Prompt: This issue becomes especially pressing when one considers that contemporary software is likely to involve things like machine learning, large datasets, or artificial intelligence—technologies that have shown themselves to be potentially destructive, particularly for minoritized people. The digital theorist Ian Bogost argues that this move-fast-and-break-things approach is precisely why software developers should stop calling themselves “engineers”: engineering, he points out, is a set of disciplines with codes of ethics and recognized commitments to civil society. Agile promises no such loyalty, except to the product under construction.

Response: Agile is good at compartmentalizing features, neatly packaging them into sprints and deliverables. Really, that’s a tendency of software engineering at large—modularity, or “information hiding,” is a critical way for humans to manage systems that are too complex for any one person to grasp. But by turning features into “user stories” on a whiteboard, Agile has the potential to create what Yvonne Lam calls a “chain of deniability”: an assembly line in which no one, at any point, takes full responsibility for what the team has created.  The Agile Manifesto paints an alluring picture of workplace democracy. The problem is, it’s almost always implemented in workplaces devoted to the bottom line, not to workers’ well-being. Sometimes those priorities align; the manifesto makes a strong case that businesses’ products can be strengthened by worker autonomy. But they’re just as likely to conflict, as when a project manager is caught between a promise to a client and the developers’ own priorities.  “There’s a desire to use process as a way to manage ambiguity you can’t control,” said María Matienzo, a software engineer for an academic institution. “Especially in places where you’re seen as being somewhat powerless, whether that’s to the whims of upper management or administration. So you may not be able to influence the strategic direction of a project at a high level, but Agile allows that certain conception of developer free will.” The product manager I spoke to put it more bluntly: “Agile tricks people into thinking they have ownership over their work, but from a labor perspective, they literally do not have ownership, unless they have, like, significant stock options or whatever.”  Software development has never fit neatly into the timelines and metrics to which companies aspire. The sheer complexity of a modern application makes its development sometimes feel as much alchemical as logical. Computers may have emerged as military equipment, but completely subordinating programming work to the priorities of capital has been surprisingly difficult. When software engineering failed to discipline the unwieldiness of development, businesses turned to Agile, which married the autonomy that developers demanded with a single-minded focus on an organization’s goals. That autonomy is limited, however, as developers are increasingly pointing out. When applied in a corporate context, the methods and values that Agile esteems are invariably oriented to the imperatives of the corporation. No matter how flexible the workplace or how casual the meetings, the bottom line has to be the organization’s profits.


Prompt: There’s another angle on Agile, though. Some people I talked to pointed out that Agile has the potential to foster solidarity among workers. If teams truly self-organize, share concerns, and speak openly, perhaps Agile could actually lend itself to worker organization. Maybe management, through Agile, is producing its own gravediggers. Maybe the next crisis of software development will come from the workers themselves.

Response: A previous version of this article incorrectly identified Al Tenhundfeld as a co-author of the Agile Manifesto. The present version has been corrected. Net zero has gone viral. Everyone is announcing their net-zero greenhouse gas emissions targets, from Saudi Arabia to Australia. By the final day of COP26—the annual United Nations Climate Change Conference held in Glasgow in 2021—more than 130 countries had made net-zero pledges of one kind or another, representing about 70 percent of the world’s UN-recognized nations. The private sector has also rushed in: more than 30 percent of the world’s 2,000 biggest public companies have committed to net-zero targets, including Amazon, Walmart, and ExxonMobil.  A global ambition has coalesced. It’s an achievement of sorts. Limiting warming to 1.5°C requires reaching net zero by midcentury, according to the Intergovernmental Panel on Climate Change (IPCC). This doesn’t mean zero emissions; rather, it means that some remaining amount of positive emissions would be canceled out by “negative emissions”—that is, by carbon removals. Negative emissions can be generated by using ecosystems like forests, farms, and oceans to store more carbon, or by using industrial technologies like carbon capture and storage (CCS) to pull carbon from the atmosphere and store it in rock formations. When these negative emissions balance out the positive emissions—when the amount of carbon being taken out of the atmosphere equals the amount of carbon being put into the atmosphere—then net zero is reached.


Prompt: Under such an arrangement, countries are free to continue burning fossil fuels, so long as they offset their emissions. For this reason, many climate advocates have been critical of net zero as a goal. One common critique is that net-zero pledges won’t stop the continued extraction and combustion of fossil fuels. Further, they’re aimed at a future that’s far enough away that present-day leaders won’t be accountable for what happens. “Net zero by 2050. Blah, blah, blah,” Greta Thunberg told a summit of young organizers just prior to COP26.  It’s true that net zero is woefully insufficient. We also need to be talking about immediately phasing out fossil fuel production. But net zero is still a worthwhile transitional goal, because we don’t yet have all the technologies we need at scale for true climate repair. Climate change is a problem of stocks, not flows: we need not only to stop emitting carbon by switching to renewables, but to reduce the existing levels of carbon in our atmosphere. Net zero alone won’t get us there. Still, it gives us a way to buy time while we develop and deploy the technologies required for full decarbonization.

Response: Yet net zero is harder than it looks. The difficulty isn’t just political—compelling countries and companies to make promises and abide by them—but epistemological. At the center of net zero is a knowledge problem: How do we know when we’ve gotten to net zero? Answering this question is surprisingly hard.  There are two main challenges. First, there is immense technical complexity involved in accurately measuring both positive and negative emissions. Take positive emissions: how many are embodied in the manufacture of a car? You could measure how much carbon is produced by a single car factory, but a car has around 30,000 parts. Those parts might be sourced from suppliers around the world, each with their own carbon footprint. Further, the parts use different raw materials, and the extraction and transport of those materials carry emissions of their own. And that’s only one factory; there are some 300,000 car manufacturing facilities in the US alone.


Prompt: Measuring negative emissions presents headaches of its own. For example, there are emergent methods for measuring how much carbon is stored in soil that hinge on spectroscopy, satellite-based sensors, and machine learning. But knowing what’s actually going on in the soil is complex, as conditions can vary even across a single farm. Knowing what’s going on with carbon in the deep ocean, as required for some carbon removal approaches, is even more challenging. Industrial technologies like CCS that store carbon geologically may seem easier to measure than biological systems, but, even then, understanding what happens to carbon that is stored thousands of feet underground isn’t easy.

Response: Even if these difficulties are overcome, however, there is still the problem of carbon deception. This is the second main challenge involved in knowing when we’ve gotten to net zero: the presence of dishonest actors in the system. Think about Volkswagen rigging vehicles to cheat on emissions tests, or gas station chain owner Lev Dermen, who was found guilty of stealing $1 billion from US taxpayers through claiming tax credits for renewable biodiesel that didn’t exist. Behind the office-park facade of net zero lies a seedy hotbed of white-collar crime.


