we become reliant upon them to bring in our harvests, the more we can be assured that these systems will be exploited.


Prompt: To start us off, could you tell us about yourself, your background, and how you came to work with the Detroit Community Technology Project? I'm Tawana Petty, also known as Honeycomb. I’m a poet, a mom, a social justice organizer, and a water rights advocate. I direct the Data Justice program for Detroit Community Technology Project (DCTP), and through DCTP I convene the Detroit Digital Justice Coalition.

Response: Right now, one of the Data Justice Program's main initiatives is slowing down the rapid expansion of Project Green Light, which is a public-private partnership around facial recognition technology spearheaded by the Detroit Police Department (DPD). We're also creating educational resources about technology, surveillance, and equitable participation in the Census. During the time that Project Green Light was ramping up, DCTP was involved in a research project called Our Data Bodies, which I can tell you more about later.


Prompt: When Project Green Light got started, we had no concept of the scope of surveillance it  would take on. The project gets its name from flashing green lights that are connected to video surveillance cameras inside and outside of different businesses. The cameras are monitored twenty-four hours per day, seven days per week, at DPD’s real-time crime centers and mobile devices.

Response: It started off with cameras at eight gas stations—ones that stayed open during late night hours. The police wanted to use these cameras to signal to community members that the gas stations were now safe to enter at any time, because police were constantly going to be watching them. They partnered with two private companies on this project: Guardian Alarm and Comcast.


Prompt: Fast forward a couple of years. We now have close to six hundred cameras all over Detroit, and the Mayor would like to push that number to 4,000. Project Green Light locations pay a monthly rate so that if something happens at that location, they get priority from police over non–Green Light locations. So they pay for policing. And then, of course, the DPD leadership signed a contract to use facial recognition on everything from drones, traffic lights, mobile devices—pretty much anything they could attach a surveillance camera to. They were using that facial recognition technology on footage from their Green Lights for about two years before social justice activists and technologists in the city really got wind of it, when DPD tried to push through a directive that would solidify their use of it. Before that proposal, there was no policy governing its use.

Response: What did the rollout of Project Green Light look like within the community, and how did you start to organize folks against it? The police really tapped into this negative narrative that has hovered over Detroit for decades. They were touting Project Green Light as the salvation of the city, like, “Hey, we have the answer. We know you are all afraid of each other, so we're going to give you all these security cameras, and you’re going to feel safe because we're always going to be watching you.” The police department’s campaign targeted senior citizens mostly—the ones who are retired or sitting at home, inundated with media images. They didn't hide the idea of putting cameras everywhere like they later hid their adoption of facial recognition. In fact, they were trying to separate the two ideas, saying that Project Green Light was different than facial recognition. But the two systems needed each other; the city needed to overhaul itself with all these surveillance cameras in order to make facial recognition a viable system. The DPD just kept saying, “Facial recognition is not embedded within the cameras,” and, “We'll only use the facial recognition if we absolutely have to.” Meanwhile, they were proposing policy directives that were asking for real-time live tracking on mobile devices, drones, traffic lights, and more.


Prompt: Initially, when we were showing up to meetings at the Board of Police Commissioners, there were a lot of residents, mostly senior citizens, who were really angry with us. They felt that we were getting in the way of a system that would make them safe, and that we were attacking police because we just wanted to cause trouble. In reality, we were just trying to educate residents, law enforcement, and the Board of Police Commissioners on the harms of mass surveillance and facial recognition. Over time, we were able to argue that facial recognition and Project Green Light needed each other to work the way that DPD leadership and city government wanted them to work, and you couldn’t have one without the other. We were also able to make the case that safety and surveillance were not synonymous.

Response: Was your resistance mainly organized around police commission meetings? How else did you all create pressure? We spoke at police commission meetings and town halls. We collaborated on a special surveillance issue of a magazine called Riverwise, where we brought together information about Project Green Light, the problems with facial recognition, and alternatives that would create actual safety. We also created a report, “A Critical Summary of Detroit’s Project Green Light and its Greater Context.” “Green Chairs, Not Green Lights” is our counter-campaign. We’re encouraging community members to come back to their front porches and look out for each other. We’re raising consciousness and building real safety, and we’re saying that a system set up to prioritize profits and institutions over people is wrong.


Prompt: I imagine you all are working in coalition with many different groups in this campaign. What are those different groups? Also, there’s a long history of activism and in particular Black-led activism in Detroit. How do you and the rest of the coalition situate yourselves within that history? Yeah, absolutely. In addition to serving as director of the Data Justice Program here at DCTP, I'm also on the board of the James and Grace Lee Boggs Center to Nurture Community Leadership. James and Grace Lee Boggs are now ancestors, and a long legacy countering these sorts of things was created under their expert tutelage. [Eds.: James and Grace Lee Boggs were revolutionaries who worked to dismantle capitalism and racist oppression nationally and through fostering community-based, grassroots activism within their adopted home city of Detroit.] Our former Boggs Center board member Ron Scott, who is also now an ancestor, co-founded the Detroit Coalition Against Police Brutality, which still exists. I'm part of the Black Out Green Light Coalition and Green Light Black Futures coalition, which is organized by Black Youth Project 100 (BYP100). I also collaborate with the Detroit Justice Center, Media Justice, Color of Change, and Fight for the Future. Finally, I'm part of a lot of coalition work with the ACLU that collaborates with dozens of organizations that have been consistently resisting mass surveillance in the city.

Response: Ultimately, we were unsuccessful in getting DPD to stop using facial recognition, but we did have some wins within the policy that the Board of Police Commissioners ultimately passed. We're definitely tuned in, which is why I think we were able to achieve any policy changes at all, even if what we wanted was a ban. Honestly, getting any of those changes in a city with this many Black people took a tremendous amount of work and was an uphill battle. All the other cities that were successful with bans were predominately white. Folks aren't as eager to take the ever-watching eye off of a predominately Black city.


Prompt: Could you tell me about those changes and what the policy looks like now?  Under the new policy, the police are prohibited from using facial recognition on any live feeds. Even though still photos are also very problematic, the thought that DPD would have been able to track people's faces as they walk the streets was very unnerving. So they're not able to do that. DPD can only use facial recognition to investigate violent crimes. They're barred from using it for immigration enforcement. They're barred from predictive analysis—using the technology for pre-crime, essentially. They're barred from mobile use, so they're not able to use their mobile devices to walk through crowds and track people using facial recognition, which is something that happened in Baltimore during the Freddie Gray protests. They're barred from violating the First, Fourth, and Fourteenth Amendments—freedom of religion, prohibition against unreasonable search and seizure, and due process under the law. Now, I'll tell you that I don't believe that's even possible—I think if you mass surveill a city, there's no way you're not going to violate those amendments.

Response: The Board of Police Commissioners receives a weekly report on how the police are using facial recognition. Unfortunately, the Board of Police Commissioners, which is supposed to be a civilian oversight body, hasn't been very transparent with those reports. None of them have been made accessible to the public. They don’t even question the contents of the reports when they are handed them in meetings, at least not any of the Board of Police Commissioners meetings I have been present at. It's discouraging.


Prompt: Most significantly in the policy, Detroit police officers are supposed to be criminally investigated if they misuse the technology. Their misuse is supposed to be reported to the mayor, the Board of Police Commissioners, and the city council within twenty-four hours of discovery, which would lead to dismissal and further legal action.