Prompt: The knowability of net zero can’t be taken for granted, then. All those policymakers and executives are making net-zero pledges without a clue for how to see them through. How can these pledges possibly be fulfilled? How can the knowledge problem of net zero be solved? The answer, apparently, is software. Companies large and small have begun to build “platforms” that promise to help organizations meet their net-zero promises. These platforms claim to be able to deliver “decarbonization-as-a-service” through the use of digital technologies that effectively track carbon. They are racing ahead of law and policy and performing de facto governance, creating new proprietary infrastructures for knowing and managing our planet.

Response: If this new regime fails to reliably measure and monitor carbon—and it very well may—that will be bad for the climate. If it succeeds, that may also be bad for the climate, not to mention ecosystems more broadly as well as human communities. But right now, before the new computational systems are locked in, we may have a chance to intervene and shape them for the better.


Prompt: Initial Tree Offering In 2012, Derrick Emsley cofounded Tentree, a Vancouver-based clothing company that plants ten trees for every product sold. That sounds simple enough, but managing the planting projects turned out to be a challenge. “The hardest part was monitoring and verifying the work and claims we were making,” Emsley told The Hill’s Saul Elbein. Confirming that the trees they paid to plant were actually planted required costly in-person trips and lots of managerial overhead—it meant “traveling there, auditing them, making sure those trees were in the ground having an impact,” according to Emsley.

Response: So Tentree started developing software to help streamline the process. That software became the basis of Veritree, a publicly available “planting management platform” unveiled in the fall of 2021. When a company that wants to offset their emissions signs up for Veritree, they get access to a user portal that lets them place orders for new tree plantings and displays metrics on their current tree holdings. These metrics are collected by the planters in the developing countries, who use custom-made “collect devices”—essentially modified smartphones designed to work in internet-limited environments—to take geotagged photographs of the trees. The trees get a unique digital token, and become digital inventory, hosted on the Cardano blockchain. Using a blockchain is supposed to reduce fraud by ensuring that trees are only counted once, so that the same forest can’t be claimed by multiple entities—a well-known problem in the world of carbon credits.  Veritree is in its early days, but it hopes to become “an operating system for the restoration economy,” in Emsley’s words. An “Initial Tree Offering” was used to raise money for a “First Edition Forest,” which features trees in Madagascar, Indonesia, Nepal, Kenya, Senegal, and Haiti. The appeal for corporations hoping to make good on their net-zero pledges is obvious: they can invest in a reliable carbon offset program and obtain a real-time picture of precisely how much carbon is being offset, and share that information with the public.  Veritree is far from the only platform hoping to dominate the net-zero space. A wide range of digital services is being developed by companies large and small. Established “Big Four” accounting firms like KPMG and Deloitte, as well as tech giants like Salesforce, are creating tools for Environmental, Social, and Governance (ESG) accounting that help measure the carbon footprint of firms, among other things. Some companies combine carbon measurement with a portal for purchasing offsets, such as the Atlanta-based startup Cloverly. Still others try to track negative emissions, like Veritree. Agreena, for example, is a Dutch startup that monitors changes in farmers’ fields after they switch to regenerative agriculture, and issues them e-certificates. Companies can sponsor these carbon reductions, and use Agreena’s platform to track them.


Prompt: Atoms into Commodities The creators of these new platforms believe that they can solve the knowledge problem of net zero with software. Given the proliferation of net-zero pledges, this is a profitable problem to solve. But the platforms all approach this problem in a particular way: they turn carbon into a tradable commodity. This points to a broader point: net zero, in its current configuration, is a market-based project. It requires creating a global market where offsets can be freely bought and sold. This market already exists, but it has much room to grow; Mark Carney, the former governor of the Bank of England, says it could be worth $100 billion.  Creating that value, though, hinges on turning lively carbon atoms into a smooth commodity. And that task, in turn, hinges on code. The new platforms aim to improve and expand carbon markets by packaging carbon into a reliable product that can be easily bought and sold online. Their value proposition isn’t just about using digital tools to do superior carbon monitoring and accounting, but about disrupting traditional carbon markets by disintermediating them.

Response: In traditional carbon markets, supply and demand is linked by retail traders who purchase carbon credits from suppliers and bundle them into portfolios, to be sold on to brokers or end buyers. This is an inefficient system, with too many middlemen; it is also rife with fraud. The new platforms want to cut the knot by connecting buyers and sellers—that is, the producers of positive emissions with the producers of negative emissions. Think of Veritree: corporations can purchase offsets by directly sponsoring planting projects in the developing world, without having to navigate a tangle of traders and brokers.


Prompt: The platforms don’t just want to revolutionize existing carbon markets, however. They also want to create new ones. Climate Impact X is a Singapore-based carbon exchange that plans to build a “forest carbon marketplace” that uses remote sensing, artificial intelligence, and blockchain to “open participation to forests that were previously left out of the climate solution.” The idea is that a data-driven approach will lower the barriers of entry for the producers of negative emissions and enable more of them to participate. And, if given the chance, they probably will: there is a lot of money to be made. After languishing for many years, carbon offsets are trading at record highs.

Response: Risk Factors The rise of a decarbonization-as-a-service sector may make it easier to commodify and exchange carbon. But what if it doesn’t actually help address climate change? There is always the risk that the platforms could be algorithmically flawed—that their software isn’t accurately quantifying emissions, whether positive or negative. But there are also deeper risks, ones that can’t be mitigated by tweaks to the code because they’re inherent in a market-based system.


Prompt: First, ask yourself what any of these platforms want. Continued emissions; more exchange. The platform becomes a vested actor. The company is not oriented toward the phaseout of fossil fuels. Rather, it wants to maintain its own life, its own revenue stream. If you were designing a net-zero platform with the goal of working towards full decarbonization, it would be a time-limited project. But that would be incompatible with market imperatives: nobody wants to start a business with an expiration date. This is why the companies running these platforms will have an incentive to encourage a version of net zero with continued residual emissions—not a version of net zero oriented toward a future that would make them obsolete.