Response: But I would say that our greatest accomplishment was raising the consciousness of the city residents. Many, many residents were engaged in a process that, at first, they were just going along with. How did you do that?  For several months, we gave testimony at every Board of Police Commissioner meeting that involved the topic. Unfortunately, residents are only afforded two minutes to speak, even on topics as dire as this one. We leveraged our minutes to push forward a vision of people sitting on their front porches, the community having good schools, affordable water that doesn't contain lead, neighbors not getting evicted, neighborhood block clubs. We pushed for senior citizens to think about the times when they felt safe, and whether or not being held up in their homes under surveillance cameras actually made them safe.


Prompt: That understanding of safety was the scaffolding. And once we had that, we could build on it. We could say: what the police department is talking about is security; it’s not what you’re thinking of when you’re thinking about safety.  It really was a slow educational process, to be honest with you—constantly bringing materials and giving testimony. We’d bring examples of conversations we’d had with children, where we'd ask them a question like, “Say you lived on a street. On side A of that street, there were metal gates and cameras and drones and police. And on side B, there were a bunch of neighbors who knew each other, who looked out for each other, who knew that if John didn't come home at 7:00 p.m., then they should probably find out where John is. On which side of the street would you feel safest?” Kids almost always said, “How could I feel safe if I don't know the people who live next to me, you know?” That same type of teaching works with adults when they started to think it through.

Response: We also began bringing in the data around how facial recognition technology misidentifies darker skin tones in women and children, and how Detroit is 80 percent Black. We started reflecting back what DPD leadership themselves were actually saying. For example, DPD leadership indicated that of the 500 times over two years that they used facial recognition, they only moved forward with 150 cases, because the other 350 were misidentifications by the system.


Prompt: We highlighted the fact that they were telling us the system was wrong at least 350 times and that they were relying on the naked eye of two analysts to catch the errors of the algorithm. This caused great concern about the potential of false arrests. So, we dissect what's being said and present that back to people consistently.

Response: You’ve mentioned how Detroit is 80 percent Black, a stark contrast to other, primarily white cities that have banned facial recognition. How does your fight in Detroit look different from the fight in whiter cities like San Francisco or Boston? We've built relationships with organizers in pretty much all the other places that have successfully banned facial recognition, including Portland, where folks are pushing for the most comprehensive ban. We've consistently told them: we need to synthesize what you all have done, but also apply a racial lens to it because it's going to be much harder to convince not just Detroiters but the world that a Black city doesn't need to be surveilled. It's a deeper, larger conversation and it requires a kind of organizing around anti-Black racism that often isn’t comfortable to do even in social justice or liberal spaces.


Prompt: That’s why I value the consciousness-raising piece so much. I really want to win this, but I also have to find some value in the fact that we've been able to raise the consciousness of people all across the US who now consider themselves invested in our struggle. So I take pieces from all the places that I've been able to visit and all the people that we've been able to talk to. But I also understand that there is a very real dynamic here that does not exist in cities that only have a 5 percent Black population.

Response: One of the things that I've consistently said is that Detroit is the last remaining Black mecca in the United States. If we don't succeed in resisting some of this violent system, there is no hope for Black residents across the rest of the country, period. Police departments have already tried to model this system in other cities—calling them Project Blue Light in Wisconsin, for example. They're just packaging up what city government is pushing through in Detroit. On any given day here, you can see drones flying through the sky like kites.  Wow, that's an apocalyptic vision. In past talks, you’ve talked about the rise of surveillance and how that ties in with the “resurgence” of the city, as money floods into gentrified areas like downtown and Corktown. Could you give a little bit of that historical context in Detroit?  There are areas of Detroit like Black Bottom and Paradise Valley that had Black hospitals, Black grocery stores and schools, and African-centered education—all these viable institutions—that were leveled for freeways. One of our challenges is getting folks to think about a time in the city when there was an abundance of thriving neighborhoods that were predominantly Black-owned, -led, and -invested.


Prompt: I’m always trying to point out the inaccuracy of the narrative that Detroiters just don't want to care for where they live, they don't want safe neighborhoods, they don't want viable institutions—that the system that we exist under is a choice. We're in a city with five hundred thousand Black people and the median household income here is $29,000 a year—which means that half the households in the city make less than that. Predominantly Black women-led households. Lots of children in extreme poverty. One hundred thousand people without water in their homes over the last ten years. Schools closed by the hundreds. I work to get people to see crystal clear that this isn't an accidental situation. It’s easy to convince anybody in the state of Michigan and the world that if something bad is happening to Detroit, we brought it on ourselves. There isn't a dissecting of how we got here, or the history of racism and the disinvestment that has happened for generations, you know? Watched, Not Seen At the beginning of our conversation, you mentioned the Our Data Bodies project. I understand the project is led by a five-person team that includes three organizers from different groups: the Center for Community Transitions in Charlotte, which focuses on folks who have recently reentered the community from incarceration; the Stop LAPD Spying Coalition, which organizes against police surveillance in Los Angeles; and you all at DCTP. How did those three organizations come together?  Our Data Bodies was initially a two-year research project between Detroit, Charlotte, and Los Angeles. We were thinking about the digital streams we all produce and the impacts that our information has on our interactions with government and police, on how we get resources, and on how our cities are developed. Within those two years, we learned that we wanted to move beyond a research project and expand on our organizing within our communities to increase self-determination around these systems.

Response: The three organizers—Mariella Saba, Tamika Lewis, and I—all originally applied for our positions on the project. The interview committee was very intentional in picking social justice organizers for these roles as researchers because the type of analysis that comes from organizing on the ground in the neighborhood was going to be important in making sure that we were prioritizing community members. That won’t happen if you just focus on having a good researcher. Research is something that can be taught; care and compassion for the people connected to the research is a longer process.


Prompt: So we all play to our strengths. I consider Stop LAPD Spying a mentor in this work, especially in resisting police and surveillance systems. For this project, Stop LAPD Spying and Los Angeles Community Action Network (LA CAN) put a lot of emphasis on unhoused populations and how Skid Row is a heavily targeted community that the LAPD uses to innovate new surveillance systems.  In Charlotte, Tamika does work around citizens returning from incarceration. Folks returning from incarceration constantly have to report back to the system. It's like the system is constantly waiting for you to fail. Tamika also brings an important perspective as a gender-nonconforming organizer: they understand how resistance to being defined under the dominate gender binary makes people targets for intensified surveillance.  How have you been able to make use of that experience and research? We’ve collectively produced materials like our Digital Defense Playbook, which is an educational resource and activity guide about data, surveillance, and safety that we created last year based on our three years of community research. We’ve taken that work to different neighborhood institutions, as well as academia. We’ve worked with data scientists, who are often disconnected from the real people represented by the statistics they analyze.

Response: We're all learning from each other and staying in constant communication about what's happening in our different cities, and hearing the same themes. Things like, “The one mistake that I've made in my life is now the thing that's limiting how I'm able to survive.” Or, “I'm feeling heavily surveilled because I'm trans,” or “I'm feeling super targeted because my credit isn't good,” or “I've just reentered society from incarceration and I feel like every move that I make is being scrutinized and monitored.” Across all the cities, community members wanted to be seen for something more than a mistake they made, or something more than their data. And they didn't want to be pursued and tracked and monitored.


Prompt: What exactly is a “data body”? Recently, we’ve seen the rise of various tools that let you see the data that companies have about you. But your approach seems more holistic. It’s not just, does Facebook have this data about me, but what are all of the different pieces of data that the government or private companies might have—and what am I able to do about it?  We try to get community members to think not just about the impact that their data has on them, but the impact that their data has on the decisions that affect their family, their neighborhood, and their city.  One of our exercises is called “What’s in Your Wallet?” As part of that exercise, we often use the example of a person who uses their EBT card at the liquor store up the street and purchases foods that aren't considered healthy. Those activities create a data trail. Maybe a bank will look at those data trails and decide not to invest in a grocery store in that neighborhood. It's difficult to know exactly how some decisions are made, but what we do know is that data is leveraged to make most of those decisions.

Response: That’s what we mean by data bodies. It’s not just the individual; it's the information that's been generated about this individual and the systems that interact to make decisions about this individual, this individual's family, this individual's neighborhood—all the data’s tentacles. In the Digital Defense Playbook, you cite a conversation with a community member who says about interacting with government agencies, "For their benefit they do communicate. But for my benefit, no." And I see this a lot in government work—if agencies want to communicate to surveil and penalize, then they can and will. But if you want them to share information to, say, verify that you’ve lost your job so that you can get food stamps, they often can’t or won’t.


Prompt: It seems like so much of your work with Our Data Bodies is trying to build data agency within a system where power is skewed heavily towards other organizations or towards the state. How do you help people build data agency to overcome that power imbalance? One of the things that we truly, clearly recognize within our work is that the power is going to come from the respiriting of community members. A lot of folks have been really dehumanized. There’s a quote that says, “Friendship begins at the moment when one person says to another, ‘What, you too? I thought I was the only one.’” And so it’s been this weaving together of stories to let community members know that they're not alone.  It’s saying: did you know that there is an open data portal in your city and that you can push for that to become a useful source of information? Or: did you know that you can request to have some of your information deleted from a government database? It’s letting people know: here's how these systems connect and interact with one another. It’s an ongoing process of learning how different people are experiencing these systems, but also tying them together with the stories of others so that they understand they aren’t isolated, that there are many people across the world resisting these systems.  We intentionally did not publish everything in the Digital Defense Playbook. There are stories that community members shared with us that emphasize how they're resisting systems that we did not share, which contradicts everything that a capitalist system would ask you to do. It's like, why not put it all out there? Well, because we actually want people to keep surviving.  The Digital Defense Playbook serves as a community organizing mechanism where we get to talk to people, we get to share stories, we get to respirit, we get to raise digital and media literacy. We don't think that it solves all the things. But we do think that when you build the confidence of community members, and you let them know that they're not alone, and that there are folks that are resisting these things all over, it does something for the spirit. So that's how we use it.

Response: In Person, In Print Like Our Data Bodies, the Data DiscoTechs organized by the Detroit Digital Justice Coalition seem like they aim to raise consciousness and agency around data within communities. Could you paint a picture of one for me? The “discovering technology” fairs, which we refer to as DiscoTechs, are kind of like a science fair at school—you know, with informational stations on different topics. To start one, we either respond to folks who have reached out to us or pick a neighborhood where we want to do one. We connect with an organizer or resident who lives in that neighborhood, who has the pulse of what's happening, and we support them in finding out what stations they think might most benefit their neighborhood.


Prompt: We start with a few stations that we definitely want to have. Recently, we’ve had stations where we’re telling community members what to expect with the census. What kinds of things get funded based on census data? What are some of the concerns that have been raised about the census? How has it been used in the past? How long is census data kept? We did research to empower community members with that information.

Response: But then the rest of the eight or nine stations are designed around what the community says they need. So they might say, well, in this neighborhood, it's a lot of senior citizens. They don't understand Twitter, they don't understand how to set up an email account, they just want to learn how to use a Mac—things like that. So then those are the stations that we will have. Community members are able to come in for free. We have music. We call it a DiscoTech, but it also has music and dance. At the last two, we gave away low-cost computers: the Raspberry Pi full kit, with the keyboard and everything. We gave those to residents who don't have that technology at home.  Who shows up to those DiscoTechs? Mostly young folks? Is it a mix of ages, of races?  It definitely depends where we have them. Some neighborhoods are predominantly senior citizens, so we'll have a lot of seniors show up. When we did one in southwest Detroit, it was a predominately Spanish-speaking undocumented community, so we had interpreters onsite, including youth interpreters. It was great. Those stations had mostly young and middle-age participants.


Prompt: I’m curious about the print magazine that you help produce, Riverwise. How are you involved? How did it come to be? I think it's the poet in me, but I don't remember a point in my life where I didn't feel obligated to push back against the dominant narrative of Detroit. I'm pretty sure there was a time, but I don't remember it.

Response: There was a newspaper in the city, the Michigan Citizen, that was trying to lift up community stories of resilience and resistance, countering the dominant narrative in the city. It was around for three decades, but then it ended. The Boggs Center felt that we had a responsibility to fill that void, or at least try to fill that void. And so we convened community members over a one-year period to see whether there was interest in trying to create consistent literature that would amplify community stories of resilience and resistance that would counter the narratives that were coming out of the city. Through those meetings, Riverwise was born. I am now part of the Riverwise Magazine Collective, and I serve on the editorial board. Eric Campbell, a former contributor to the Michigan Citizen is the managing editor. We put it out quarterly, and then we do some special editions, depending on what the situation is. That's how the special surveillance edition in collaboration with DCTP came about.


Prompt: We convene weekly and go through stories that we've heard ourselves, or we've pursued folks who we want to write for us, or we have people who send in submissions. Then we determine whether we want to theme the magazine based on something that’s happening in the city, or if this is one where we're just going to lift up various stories. And then we have these community discussions around what's written in the magazine. If a person did an article or something for the magazine, then we'll ask them if they want to host a community discussion and we will support them in that. We also host writing workshops to support residents who want to improve their writing skills or learn how to contribute content to the magazine. It’s not our coalition that does most of the writing workshops. We tap people in the community—poets, writers, you know, organizers—who want to host those workshops and then we just support them.  Calling All Co-liberators How can people support the fight against facial recognition? They can support organizations like Fight for the Future which are pushing for a federal ban on the government use of facial recognition. They could call or email their Congressperson. They can help us amplify our struggles.  In Michigan there are a few current bills that could use some support. There’s a bill in the State Senate, 2019 SB 0342, that's likely going to be passed. It was initially a ban on all police use of facial recognition, but now it's a ban on police use of real-time facial recognition. There was House Bill 4810, a five-year moratorium on the police use of facial recognition on everything—drones, body cameras, any surveillance technology—that’s still kind of lingering out there. And then there is the Community Input Over Government Surveillance ordinance that's before the Detroit City Council, which creates guidelines for council oversight and public input for surveillance technology. That one is currently being passed back and forth for amendments.  On the federal level, there's a Congressional bill called the No Biometric Barriers Housing Act of 2019 that bans the use of biometrics in public housing. There's also a bill out there called the Ethical Use of Facial Recognition Act that would prevent federal funding from being used for facial recognition technologies, including police and other government use. I’m not really sure what's going to stick beyond the Detroit city ordinance, though, and maybe the Michigan State Senate bill.