Response: More broadly, a market-based system cultivates a tendency toward cheapness that’s hard to square with the costs of carbon removals. Why buy a carbon offset for $50 or $100 a ton when you can buy one for $10 a ton? How is a sustainability manager at a company going to justify that to higher-ups or shareholders? Yet that $10 offset is much less likely to be trustworthy, since proper monitoring and verification costs money. Moreover, the most permanent kind of carbon removals, performed through industrial technologies like CCS (Carbon Capture and Storage), still cost hundreds of dollars per ton. Yes, some platforms will attempt to introduce boutique or premium removals. But no matter how sophisticated the platforms for carbon management become, market logic will inevitably push companies away from these more expensive and more robust offsetting techniques, and toward cheaper and less effective ones.


Prompt: Another issue with a market-based system is that offsets can be purchased by any market actor. But talk to any climate scientist and they’ll tell you that to reach net zero, removals should only be used to compensate for emissions from sectors that are hard to transition to renewables, like aviation or agriculture. In an open market, offsets can be bought up by anyone, including entities that have no future in a post-carbon economy such as fossil fuel companies. That’s bad, because we need to allocate removal capacity to sectors that we want to preserve and whose emissions are truly hard to abate. Platforms can make carbon markets more efficient, but they can’t perform the sorting function needed to prioritize the offsetting of particular activities and industries.

Response: A final problem with a market-based system is that it turns the platforms themselves into black boxes. As profit-seeking enterprises, they must protect their algorithms and data, as otherwise their competitors might gain an advantage. But this opacity obstructs the learning and experimentation process that’s required to combat climate change. We need a broad-based scientific effort to help figure out what works in terms of curbing emissions and removing carbon from the atmosphere. That can’t happen if all the data is locked away on proprietary platforms, hidden from view.


Prompt: We wouldn’t just be entrusting the platforms with data, however. We would also be entrusting them to play a major role in the governance of ecosystems, with significant social consequences. Creating negative emissions is never a neutral, purely technical process—it always involves political choices. For example, communal land title is sometimes seen as a risk to the permanence of carbon credits.  This led to the exclusion of communally held land from one carbon credits project in Cambodia, as research by Sarah Milne and Sango Mahanty has shown. As these calculative practices scale up in digital realms, the repercussions will be turbocharged.  Getting to net zero matters, but how we get there is just as important. Put another way, different attempts to quantify carbon produce different kinds of social relations. Ceding unilateral control over these choices to corporate platforms—letting them decide which kinds of net-zero social relations to make—would be a significant mistake.  Public and Planetary Software is essential for facing the challenge of climate change. We need to build a computational infrastructure for tracking carbon. The impact of humans on ecosystems has been so deep and so complex that digital monitoring and modeling are essential for ecological repair. As Benjamin Bratton writes, “planetary-scale computation” could “contribute to the comprehension, composition, and enforcement of a shared future that is more rich, diverse, and viable.” But right now, we are headed towards a world of proprietary platforms, repeating the same mistakes that we made with the development of the internet.  Shouldn’t knowledge about the Earth’s carbon flows belong to communities and the commons? Shouldn’t the benefits of such data go to the people who are working to remove and sequester carbon—tending the trees, soil, seagrass meadows, and injection wells—and to society more broadly? Shouldn’t the political choices about how to quantify carbon—and, by extension, about what kind of social relations to create in pursuit of net zero—be made democratically, rather than by executives and shareholders?

Response: We need platforms that monitor our world for the sake of collective management of a shared commons—not platforms that measure our world for the sake of profiting from the data created from it, extracting value from the digital layer the same way that value is extracted from the mines, forests, and soils of our physical world. Plundering the earth and then repeating the plunder in the metaverse is dystopia squared.


Prompt: We could imagine platforms that are so much better: better because they actually get us to net zero and address other sustainability and social challenges. The public sector must be central here. It alone can bear the costs of accurate monitoring of both positive and negative emissions—costs that disincentivize companies from buying high-quality carbon offsets, no matter how many advanced digital tools for carbon management emerge.  Public platforms can also help dislodge another obstacle to climate action: community resistance. We will have to build an incredible amount of new transmission lines, solar panels, wind farms, geothermal facilities, factories, mines, and more to pull off a wholesale transformation of our energy system. But when people don’t understand the contours of the problem, or don’t benefit from the solution, they will oppose such initiatives. We’ve seen already that technocratic climate projects without public input are likely to face hostility from local communities. If such communities aren’t brought into the design process, the energy transition is imperiled.  Better platforms are not a panacea for this challenge, but they could help. Imagine a platform for tracking carbon that isn’t just operating quietly in the background, but is highly visible, easy-to-use, open source, and closely integrated with community planning projects. Such platforms could enable people to collaborate on roadmaps for decarbonizing their town or region. They could integrate data around carbon flows and other ecosystem attributes with real-time visualization tools, in order to anticipate different scenarios and deliberate around possible tradeoffs. The platforms could facilitate a more participatory ecology, and thus generate community buy-in for decarbonization measures.

Response: More broadly, public planetary data infrastructures would enable the inhabitants of Earth to know their world. Knowledge about one’s environment should be a basic human right. Imagine a world where you could know what’s in your air, what’s in your drinking water, what species are in the forest near you and how much carbon it’s storing, or what the health of your local lake is like. You could use this information not just to gauge the environmental risks you face, but also to discover which companies are degrading the ecological systems you live in and hold them accountable.


Prompt: This isn’t to suggest that every piece of data needs to be public. As the Indigenous scholar Stephanie Carroll Rainie and her colleagues have explained, open data can be in tension with the rights of Indigenous peoples to govern their own data. In particular, it may cause tensions for communities that continue to experience data extraction under settler-colonial frameworks, and who are working to establish their own frameworks. When it comes to knowing net zero, the important thing is that the computational systems for monitoring emissions and carbon flows are publicly or community-owned, accessible to community members, and democratically governed. What this actually looks like on local, regional, and planetary scales needs to be established through participatory processes that will require time and trust.

Response: Across the Binaries How do we get there? The answer is not fancy. It involves assembling a coalition for public ecological data infrastructures, drawn from several existing communities. There’s the long-standing open source software movement that could participate. There’s also the open data movement in science, and the movement for Indigenous data sovereignty. Environmentalist NGOs are tracking data about emissions, from larger projects like the Environmental Defense Fund’s methane-tracking satellites to databases like the Carbon Disclosure Project. There are a number of people across these fields who might join a movement for open and public planetary data. So why doesn’t this movement exist in a more mainstream way, or even as a common demand at climate protests?  One challenge is the fact that this is an anticipatory mobilization. We’re not mobilizing against something that’s already happened, we’re acting defensively based upon trends that are just beginning to emerge. Proprietary carbon management platforms are still in their infancy; their full impact might not be felt for many years.  Then there’s the cultural divide between the worlds of climate activism and tech activism. Organizations concerned with climate change may be inclined to see the digital as outside their core mission; after all, many people became involved in this space because they loved being outside, not because they wanted to think about algorithms. Moreover, such people may be actively opposed to technological interventions, or understandably dismiss net zero as a narrow, technocratic goal. Meanwhile, people with expertise in algorithmic justice issues might not be tracking developments in the environmental sphere. Their attention is likely devoted to a multitude of other concerns.


Prompt: But each of these communities has critical things to contribute. Climate activists can help us avoid the trap of “platform determinism”—that is, the risk of fetishizing the platforms as mythically powerful actors, instead of centering the choices made by the humans who design the platforms. Such activists also bring expertise in movement building: they know how to put pressure on investors and companies, and how to form relationships with policymakers. On the other hand, those who are working on the politics of data, whether from socialist, decolonial, or Indigenous perspectives, have valuable experience in identifying the problems with data appropriation, access, and use, as well as in creating just data frameworks. And technologists can put their knowledge of quantification and design to work building platforms that are genuinely usable and inspiring.  The knowledge problem of net zero is difficult but not insurmountable. Solving it the right way will require a group effort. We must build data infrastructures that embody multiple ways of knowing and understanding our world, and that help us advance both ecological and social ends, before corporations conquer this space for themselves.

Response: I wonder what’s taken me so long to pop the question, and why this ritual that’s been performed countless times by so many before me bears down on me like I’m the first woman in history to put a knee to the floor and offer the ring and say the words. She’ll say yes. We talked about it. When we lay beside each other, Aluna gains the power to ease the edge around momentous things, and it’s all in how she finds the right tenor, right whisper, the right circles of pressure to trace along the dips of my neck. I’ve brought all sorts of crises to her before sleep. VR recordings of tragedy filmed that very morning, from hundreds of miles away and through the dissociative lens of a drone’s 360 degree camera. Roaming tent cities trudging across the Sahara that siphon power from abandoned solar panel farms. Ocean slums sprawling off the coasts of Italy, Spain, France, sinking as their fate is decided in boardrooms graced with AC. Sea spray is everywhere it shouldn’t be, and scatters the footage into clouds of discordant pixels—that’s when Aluna pauses our replay, blinks our retinas clear. While the bedroom is at its darkest, we shift to face each other and she tells me what she thinks comes next. Never lessening the blows, but making it all feel approachable, which is exactly how she responded when I asked if we might actually spend the rest of our lives together. And she said yes.


Prompt: It feels like I lost my chance. Tonight marks our first week sleeping on the shelter’s temporary foldout beds. We’d considered my SUV but it’s packed tight with all the remaining fragments of our apartment, the things that survived the flood. We gave it a shot, wedging ourselves between piles of clothing in the front seat, but Aluna couldn’t fall asleep. She didn’t complain once. She made constant shifts in her seat through the night, awkwardly reaching for my body only to be thwarted by the packed detritus of our old home.

Response: Video floats at the shelter tent’s apex above all our heads. It plays the breakdown from every angle, accompanied by live commentary. First comes a deep whine, then a spear of pressured mist breaking through Boston’s seawall. Rapid growth from needle thin spikes of water to spiderweb cracks. A network of black spread over concrete, and freeze-frame there.


Prompt: They’re calling it unprecedented. It’s become our country’s favorite word. A guy walks between our cots, offering each of us a refill from his chrome thermos. He looks confused yet determined, young enough to be a Harvard undergrad, coming out to volunteer and help the new climate refugees that huddle in the mandated shelters on his campus. We’re a couple blocks from where the flooding occurred and yet Cambridge is absolutely dry.

Response: “She’s sad again,” Aluna says, like I can’t hear the dog’s cries for myself. It’s an incessant whimper from a few cots down, battling the mutters of a human trying to shut their pet up. If Aluna had her way she’d know the puppy’s name, who is looking out for her, the neighbors beside them who will have to endure her cries. She peers about the tent and watches as much as she can.


Prompt: Since our apartment flooded, my work instruments have been reduced to a loan computer from the company. By the time Aluna and I realized what was happening, our floor swam beneath saltwater. She splayed her arms across the dining table and scooped up a swath of our electronics like a squirrel. Saving what she thought was most important to us, though in real-time, as crisis plays out, that’s so much harder to gauge. You can’t ever be sure of what’s supposed to matter. You grow up with all those educational vids about what to do, how to save yourself, and yet when evacuation sirens blare across the neighborhood all thoughts vacate. Most of us aren’t built for catastrophe.

Response: I unroll my computer, laying it on my lap. My supervisor has given me some leeway with sign-on times for work due to, well, everything—but I still feel uncomfortable catching up on team messages thirty minutes late. I never imagined that being a climate victim would be so embarrassing. Aluna and I lived in a good neighborhood, made decent money, and were much more used to watching disaster rather than being a part of it. After the seawall breach, I didn’t know what to tell my boss except that it happened, that I wouldn’t wait and burn PTO, that I’d log on as always and work admin. Not out of loyalty to the brand, but to a lifestyle I wasn’t prepared to abandon. Besides, Aluna and I need the money. We haven’t touched our savings yet and we wanna keep it that way, so the work pays for the little things that patch our days together—like walking off campus to purchase snacks from the grocery store. Aluna buys cheap things to distribute among the children here. Her way of keeping up routine as a teacher, since most local schools are temporarily closed and she wouldn’t be much help conducting class from a refugee tent regardless.


Prompt: My team’s been talking about the disaster all morning, filling up our text channel with questions and reports on how bad Boston’s been hit. Bickering everywhere, Garrett says, maintenance pointing fingers at the original construction firm, mayor’s scrambling. Good thing is no fingers pointed our way yet but.. Bottom line is the wall should’ve never failed.

Response: Unprecedented, unprecedented. Manager claims he doesn’t have much for me to do right now. Our division at Centra isn’t taking the brunt of the heat, none of the inquiries about damaged property or when the neighborhoods might be “fixed”—as if we can cast a spell and suck the ocean back in place. It’s hard to not glance at other refugees (a word I still find so strange to use here, so near my home) who either tap away on their own devices or blink through screens on their internal retina displays. I wonder which of them are filing the next complaint to the company I work for, and if I might swallow enough pride to do so myself. We all seem the type to be ashamed of this all, how we’re good enough to own multiple devices and line the cots with sets of clothes saved from the water, and yet none of us are second-home rich. Not enough resources to avoid the tents, but just enough to feel bad using them.