Response: But wherever you are, you can support the fight by continuing to try to politicize your community, push for alternatives to surveillance, and minimize the conflation between surveillance and safety. And in Detroit, we'll just continue the work by showing how invasive and insidious this technology is—hopefully before we see a slew of false arrests. We don't want to be living in a social credit system, where our every move is dictated by algorithms and surveillance cameras.


Prompt: Or at least more than what we have already. Exactly, yeah. It’s already a social credit system in Detroit, but we don't want to add more and more technologies to that and exacerbate the violence and marginalization that residents are already feeling. And we don't want this rolled out all across the globe as a way to contain and control Black and brown people and Indigenous people and poor white people. Surveillance is not safety.

Response: The hardest part for us is that law enforcement, government institutions, and too many people don't seem to see an alternative, especially in areas that have been deemed dangerous. But everyone needs to understand that most crime in our neighborhoods is rooted in poverty and disinvestment and racial violence. We need co-liberators; we don't need any more allies. We need folks to really feel their liberation is tied up in our liberation, you know? You founded the Library Freedom Project and you're also a core contributor to the Tor Project. Which came first for you? Library Freedom Project (LFP) came first. I was working at a library outside of Boston in Watertown, Massachusetts. Through a confluence of forces, including living through the Boston Marathon bombing and the police militarization around that, plus the Snowden revelations just a couple of months later, plus the nascent but growing Black Lives Matter movement... all of it made me think about technology and policing and privacy in a way that I never had before.  I started LFP in the summer of 2014. At first it just involved teaching people about privacy in my library, doing some introductory community events. When there turned out to be a lot of interest, I cold emailed the people at Tor saying, “Hey, I'm a librarian working on privacy, and I'm teaching people about Tor. Can I be in touch with your outreach people?” And they responded, “We don't have any outreach people. Do you want to be our outreach people?” That’s how the Tor connection happened.


Prompt: I read that the Library Freedom Project's pilot project was setting up a Tor relay in a public library. What is a Tor relay? The Tor network is made up of nodes run by volunteers. When someone uses the Tor Browser from their own computer, their web traffic gets bounced to all those different volunteer nodes so that someone looking from outside can’t trace that person’s web traffic back to their computer at their house. A Tor relay is one of those nodes; it’s a computer that’s configured to just forward traffic all day to other nodes of the Tor network.  We did set up a Tor relay in a library in New Hampshire around the summer of 2015. It wasn’t quite LFP’s pilot; I had already been running LFP for about a year at that point. But a lot of people first learned about us because the relay got the attention of the Department of Homeland Security (DHS), and that whole situation got some press coverage.

Response: How did the Tor relay project come about? And what was your pitch to that library? I had been traveling around the country doing these direct trainings, building relationships with librarians and helping them understand the surveillance problem from justice-focused angles. I was focusing on strategies that they could employ, both in their direct work with patrons, and then also in a bigger, advocacy sense—macro-level stuff they could do out in their communities.  The Tor relay project came about because I started thinking about how libraries are in a strong position to run privacy infrastructure. And Tor relays were the perfect example. In order to run one of these things, all you need is a little bit of bandwidth. It also helps if you are an institution rather than an individual, because law enforcement might be more likely to hassle an individual, especially if they run one of the exit relays, which is identifiable on the network.


Prompt: I thought, “Libraries are ideal for this.” Fortunately, because I had built all these relationships, I knew who the other hardcore privacy-minded librarians were. One of them was my friend Chuck McAndrew at this library in New Hampshire. He was already a Linux guy and he was as evangelical about privacy as I was. He was 100 percent on board with being the first library to set up a Tor relay. The conversation asking him to do it was quite simple. I was like, "Maybe you want to do this?" And he was like, "Yeah." So it was easy.

Response: The Tor Project has its critics. Did you get any pushback?  We set the relay up and promoted it. A cute little story ran in Ars Technica. And then the library contacted me a few weeks later and said, "We've gotten this email from our local police department who've been contacted by the DHS. They said that we’re not allowed to have the relay and that we have to turn it off." The library was understandably frightened.  I remember being pretty taken aback when I first read the email. But then I thought, “Well, this is the best thing that's ever happened to us.” At that time, people weren't thinking about DHS in the way that they are now—I mean, certainly immigration activists were, but the general public was not. You might recall that before Trump, DHS was seen as the ugly stepchild of the intelligence community. They're a Bush-era construction. People were like, “What do they even do?” And the "homeland" thing in their name is just creepy. So of all the federal law enforcement agencies that could have gone after us, they were the best because they're total yahoos.  We rallied around the library and got a lot of support from the ACLU and the Electronic Frontier Foundation and the local community. The libertarian separatist community that lives in New Hampshire even showed up. It was a great demonstration of support for the library and privacy, but also a broader rejection of that kind of law enforcement interference.


Prompt: We had a big public hearing, and you can imagine what a library board meeting on a Tuesday night in rural New Hampshire is normally like. But that night, it was standing room only. A bunch of press came. Meanwhile, no one from DHS showed up. They knew they had no legal grounds to ask the library to remove the Tor relay.  So anyway, the relay got turned back on and it was a lovely story. That was the first big thing that happened for LFP.  That's wild. How did DHS find out about the relay? Were they monitoring the library's internet traffic or social media or what? I guess they read Cyrus Farivar? He was the journalist who wrote the article about us for Ars Technica. Someone later did a FOIA request for the DHS emails and found that an agent linked that article and then said something funny about me. That was basically it.  Privacy School When did the Library Freedom Institute (LFI) happen?  People were super into the LFP trainings. I was getting invited to speak to a lot of librarians. It became apparent to me pretty quickly that I couldn't scale the project in the way that I needed to without bringing other people in somehow.  It was also clear to me from the beginning that we needed to have a community response to surveillance. I really wanted to build a community of practice that could meet that challenge, so I started thinking about what that could look like. I developed a blueprint for a six-month-long train-the-trainers workshop where librarians located in different places could get together online every week and learn about this stuff. I got grant funding, and our first LFI cohort of thirteen librarians started in June 2018.

Response: We're currently experimenting with different timeframes, but LFI workshops currently run for four to six months. Librarians apply to get into it. It's totally funded by the Institute of Museum and Library Services (IMLS), so it's free to attend. We spend each week online together thinking about a different aspect of the surveillance problem. To date, there are forty-three librarians that have finished the program, and another twenty librarians will begin the course in March 2020.  Where are these librarians joining from? We have librarians in twenty-one states. In this last LFI cohort, we had three people in Georgia, somebody in West Virginia, a couple of New Yorkers, a few in the Bay Area, one at Los Angeles Public Library, Boston Public Library, Hennepin County Public Library in Minneapolis. All over the US. For now, we’re restricted to the US since our funding is through IMLS, a US federal agency.  I make sure there are a lot of folks from rural libraries and Southern libraries since those libraries tend to be under-resourced and far from in-person training opportunities. We also prioritize public librarians because they tend to interact with the public more than academic librarians, and also because public librarians generally don’t have the professional development funding to make something like LFI happen on their own.  Do they come representing their patrons or are they also curious for themselves? A little of both. In order to be accepted into the program, there's a short application and it's basically a free-form questionnaire about what they see in their communities and what their personal experiences are that make them a fit for LFI. Sometimes their community is representative of who they are.  One of our librarians from the last cohort is Anishinaabekwe of the Sault Tribe of Chippewa Indians. They work in a non-Native community now, but their whole objective was to think about how surveillance affects Indigenous people. How, for example, Indigenous women are more subject to certain kinds of both domestic violence and state violence, and how surveillance intersects with that.