Prompt: Admin tasks are the majority of my workload at Centra. Garrett and I are specifically in charge of benefits paperwork for the employees working under our relocation division, a reasonable job since the company keeps that section small. While Centra brands itself in all the climate net corporation tropes—commercials aglow with green fields, wind turbines swaying against sunset—the refugee relocation programs we helm are a side gig. That’s how it is with climate nets, a bit of a trend for corporations eager for a brand cleanup. Shove a random percentage of the budget to securing rent-controlled housing in northern, inland cities shielded from the typical forms of climate catastrophe, then offer up leases to a portion of the newly homeless. Great PR, makes the government happy that we do their work for them, and it provides everyone forced to live in tents a shard of hope.

Response: A couple hours into my work day, Aluna rests a small bag of potato chips on my shoulder and kisses my cheek. She’s fond of a greeting with food involved because I’d probably forget to eat otherwise. As she takes a spot on the bed next to me, Aluna glances at the computer in my lap. “You think Centra’s gonna put us up in a loft or something a little more? Maybe a whole house. They’ve got space out in Colorado or wherever for giving us some land, don’t you think? Full patio, a yard neither of us will know what to do with.” “No thinking for me, love.” I dance my fingertips across the screen. “Only typing.” Aluna grabs the bag of chips before they slide from my shoulder, opening them as she scoots closer. “Liar. You just don’t wanna tell me our spot in the queue, don’t deny it.” Wherever we’re at, it’s probably so far down we shouldn’t think about it. Company gossip has gotten more frantic as it seems that our relocation system has ground to a halt. Centra’s been skimming people off the climate net division and nobody’s left the Cambridge tents with a golden ticket. You’d know if someone got a way out, the excitement and rush they’d fail to hide, but nobody here has escaped.


Prompt: Something we’ve said snared the attention of the man who sleeps a cot away from us. He leans forward, locking eyes with me. His blazer hasn’t come off the whole week and it’s acquired a film of dust. “Hey, I heard ‘queue.’ Can you check my status? Is there a way you can look at that?” With a grimace, I shake my head.

Response: “Sorry, doesn’t work that way. I couldn’t show you the odds if I wanted to. There’s no access to relocation logs from my department.” “Damn. Come on, really?” He hugs himself. “If you want me to pay for it, I will. Name your price. Money’s not a problem, trust me. I’m supposed to be out of here in a few days anyway, I just want to see the queue for a plan B.” “I don’t work relocation, has nothing to do with me. Like I said, I’m sorry—I really would, but there’s nothing I can do. We all gotta wait.” “Everyone’s fucking waiting. That all we’re supposed to do now? Those guys who got flooded in Miami, too, just sitting there.” The man squats, eyes locked on the rubber mat below us, a kindergarten sky blue. “Nobody’s moving anymore. When’s the last time you heard someone get the golden ticket? Who’s being whisked away to safe cities? Because I don’t know anybody.” It’s not that he’s wrong, it’s just that I have nothing to say about it. There’s nothing I could say that would fix this. As the man leaves us with the ghost of his cologne, Aluna gives my hand a brief squeeze, a pulse.


Prompt: And at night, that dog starts whining more. I could turn on my night vision, but instead I lay in the dark with Aluna wedged by me, still dreaming, sharing the cot’s limited real estate. Around me are rustling blankets, murmurs. Pointless, flitting. These limp sounds rise with the dog’s whimpers, a cross-species call and response.

Response: I think I can find a relative peace again. At least one strong enough to drift back asleep, salvage some scraps of rest before the day starts. My eyes are shut against the tent’s collective discomfort. It’s the most solitude I’m capable of carving out for myself, and for the past week it has been enough. Enough against the same sighs, the coughs, the sobs that should’ve never traveled so well across this space.


Prompt: The dog’s whining swoops up an octave. I’ve never heard her so distressed—beyond distressed. A shimmering yelp scraping against my eardrums, forcing me upright. Aluna’s hands scramble up my forearm and feel out my skin. There’s nothing left except for the dog and that howl, a guttural pain. Then she’s done. One more bark, cut short and high. She’s left us in silence undercut by shifting blankets. Our neighbors freeze and look about for the source of disruption, as if pinpointing it all might let us drift back to sleep. As if we won’t all sink back to our cots, turn along the taut stretches of nylon, curl around our partners and ourselves to find a steady beat again, something like the mattress you lost back home under tons of seawater, something that was once warm with you and whoever shared life with you. But it won’t be enough to sleep.

Response: When the morning comes, Aluna returns to bed. I hadn’t realized she left. “She’s okay,” Aluna says, “but shaken. Someone tried to strangle her last night, right here. We think it’s one of us.” Everyone is much too awake. People glare at their neighbors, at the ceiling. In their little movements is stored all the dread that has no legitimate avenue for escape. Our urge for relief isn’t new, though it’s become painfully visible.


Prompt: My work chat is a repeat of yesterday, gossip about whose heads are on the chopping block. Talk of a “rapid retreat” from upper echelons that none of us know how to interpret. I can’t vent to Aluna no matter how much I’d like to, not in front of the other refugees. She drifts back and forth, out into town, buying snacks for the children and a treat for the dog. This is the first time her offers are rejected. From afar, I see parents push her away. Gentle shakes of the head, hands rising up. She’s too far for me to hear how she responds.

Response: *** I suggest we leave at sunset. She doesn’t know how to take that. We’re exchanging messages over internal displays, eating the rations they’ve started handing out for lunch. Aluna would wait and see as she put it, staying in the shelter, till the next disaster forced us to relocate again. This is no home and yet she can barely imagine leaving it. Maybe it’s the proximity to what we lost that keeps her tethered. Cambridge’s parks, rowhouses, and stores provide a familiar urban texture, and when you drift far enough from the tents it succeeds in lulling you back to normality. It’s delusional. I work where the miracles are made, and the only thing Centra is concerned about is laying people off and minimizing damage for the PR fallout of the broken seawall—a tragedy that they refuse to claim as their responsibility, taking all distancing measures available. It will grow clearer over the coming days that there is no help on the way. Not for any of us. We have to leave the city.


Prompt: And where would we go? Aluna asks. She already mentioned us hitting up friends who live near Cambridge, ones who haven’t experienced climate failure outside of the dearth of food lining the shelves. We’ve held off because that shame flares up. None of our community has the bandwidth for that type of support no matter how much we wish they could provide it. They ask us what happened, if we’re alright, how they might help, and we dodge each question enough to allow them an out. They always take it.

Response: We can’t go to them, not now. While Boston as a whole might be running relatively fine, the pockets where they’ve shoved us will soon boil over. I sigh and send Aluna a message. Even though we’re sitting across from each other, I find a way to avoid her eyes. There’s a spot little less than an hour out of town owned by Centra. Part of their data infrastructure, and it’s quiet. We don’t need to be there for long… Just give it time for things to settle over here, a few days at most—the SUV will hold its charge, so we won’t have any problems coming in and out. A mini-retreat? She doesn’t even crack a smile. Right before dinner, we get up and leave. Just like that. There’s nothing for us to bring along. All that’s left of our submerged home is in our SUV, sitting beneath platinum LED streetlights.


Prompt: Autopilot’s enabled for this region, though I’m quick to shut it off. The highway’s riddled with flooding issues now, and I doubt the car could keep up. As we exit the parking lot and get on the road, Aluna and I pass the low, inflated lozenges of the refugee tents, pinned to the soil with near-invisible lines of rope. Nearly biological in their aversion to clean, sharp angles, growing out of the flat campus lawns like massive fungi. Logos adorn the sides, all the entities responsible for erecting this crisis architecture. Centra’s branding appears on the tent as a circle adorned with light rays, a flat design vision of a glowing sun. In the encroaching murk, it can’t be easily defined. The sun seems to waver in the shadows, like a pinned spider flat against the outer wall.

Response: *** There was once a time—probably late ’50s, early ’60s—when vehicular windshield HUDs were an inescapable trend of automotive design. Glowing, transparent skins hemmed glass borders, providing location-specific updates, weather, and navigation tips. By then, every other American had a retina display, though the AR novelty of these car HUDs was pushed as if it were cutting edge. At its core, the overlays are candy-colored, highly restricted web browsers tacked to the front of our vehicles. “Futuristic” was the word that nobody wanted to use, and yet guided every step of the design process. The HUDs exist because, as we near the end of the century, they seem like they should.


Prompt: The glyphs and readouts bordering my windshield begin to disappear. First it’s the weather icon, a cloud eclipsing a crescent moon, winking out. Then all the stats about the car battery. That one’s especially ironic since you’d assume the SUV’s drawing on local, in-vehicle data. Just like all the other visuals drifting away, it warns me of NO INTERNET CONNECTION before vanishing.

Response: We’ve split from I-90 onto a lone road that twists away from the city, away from the gleam of retina-enhanced billboards that outshine tent villages sprawled beneath overpasses. Density gets a lot lighter out here. Autumn foliage flanks us on either side, swimming up to high focus in the titanium pools of our headlights. It’s been almost half an hour since we passed another car.


Prompt: “If you don’t know where we’re going,” Aluna mutters, “you might want to turn back, Imani. GPS is about to go out.” That’s concerning. It’s one of the few visuals remaining on the windshield. I squeeze her thigh. “It’s not far love. I’ll get us there. Trust me, it’s exactly the right place for us to lay low. There’ll be better connection in the barn too, so we can keep track of how things play out in town. When it seems a bit safer we can drive back in.” “Why would the barn have good connection if it’s abandoned?” “These things never go fully dead.” I keep an eye out for our turn. “That said, though, Centra’s moved most of their servers elsewhere, further inland. They think they’re future proofing. All this one’s used for now is cold storage, backups of backups.” I’ve got no doubt it has to do with the sunk-cost fallacy. Decades ago Centra spent millions to get the server farm up and running, and they can’t bear wiping the whole thing out. Funny how risk averse these corporations get in the face of unstable environmental conditions.

Response: “Look,” I say, pointing at the growing lights on the horizon, a fluorescent wash against overcast. “That’s the suburb around the corner from it. Not much longer.” “Good ’cause we got no reception at all now.” Aluna’s stare hits that middle space, out of focus. She’s accessing her retinal screen and judging from the grimace, she’s not liking what she sees.


Prompt: “Imani? This isn’t right. No connection whatsoever, we’re completely in the dark. Is there a dampener or something?” “I’m… not sure. I don’t know why there’d be one active around here.” Rising over the canopy is a gas station sign, blaring out to the night. I can’t help slowing past, getting a closer look at the metal bars meshing the windows and door. They’ve got a drone hovering at the entrance, hardened edges and matte black finish implying combat. The few cars in the parking lot give off the same energy. Tints and acute angles. I’m half-convinced we’ll glimpse an insignia of some sort, hopefully one of a private military firm instead of a paramilitary group, like the ethnostate bands that crawl through the Pacific Northwest.

Response: The homes out here are different too. Most of us try to avoid traveling via highway, so the suburbs have become a rare occurrence in our lives. Last time I passed through was maybe a year and a half ago, and the two-story homes were adorned with the typical New England fanfare of ivy and wrought iron. A handsome weariness. Last time I came through, the internet worked. Now it’s all dark. Bars mesh over every window. It’s a stretch to call this a neighborhood, this collection of fortresses tucked away at the end of winding driveways, peeking through the forest in utter silence. If it were daytime we might even see the antennae they erected to shut down the network. All we’ve got is their absence.


Prompt: “We’re okay,” I say, and Aluna doesn’t respond. I turn down the side street marked with the Centra logo, and we creep down a long gravel path. *** It’s called the barn because it’s a massive, ugly, hulking structure that carves up the forest with gray paneling and harsh floodlights. The electrified gate swings open once it recognizes me and allows us to approach the dead server farm. Maybe not the right word there, dead. The building’s humming with vibrations and light. While there are potholes eating their way across the asphalt, and there’s not a single other car in the area, the place is still on.

Response: Once we drive past the threshold, the car’s HUD returns in a flicker. Our connection piggybacks on Centra’s network. Aluna settles in the passenger seat. “I’m checking the news.” I park near the barn’s main entrance, two glass padlocked doors. Judging from the imagery of server farms I’ve seen back in the day, the aesthetics of these buildings refuse to change. They remain one step abstracted from a warehouse.


Prompt: “We don’t have to stay here for too long,” I say. “Just a night or two. Just to see if things heat up in town or if we’re good.” She nods along, but I’m not sure if it’s enough. This feels right to me, getting out, so I have to find a way to swallow the guilt. The last thing Aluna wants is to be far from the community, disengaged with helping in all those small ways. I don’t operate like that. Not to say I don’t care, but when I exchange snacks or provide some clothing, I only feel dread. I’m never doing enough. Aluna might find fulfillment in those acts, or she might hide her fear better than I do. It’s not something I’ve had the urge to figure out until now.