Prompt: To talk about surveillance online, you have to talk about how the internet works, and it seems like a fine line between being too high-level and too technically nitty-gritty. How do you teach about the internet?  Most of the time, what we're teaching is fairly 101-level. In terms of getting into the structure of the internet, we try to avoid getting in the weeds just because most people, whether they’re the librarians who we’re training for the first time or the patrons who our graduates go on to train, come into a privacy-focused educational setting feeling hopelessness and resignation. Often, they're dealing with a problem that is happening to them right now, like stalkerware or having had their identity stolen. They're already freaked out. Most people think they don't have a good sense of how technology works. They already feel stupid asking questions about it.  In LFI, we work with a trainer named Mallory Hanora, who comes from the world of  prison abolition and teaches us how to create transformative workshops. Their framework is about incorporating the experiences of the people in the room, being as nonhierarchical as possible, meeting people where they are—all these sorts of things to create an environment that people can actually learn in.  Then, LFI graduates are able to bring that kind of framework forward in their workshops with their own patrons. Usually when they teach, no matter what the focus of the lesson is, people will say during the question and answer period at the end things like, "I started using this password manager. Is this good?" Or, "My nephew told me about this thing I can download to block ads. What do you think about it?" That is fascinating to me because it confirms to me that people do care about their privacy. They are already taking steps to mitigate or manage what is revealed about them on the internet. They haven't developed a nuanced threat model for their own unique situation, but most people are already doing something. In those moments, LFI librarians have the information and facilitation tools to help patrons build on what they already know.

Response: User Testing in Uganda I want to make sure we also talk about Tor. What does your work on the community team look like?  I was the community team lead for two years and I'm still a contributor, though not at the level I used to be as Library Freedom Project has taken up more of my time. The community team works on outreach—teaching people about Tor and getting more of an understanding of who it's for and what it does. LFP really fits into that work. But beyond LFP, Tor is a global community, so our outreach is global.  The interesting thing about Tor software development and usability research is that we don't do the surveillance stuff that some software does to make sure that it's usable for you. We don't track your clicks or how your mouse moves around the page; we're not doing A/B testing and getting analytics back. So how are we supposed to know how well Tor is working for you? For years, we got that feedback directly from the most technical people because that was who was using Tor. But the problem with that method was that it meant we were designing for the most technical people, and if only the most technical people are using Tor, then Tor doesn't actually work.  A couple of years ago, we started focusing on making the Tor Browser usable for people doing social justice movement work—water rights, reproductive justice, queer and trans issues—around the world. We wanted to focus on members of these movements in the Global South for a few reasons. One is that we didn't want to have the kind of free software project that was all white dudes in the US and Western Europe, which is what most of those projects are and, to be honest, what ours kind of was. We also thought it was important to understand the context of using Tor in places where the internet is much slower and more expensive—places where there are all kinds of environmental factors that make using it harder, even if you know how to use it technically.  Our teams started traveling to meet with community organizers who were part of political movements in different parts of the world. We spent a lot of time learning about their contexts, what kinds of work they do, and who their adversaries are. Then, we showed them the Tor Browser, conducted some user tests, and asked for feedback. That's how Tor usability work has been happening for some time now.


Prompt: Can you give an example?  In 2018 I traveled to Uganda with Antonela Debiasi, the head of Tor’s usability team. We visited two cities: Kampala, the capital, and a smaller city called Hoima. Hoima is in what's known as the Albertine region of Uganda, after Lake Albert. They discovered a lot of oil in the Albertine region around fifteen years ago, and US, Chinese, and Israeli companies have been scrambling to extract the oil in that region since then.  Antonela and I met with a number of people in Hoima, mainly environmental activists. They were mostly doing journalism, writing and publishing anonymously to try to bring international attention to the environmental effects of large-scale oil extraction that they were experiencing. We asked them who their adversaries were and what they knew about the companies operating there. They had some anecdotes about people being followed and weird things happening with their phones.

Response: In that situation, we were able to bring knowledge about the surveillance capabilities of these big companies. We talked about different kinds of monitoring that may have been happening, like Stingrays for intercepting phone calls. Of course, Tor can only solve a piece of those issues, but it can really help with anonymous research and publishing, especially if you teach people about what its limitations are. And it's like that with every different group: we learn about their context, we think about what Tor can do in that specific context, and we share information about other ways people can protect themselves. The process was similar when we went to Kampala, although the activists we met were focused on different issues. There are a lot of refugees there from Sudan and South Sudan, so people were working with them. And we met with reproductive and gay rights activists.  In both cities, we were meeting with a combination of different people who knew each other through their own networks. I think that is fairly typical. In some cases, we try to go back again and meet with people a second time. But, in general, we learn all these things and then we take that information back to the developers and incorporate what we learn into the Tor Browser.  What were the meetings like? In general, our workshops with activists are fairly straightforward. We get together in a classroom and learn about their threat models—what kind of work they’re doing, who their adversaries are, what kind of work they would be doing if they felt less threatened by those adversaries. Since we work with people who are all familiar with each other through social and political networks, they tend to feel comfortable sharing these details in a group. After we get a better sense of their work, we give them a hands-on training on using Tor. We have them use their own phones and laptops, and we walk them through the download process while explaining what Tor does and doesn’t do. If it’s not safe for them to download the files directly—because evidence of the download would be visible to their ISP—then we can sideload them using a USB stick. We troubleshoot any issues that come up, and we learn about unique local challenges like data limitations, slow internet, or electrical outages. We think about the specific adversaries that these activists are facing and what kinds of capabilities those adversaries are likely to have.


Prompt: For example, from what we know about the companies operating in the oil market in Uganda, we can reasonably assume that they’re employing some security firm like NSO Group to spy on the activists. [Eds. NSO Group is an Israeli spyware company that sells surveillance software to governments.] And we know that the Ugandan government is monitoring them. Knowing those specifics helps us explain to activists how Tor can help. We also spend time conducting user tests, asking activists to complete a series of tasks using Tor Browser, and documenting what was difficult.  Beyond the fairly unique threat models that people are working with, it's helpful to know how internet infrastructure impacts Tor use and performance in different places. For example, using Tor in San Francisco is slower than using Chrome in San Francisco because, in order to anonymize your traffic, Tor bounces your web requests to relays all over the world before it returns the website you want. So we figured that a slower internet connection would make Tor even slower. How much slower? In Uganda, it turns out: not much! The electricity goes in and out, so you get disconnected, but that impacts every browser the same way. It's also helpful to know how much data Tor is using and how much mobile data plans cost; a lot of the people we met there are primarily browsing on their phones and we don’t want people to have to use up their whole data plans. We learned about censorship by internet service providers there and which anti-censorship mechanisms that are built into Tor will work in those contexts. There’s all sorts of feedback that's coming to us in those meetings. We take all this information and write up a report for the developers and the user experience team so that they can address any challenges that arose.  Socially Necessary Library Time You’ve said that the discussion about privacy is really a discussion about power. The fact that Tor solves a similar privacy problem for environmental activists in Uganda and also for librarians in the US seems to highlight that.

Response: Absolutely. That's the common thread in all of this, and that's my approach with Library Freedom Project. To me, privacy is the Trojan horse. Then when I get in the building, I'm like, “Alright, let's actually talk about capitalism.” Privacy is important, but what we're really talking about is the newest frontier of exploitation by capital.  With both Tor and the Library Freedom Project, you're making libraries places that are anti-capitalist not just because they're free, but also because data harvesting won't work in there. You're making a Faraday cage around libraries.


Prompt: I love that. I do think of libraries as one of the most socialist institutions that we have in the US in 2020: they are funded with public money. They are not means-tested. They're everywhere. You talk to the average librarian about why they got into the profession and there is a real love for the public. You can go into a library and you don't even have to use it for its explicit purpose of looking at books or magazines or computers. You can just go there and be, even if you’re the kind of person that late capitalism has decided is not worthwhile. To the library, you are. And this is a radical idea. Libraries’ doors are still open, even as their budgets get cut. They’re special spaces and I want to help them expand what they're capable of doing.

Response: At the same time, right now, seven of the top ten companies by market capitalization are tech companies. Seven out of ten are using data that they take from us, without our consent, to create their products. That is part of our labor power: those products are made with our emotional labor, our mental labor. Privacy is a way to reclaim our labor power. I want people to think about those relationships.  And, yeah, I also want people to not get their identities stolen. All of the more concrete problems are still important to me, especially when you think about who is subject to them—it's poor people and elderly people and people who don't have power. But with all of this work, I'm really trying to force a conversation about who controls the internet and what that means for our lives.


Prompt: 1/ When the pandemic first struck the United States, it was not uncommon to hear people compare its virality to the other, online, kind. The numbers climbed impossibly—then inevitably—high. In a nightmare inversion of network effects, the more people who got it, the more deadly it became. In New York City ICUs, patients were dying in the hallways.

Response: Then, as the weeks passed, a different technological metaphor started to seem more apt: the X-ray. The novel coronavirus itself remained, in many ways, inscrutable. But it revealed the brokenness of our systems for providing care. Nursing homes and prisons became deadly zones of infection. Food production plants followed. Doctors and nurses were going to work in garbage bags, while governors, who had been told to compete with one another, bid up the price of PPE that never materialized.  Cities could not dispose of their dead fast enough. They closed schools and daycares indefinitely, without explaining what exactly the working parents who were now also full-time caregivers were supposed to do—and the working parents were the lucky ones. Every Thursday, the Labor Department reported that millions of Americans had applied for unemployment the previous week. That did not count all of the people who could not apply for unemployment because the state websites were crashing and the hold times on their hotlines lasted all day.


Prompt: Did it even make sense to call what you were feeling “anxiety” or “depression,” when there were so many real reasons to worry? Amid so much loss and suffering, what feeling person would not grieve? Nonetheless, social media revealed a steady stream of people who could not be persuaded to care enough for their fellow citizens, or themselves, to wear masks on the bus or to the grocery store. Armed protesters showed up at government buildings to demand a return to business as usual.  2/ The pandemic put technologists, and technology firms, in an ambiguous place. On the one hand, their products have become more essential than ever. Internet traffic is up; cloud services are in high demand. Countless Americans have turned to Amazon and Instacart to shop (or work), and Zoom to take classes or attend religious services (or work). Tech stocks are soaring, even as the real economy falls, and the fights that at least some prominent figures in the industry have picked with journalists and lawmakers reflect a new sense of invulnerability.  At the same time, COVID-19 has exposed points of fragility in the system. If the biggest tech companies are essentially vast engines for making predictions, the pandemic was unforeseen: you could see the breakdown of the machine learning machine. Moreover, this was a crisis of care, and care is precisely what software cannot provide: it is designed to coordinate, and sometimes eliminate, human work. The tech firms could offer gig and warehouse jobs, but they could hardly make up for plummeting employment. They could apply their expertise in digital surveillance to contact tracing, but the populations most at risk—Black and Latinx communities—had the most reason to fear being tracked.   Then the Minneapolis police murdered George Floyd, just two months after the Louisville police murdered Breonna Taylor. Cities across the country erupted. A government that couldn’t be bothered to do the bare minimum to contain the pandemic quickly moved to mobilize battalions of militarized cops. There was no money for PPE, but no shortage of resources available for repression.

Response: Again, the role of technology was ambivalent. On the one hand, smartphones produced the videos of police violence that sparked and spread the mobilizations. Technologists soon found other strategic uses for digital tools—for instance, mapping police movements by listening to scanners. On the other hand, tech posed a constant danger. Drones developed for wars in the Middle East hovered above protests. Your own social media could be used against you—and so could other people’s, as a woman in Philadelphia learned the hard way, arrested after a stranger posted a photo of her with her face covered on Instagram. The networks used to organize and amplify collective action were all too easily weaponized by the state. If you go to a protest, leave your phone at home.  3/ We made this issue in the midst of these intertwined and rapidly unfolding crises. The pieces were written in the midst of the grief and rage of the past months, but also the moments of possibility and hope, which have so often taken the form of people taking care of one another, from street medics washing out pepper-sprayed eyes to militant nurses and teachers organizing for better conditions for patients and students. There was a reason so-called “Momtifa” captured the public eye.  Some of the pieces in these pages deal directly with the most current and urgent aspects of the crises. What they find is that technology is often part of the solution—but only a part. Smartphones can help, but only in tandem with functioning healthcare and state institutions. The clean lines of the tech-laden megahospital suggest a future of frictionless care. But in their shadow, essential workers are saving lives in tents.  Technology alone can’t save us. Often, in fact, it can hurt us. The harms it inflicts aren’t new. The software might have been made recently, but the social relations that software embodies and enacts were made a long time ago. Contemporary digital surveillance emerged from older practices, and obeys old carceral logics. As Sarah T. Hamid explains in these pages, today’s facial-recognition and predictive-policing algorithms belong to a centuries-long lineage of tools for “the control, coercion, capture, and exile of entire categories of people.”


Prompt: Taking care of one another will require dismantling these tools, whether in the form of a laser pointer that scrambles a facial-recognition camera or a legislative ban that outlaws facial-recognition technology. It will also mean constructing alternatives. Moments of social mobilization enliven and expand our political imagination. Among the things that sorely need reimagining is our technology.  4/ The poet Richard Brautigan once imagined “a cybernetic forest,” filled with pines and electronicswhere deer stroll peacefullypast computersas if they were flowerswith spinning blossoms.

Response: This issue explores what a more habitable digital world might look like. There are recovered histories and preliminary experiments, sketches of past and possible schemes for organizing networks differently, and for redressing networked harms.  The issue also asks, Who cares? In one sense, this means: Whose lives are touched by particular technologies, and who participates in their development and design and deployment? But it also means: Who performs the work of looking after and tending to people, and the machines that are integral to the systems that people need? The unglamorous work of maintenance and custodianship, of remembering abandoned knowledge—and programming languages—is what makes it possible for the millions of Americans who have lost their jobs in recent months to receive an unemployment check.  Computers cannot care for us as completely as venture capitalists might like. But we hold out the hope that, with some deep social and technical reconstruction, they can be put into service of creating a more caring world.