Response: We lean our seats back as far as they go, crushing the remains of our apartment in the back. Each readjustment brings another plastic creak. “Look,” Aluna says, and shares video of Southie. More drone footage, smooth like the camera’s on rails in the sky. The water has already started to lessen. All of our neighborhood’s detritus has mixed in the flood to make the ground invisible. Frothing, dark water, yet so low, getting lower… It feels odd to think of it this way, but the destruction feels pathetic. A quilt drifts from what was once a window. It’s matted with glass and other things, objects I can’t identify no matter how close the zoom gets. Whatever’s been abandoned wades through ruins that we want more than anything to return to.


Prompt: I blink away the footage and turn to face Aluna. “What do you think?” And at first, it seems she might respond as she used to when we slept in a bed together. Aluna opens her mouth and hesitates. Her hand reaches across the cup holders and up my arm, to my collarbone, and finally the dips of my neck.

Response: “I think we should learn how to be lost. It’s okay, or it’ll have to be. Know what I mean?” “Want an honest answer?” She nods. I catch her hand in my own, feel where the ring should be. I should’ve asked her already. I bought her a ring, and I don’t know where it might be buried. It could be in this car with us or tumbling down a sewer drain.


Prompt: “We shouldn’t be fucked over so fast, Aluna. It’s not supposed to all end so quickly. I always thought there’d be a… I don’t know, a warning? A heads up of some sort. Like, yes, the end’s coming, as it’s been since forever, but here’s a week head start. Or even a day. I don’t know how we wake up and face all of it gone, and whatever. That’s it. We keep going.” “I mean, you just said it. It’s always been coming. The warning call’s blared for decades, and we watched it every night. We just thought we’d be lucky.” We can’t live off luck. One day soon, we’ll have to find a path forward. It’s not something I can think of now. Now, all I see is Aluna, her cheekbones carved through the data center’s security floodlights. For an hour more, we stay up and watch more footage from back home. The tents are not faring well tonight—actual skirmishes popping up, people who never imagined fighting for survival forced to fend for any resources they can get a handle on. I wish a wake up call didn’t involve people getting hurt.

Response: By the time we start drifting off, we agree it’s not as bad as it could’ve been. Even from the scattered news footage, it’s clear there are people like Aluna among the tents. Lots of little things resulting in countless points of de-escalation. Though we’ll need more to recreate our homes, it’s a start. I think, next morning, we’ll head back.


Prompt: *** I check the back while Aluna’s fast asleep. The trunk, too. Moving as quietly as possible through years and years of our shit, all of it bursting at the seams and threatening to fall across the parking lot. Every exhale is a puff of mist, and I blink to clear my eyes. Journals, clothes, random pieces of silverware, actual physical books, toothpaste, blankets—I bring one out, drape it over Aluna’s body in the passenger seat, then go back to my search.

Response: I find it wedged on the trunk floor, beneath the corner of a box. It must’ve fallen out of the case. Unmarred, a thin silver ring. After scooting back in the driver’s seat, I hover with the ring tucked in my palm. It grows warm there, in the safety of my hand. I don’t ever want to let it go until Aluna’s ready to take it. So I’ll wait till next morning, and see what she says.


Prompt: Rationalization is a form of compression that lays a grid over our world and attempts to remake it to fit its shape. The goal of rational thought is to break down a complex and infinite reality into small pieces and reconstitute it in a logical system. In computing, rationalization is the process by which phenomena like actions, identity, and emotions are split, stripped, reduced, standardized, and otherwise converted into computable data and mapped within machines.  It is a process of rationalization that allows a company like DoorDash to use computational algorithms to determine “optimal” delivery speeds, and then to discipline its workers for not matching those predetermined outcomes. To believe in the efficacy and reliability of such a system, we must first accept that DoorDash is able to measure and model an intricately layered series of complex relationships—including traffic patterns, consumer desires, worker behaviors, prices, and more—and is then able to draw actionable predictions from all that information. To accept this requires a faith that each part in the complex system is knowable, quantifiable, and fixed. This is the ideology of rationality at work.

Response: But the world is not rational! The world is, in fact, irrational! It is chaotic, expansive, interrelational, and incalculable. Machines, in particular, are far too rigid in their logic and far too limited in their capacity to meaningfully capture the world. Yet we continue to grant them ever greater power. Across the public and private sector, computer-aided systems of management premised on transactional relationships and the supposed ability to optimize outcomes are being used to guide our interactions. As DoorDash workers will be the first to tell you, these systems shape behavior, remaking the activities and phenomena they are meant to model while radiating innumerable harms—from incentivizing unsafe driving speeds to suppressing wages—as a result.  To resist this reconfiguration and mitigate these harms, we must reject rationality and embrace a fundamentally irrational worldview. If rationality says the world is measurable, knowable, optimizable, and automatible, an embrace of the irrational is a rejection of that ideology. Embracing irrationality allows for multiple interpretations, contradiction, inexplicability. It empowers us to reclaim the act of meaning-making as a collaborative, social exercise as opposed to one that can be automated and forgotten. Ultimately, a program of irrationality requires that we harness the power of our machines through a form of democratic oversight that acknowledges the false promise of rational management and insists that, in the absence of certainty, we must work together to organize society. Irrationality celebrates doubt, because only if the future is unknown will it be ours to build.  Rational Data from an Irrational World Rationalization—the process of abstraction in the service of computational reasoning—has long been a feature of the sciences, math, and philosophy. Of course, tools of theoretical inquiry are often put to practical use by those in power. Beginning in the late nineteenth and early twentieth century, labor processes were mapped out rationally to the great benefit of early industrialists. In the postwar period, cyberneticists and game theorists, many employed by the US military, theorized that they could go beyond simple numerical equations or discrete production processes and rationally describe much more complex phenomena using newly developed computing machines.


Prompt: Around the end of World War II, the first general-purpose electronic computers were introduced. The data being entered into these machines was numerical, it was subjected to mechanically coded mathematical formulae, and the output was a solved equation. An amazing innovation, and one that—provided the inputs were entered accurately, and the machine operations properly encoded—returned an accurate and reliable result. An increased focus on feedback soon enabled a process known as “machine learning” through neural networks—a technique that has been revived in the last decade to propel a new AI boom, driven by breakthroughs in computer vision and natural language processing.