Prompt: What is the Carceral Tech Resistance Network? The Carceral Tech Resistance Network (CTRN) is a coalition of organizers who are campaigning against the design and experimentation of technologies by police, prisons, border enforcement, and commercial partnerships. We work to abolish the carceral state and its attendant technologies by building community knowledge and community defense. Our group is made up primarily of femme, Black, immigrant, POC organizers. My own work is embedded in Los Angeles, the Bay Area, and Portland, Oregon, but CTRN has organizers in most West Coast US states.

Response: The network was created out of two primary needs: first, we started to realize that these technologies, often rolled out at a local scale, have afterlives—they travel to other contexts, where communities may have less familiarity with them, or no organized base prepared to confront and dismantle them. So there was a need to knowledge-share and foster mentorship between community organizations. And second, we felt an urgent need to build a different relationship to the cataloging, databasing, and archiving practices that are widely deployed in movement spaces—but which also share a troubled history with the exact same surveillance technologies we are working to dismantle.  How did you first come to work on these issues? I started thinking about these policing techniques during the Ferguson uprisings. I became fascinated by predictive policing, an object that has captured popular and scholarly attention since its inception. Originally, I had aspirations to be an academic; I took the project of techno-criticism seriously. I described this recently as an impulse to “speak these technologies into illegitimacy.”  Things changed once I started to realize that academic research has a long history of being co-opted—even used against itself—by the particular systems that I was studying. Similar to prison industrial complex abolitionists in the 1980s and 1990s, I started to recognize that criticism was not going to be an effective tactic to enact change. So I started to look for other pathways. A couple of years ago, I came out to Los Angeles and began organizing here. And I realized that once you position yourself as an organizer, change becomes possible in a very different way.


Prompt: As an organizer, you’re focused on resisting and dismantling “carceral technologies.” What is a carceral technology? The rebellions in the wake of George Floyd’s murder have largely focused on the physical aspects of police repression, like killings by police officers and brutality towards protesters. But there are also various technologies of police repression that are less physical, and indeed sometimes invisible. Could you give us a sense of what some of those technologies are? Carceral technologies are those that are bound up in the control, coercion, capture, and exile of entire categories of people. CTRN organizers campaign against CCTV, face printing, DNA and biometric databases, acoustic gunshot detection, drones, electronic monitoring, AI and risk profiling algorithms—all of which function as weapons in the hands of law enforcement or prison administration.  When we talk about carceral technology, it’s important to note that we are not just talking about digital technology. We are working with an inheritance that predates digital technology. We are talking about the long history of carceral technologies—lanterns (which Black, mixed-race, and Indigenous folks in the eighteenth century were required to carry if not in the company of a white person), rowdy sheets (colonial crime intelligence and profiling ledgers), sentry boxes (telegraph boxes that gave white, "reputable" citizens a direct line to police power in the early twentieth century), rogue galleries (image galleries of individuals criminalized by police bureaus), calipers (to catalogue biometric data from those in police custody), pin maps (analog "hot spot" mapping techniques used to criminalize entire neighborhoods and communities). And we are talking about a long history of carceral practices, like forced sterilization, medical experimentation in prisons, work homes, and security landscaping (architectural techniques popularized in the service of police surveillance, such as stripping entire neighborhoods of greenery). As abolitionists, we want to dismantle the system that makes those practices possible. And we are organizing in communities that have a long history of fighting those practices, communities that have acquired knowledge about how to fight and build safety against the rollout of experimental carceral programming—whether analog or digital.

Response: Sometimes, the argument against carceral technologies like predictive policing or facial recognition is framed as a privacy issue. I get the sense that you and your fellow organizers in CTRN don’t share that analysis. When these technologies first captured popular attention, the anxiety over surveillance started to take up a lot of space in the room. There was an intentional move by white scholars to push back on these technologies by presenting surveillance as a generalized harm; that is, as something that affected everybody. Because surveillance violated people’s privacy, everybody should care about it—not just racialized populations or communities targeted by the state.  This was a well-intentioned move. But it muted much of what directly impacted communities needed to talk about, what they wanted to build awareness about, and what they wanted to fight against. The privacy framing made it so that the harm enacted by carceral surveillance systems were fixed to a spectrum of intrusion, the one end of which is Target being creepy by spying on its customers, the other end of which is facial recognition–enabled immigration detention.  CTRN is very intentional in how we position our work. We organize against carceral institutions, actors, and systems—not surveillance. The focus on "surveillance" has a depoliticizing effect on the work we do. Organizers campaigning against carceral technologies are not organizing against "intense creepiness." They are organizing against a category of violence—legally sanctioned violence by the carceral state—that has a long history of racialized surveillance, and a short history of digital surveillance. These technologies aren’t just creepy. These technologies don’t just make the subject feel watched, or like they can’t express themselves. These are violent technologies—carceral technologies. So the goal can’t just be to make them a little less intrusive.


Prompt: Who profits from these technologies? How do you see the role of industry in structuring or shaping these kinds of instruments and the social relations they embody? Does it make sense to speak of a “carceral technology industrial complex”? Speaking in terms of industrial complexes is very helpful. After the Ferguson uprisings, there was this particular way in which reform and technology acted together to incentivize certain modes of innovation, like body-worn cameras, that were linked to measures that were supposed to help improve police accountability. Not only did these technologies expand police investigatory and surveillance power, they fundamentally failed to improve the rate of violent encounters between over-policed communities and law enforcement. But this problem space of police reform was incredibly profitable—it was profitable then, and it's profitable now.

Response: I’m reminded of a line from Foucault that Angela Davis uses in her book Are Prisons Obsolete?: “Prison ‘reform’ is virtually contemporary with the prison itself: it constitutes, as it were, its program.” The history of the prison, in other words, is the history of reform. We have to recognize that technological innovation, and the reformism that animates it, is a carceral tactic. It's a means by which these systems have expanded over time. Police have been experimenting with different kinds of technology for hundreds of years. It has offered them a strategy to divert focus from the extreme conditions of violence that they enact on communities, all while amassing vast amounts of resources and connections. Technology is one way that police have historically mobilized academia to work in their favor. It has also helped police forge links with industry.


Prompt: For instance, one early innovation in police technology was adding radios to squad cars. Who built those radios? Motorola. From the 1930s onwards, Motorola radios were installed in police vehicles. That turned out to be a lucrative line of business for Motorola, and it’s no surprise that the company continues to maintain a large communications infrastructure for law enforcement. They have made a lot of money from decades of these public-private partnerships, and so many of the technologies that we enjoy as private consumer goods now were seeded through public funds intended to “fix” policing.

Response: It isn't just that these investments are system-sustaining—it's the very fact that these innovation ventures have never achieved the accountability or reconciliation they promised. They've just made policing deadlier and less accountable. Presumably companies can then market the products they develop to police overseas as well. Can you speak to the international dimension here? Yeah, absolutely. Because American policing and prisons have these entanglements with industry, companies have been able to set up different parts of the United States as test sites for new technologies. Certain cities have become spaces of experimentation. It’s no accident that ShotSpotter, a gunshot detection system, exists in Chicago but is also marketed to Johannesburg—two cities that also share a common history of racial segregation by city planning. Companies start to see and profile these places, these cities, as similar. These markets begin to resemble one another. So a product that's beta-tested in the United States gets sold elsewhere.


Prompt: In fact, many of the technologies that are developed here are being developed with an eye to a global market. I’d go as far as to say predictive policing wasn't even really for the United States, which has a high threshold for things like accountability and transparency. When predictive policing first came to American police departments, the marketing line from industry was that the departments were resource-scarce. Predictive policing, the story went, could help law enforcement agencies save money. That argument is absurd. American police departments are far from resource-scarce. But that argument wasn't for us. That argument was for police departments that really are resource-scarce. It was a sales pitch for police departments in Karachi.

Response: But it’s not just about global markets. It’s also about global contexts. American policing functions as a research site for military innovation—the “green to blue” pipeline is bidirectional. For instance, the National Institute of Justice’s 2009 predictive policing innovation grants (which funded Chicago’s now-deprecated Strategic Subjects List, or “heat list”) seeded the development of risk assessment technologies that served as templates for military detention algorithms in Iraq and Afghanistan, and that helped support counterinsurgency operations. Similarly, social media flagging systems designed for gang policing in urban contexts were studied by DARPA for monitoring ISIS recruitment. The racially hostile relationship that American police have with vulnerablized communities—what are commonly referred to as “low-information environments”—means that those communities can function as isomorphic innovation domains for US imperial contexts. So they test policing tech domestically, in places where the police have a hostile relationship with racialized communities, in order to design war tools for similar communities overseas.


Prompt: This is why building transnational coalitions is so important, especially in this moment in American political history when we’re seeing so much momentum behind diminishing police power. Cities like Portland, Oregon, are enacting prohibitions on the kind of crowd-control armaments their law enforcement are able to use. But the Portland Police Bureau (PPB) has adopted Dhaka, Bangladesh, as a city that it wants to teach how to police effectively. That's where my family's from. Is that where PPB’s tear gas canisters are going to be shipped?  And how are other cities around the world going to get American policing out of their cities? I want to figure out how we can start collaborating with people in Dhaka to organize against the same systems. Confronting a transnational empire will require transnational networks. The US carceral state, through war, development initiatives, and arms and technologies exports, is a transnational phenomenon.

Response: Beyond Bias To return to the question of reform, I wonder if you could speak to the importance of taking an abolitionist framework when organizing against carceral technologies. For example, there are some people who argue that you can reform systems like predictive policing by “debiasing” them, so that they produce fewer racially biased results.


Prompt: Carceral technologies are racist because the institutions that develop and use them are intended to manage populations in a country that has a white supremacist inheritance. These technologies are not incidentally racist. They are racist because they're doing the work of policing—which, in this country, is a racist job. There has been a lot of work devoted to proving that particular algorithms are racially biased. And that's well and good. But there was no question that these algorithms were ever not going to be racist.  What would a not-racist predictive policing program look like? You would have to reimagine prediction. You would have to reimagine policing. You would have to reimagine the history of computation. You would have to reimagine the racial configuration of neighborhoods. You would have to reimagine a lot of things in order to arrive at even the slightest possibility of a not-racist predictive policing system, or a not-racist facial recognition system. So yes, they're racist. There's no question that they're racist. But the reason that they’re racist is because they're used to enact modes of racialized violence.

Response: In recent years, scholarly communities have focused more attention on issues of fairness, accountability, and transparency in machine learning. We’ve also seen a broader conversation emerge around “AI ethics.” What’s your view of these discourses? A lot of these research communities begin with methodologies from STS (Science and Technology Studies) and adjacent fields, where the emphasis is on trying to understand sociotechnical systems. But they often have an inability to apply that analysis to themselves—to interrogate the role that academia and techno-criticism play in the vast sociotechnical assemblage that buttresses the conception, design, and implementation of carceral technologies.  It’s not due to a lack of imagination that these scholarly communities have continuously circled the drain on questions such as the presence of racial bias in particular systems—this is a political arrangement. It’s a structural condition of how the grants that fund their work are allocated, and the relationships they have to industry and to government institutions. For decades, research questions have been staged to these scholarly communities in very particular ways by carceral institutions. There is a given-ness to the problems that these researchers are failing to interrogate. For instance, it's no accident that for years everyone was like, “We need explainable AI,” and then DARPA started handing out millions of dollars worth of grants to develop explainable AI.  Historically, certain academic disciplines have had moments when they decided to reexamine their relationship with the military and police industrial complex. Consider anthropologists refusing to participate in the US military’s human terrain systems in Iraq and Afghanistan, for instance. But the ethics-in-technology communities haven’t had that kind of reckoning yet, where they start to deeply interrogate why they're asking the questions that they're asking. Because these technologies are moving so quickly, I think people in these research communities haven't had a chance to reflect on why they keep asking the questions that they're asking. Where do the questions come from? And why is it that they’re asking the exact same questions that DARPA is asking? And why isn't that entanglement ethically complicated for them?


Prompt: You’re no longer an academic but you’re still very much a researcher. You’re constantly doing research into how particular police programs function, how they were funded, and so on. How does the kind of research that you do now differ from academic research?  Recently, one of the actions that I helped coordinate involved standing in front of City Hall and giving seven hours of testimony on police violence. Scholars might dismiss this sort of thing as being spectacle-driven. And that's fine. But it's also rooted in a desire to create alternative epistemologies. It’s rooted in the recognition that you can't just offer another data visualization, because doing so reinforces a particular way of knowing and a particular entanglement with knowing institutions. So we ask: how do you diversify your ways of knowing? That’s the question. How do you make interruptions into what is broadly accepted as valid knowledge—and make something new? How do you make interventions in the breadth and depth conditions of knowledge? How we know, the way we know, our epistemic practices, are a political decision. They enroll us in technological and research traditions and transform our relationship to both the object of inquiry and the intention behind it. I remember this one moment when CTRN was archiving different policing program grants. We were working in a spreadsheet. There were blank cells in the spreadsheet, and we became obsessed with filling them in. And then after a week we were like, “Why are we doing this? Why are we so obsessed with having a complete spreadsheet?” We started to realize that our way of knowing and our mode of inquiry were being influenced by the nature of the spreadsheet. It wasn't curiosity, or any real need to find the information. It was the structure of the technology.  Knowledge takes a particular shape when you start to use particular mediums. So it’s important to continuously reassess how your knowledge is being shaped because, at the end of the day, if you give into what the technology wants, then your work just becomes police work. Your organizing work just turns into a project to surveil the police, you cultivate a need to satisfy each blank cell, you strive for total information. You start to take on the state’s paranoid affect. You can lose yourself in that.

Response: Beyond trying to build a different relationship to knowledge, another thing that we do that is fundamentally different from academic communities is that we always start with first commitments. That's always the longest conversation of any new organizing formation. What are you committed to? What are you refusing to compromise on? What are you building towards? These are long conversations. When we first created CTRN, it took us more than six months to resolve and find agreement on our commitments.