Response: Machine learning sorts through vast amounts of chaotic data and, using adaptive algorithms, closes in on specific arrangements of information while excluding other possible interpretations. But, in order for any computation to occur, a process of rationalization must first create machine-readable datasets. Real-world phenomena must be “datafied” by sorting it into categories and assigning fixed values.  Take, for example, most image recognition software. Whether the goal is identifying handwriting or enemy combatants, a training set of data made up of digital images—themselves encoded arrangements of pixels—is typically created. This initial process of digital image capture is a form of reduction and compression; think of the difference between the sunset you experience and what that same sunset looks like when it is posted to Instagram. This mathematical translation is necessary so the machines can “see,” or, more accurately, “read” the images.  But for the purposes of this kind of machine learning, further rationalization must occur to make the data usable. The digital image is identified and labeled by human operators. Maybe it is a set of handwriting examples of the numeral two, or drone images from a battlefield. Either way, someone, often an underpaid crowdworker on a platform like Amazon Mechanical Turk, decides what is meaningful within the images—what the images represent—so that the algorithms have a target to aim for.  The set of labeled images is fed into software tasked with finding patterns within it. First, borders are identified in the encoded arrangement of pixels. Then larger shapes are identified. An operator observes the results and adjusts parameters to guide the system towards an optimal output. Is that a 2? Is that an enemy combatant or a civilian?  Once this output has been deemed acceptable, the system is fed new, unlabeled images and asked to identify them. This new data, along with feedback on the functional accuracy of its initial output—“yes, that is a 2”—is used to further fine-tune the algorithm, the optimization of which is largely automated. This basic process applies to most machine learning systems: rationalized data is fed in, and through association, feedback, and refinement, the machine “learns” to provide better results.


Prompt: But rational data is an unstable foundation from which to learn. Those initial stages in the machine-learning process when phenomena are translated into code, when the irrational is rationalized and the real world is datafied, demand close scrutiny. And as the phenomena we are asking the software to interpret become more complex—as these systems are tasked with going from recognizing that an image contains a face to recognizing a specific face, to recognizing the emotion on that face, to determining what actions might result from someone in a certain emotional state—the more skeptical we should be of any supposed insights that are generated.  The process of translating the world into code is reductive. There is a similar reduction in the labeling of data into certain categories—there will never be sufficient categories available to represent all possibilities. In an infinitely complex and constantly shifting world, any one-to-one representation is impossible. And anything that is lost in that original training data will be invisible to machine learning systems that are built upon it.  Far from being a neutral process, the creation of training data is fundamentally social and subjective. It requires human actors to determine the available categories and label the data accordingly. The attendant assumptions, biases, and distinctions made by these human actors are necessary to create “rational” data, and once encoded they define the possibilities and limitations of what machine learning systems can “learn.”  To be clear, all forms of knowledge-making are social and subjective, not just machine learning. The difference is that other ways of making sense of the world acknowledge their own fallibility. For instance, in academia, disciplines have developed various techniques for vetting new information, such as peer review. The issues are not always resolved, but there are processes that help create meaning collectively.  The Irrational Program The making of meaning cannot be automated because an irrational world cannot be coded rationally. Machine learning systems, with their immense computational power, can surface novel arrangements of information and offer new forms of perception. But any claims to objectivity made on behalf of these systems should be disregarded outright.

Response: Moreover, these systems are engaged in actively shaping society to fit the models they create. When the options for human activity are reduced to a set of “optimal” choices made available through a machine-generated recommendation, other courses of action—and thus other possible future outcomes—are eliminated. We cannot allow this reduction to put limitations on the world in which we live. Instead, if these systems are to be salvaged, we have a responsibility to relentlessly interrogate who and what constitutes “data,” how it is made, what patterns we seek within it, and what we do with the insights that are surfaced. These questions must be put to the widest public forums available, and the decisions about how to respond must be made democratically. Then those questions must be asked again and again.  The process of rationalization, and the technology it enables, are social in origin and have a social impact once deployed. Ultimately, we must embrace their collective nature and respond collectively. This means organizing the workers at the point of rationalization and organizing the subjects of datafication to resist until their demands for input into the development of these systems is met. We make technological systems as they make us, and we can remake or unmake them. When we recognize our role in the co-creation of technological systems, and take collective control over that process, who knows what innovations may result? I walk slower these days. Walking used to be about where I was going next: moving fast and hard through space. I paid less attention to the here and now; here was en route to my tomorrow. My old pace matched my lifestyle—stomping through a long Bay Area commute and a calendar packed with business travel. A life filled with too much working.  After my spinal cord injury, that all changed. Now, I walk slower. My engagement with the world is different. I no longer just move through space, I spend time there. I spend time here, now. I use a cane to steady myself. My cane is not only an assistive device, it is a symbolic one. My cane signals to others: the way I am interacting with this space is different, and beware, the way you will interact with me is different, too. Disability has redefined my relationship to many things. Not only with spaces, as I describe, but also with time. I now meet the world differently, with a different body, and this body moves, thinks, and acts at a different pace. This is crip time.


Prompt: “Crip time” describes the alternative relationship many disabled people experience with time. As Ellen Samuels, a disability studies scholar, puts it: “Crip time is time travel.” There are many layers to crip time—from the simple fact that many of us walk or roll through space slowly, to the altered trajectories that unfold over the course of a lifetime. Crip time forces a confrontation with the messy realities of the non-normative, all the ways that our temporal experiences fall outside our expectations. Instead of looking to the norm—the averages, patterns, and trends that fill data-dripping techspeak—crip time provokes us to wonder: What about the peculiar? What about the ad hoc, the irregular, the one-off? What about the unique messiness of the here-and-now? Because I now walk slower than before, I notice much more: uneven and poorly maintained sidewalks, worn-out or missing “six feet” social-distancing floor stickers, the monstrosity of stairs. I notice when places are not built for people like me. But I also notice everyday beauty. A slower pace allows me to see the craft tangled in the mundane. I notice the playful swooping geometry of songbirds and the peppery glitter of tree shadows as they jump across the path in front of me. I have to take breaks and let my body rest. I must care for myself in ways I never did before, in ways I was never taught to. Will I be able to find something sturdy to sit awhile and rest? What will I do if I can’t? Exiting the Flow Where does rest figure in our everyday experiences with technology? I work as a user experience (UX) researcher. As UX professionals, we learn about the psychology of response times and how they relate to human thresholds around human-computer interactions. A machine can move too fast for a person to comprehend, which is not ideal. There is a sweet spot, according to industry expert Jakob Nielsen, to aim for: somewhere between 0.1 and 1.0 seconds is ideal for the system to stay in line with a person’s flow of thought. Ten seconds is the outer limit that a user will wait before getting bored or frustrated in waiting for a system response.

Response: But why do we get bored or frustrated? In our cult to the gods of relentless busyness, continuous digital activity feels holy. Corporate life pressures us to act quickly. We have become accustomed to high-speed internet connectivity and vast computation processing, all of it occurring with near-simultaneity as our fingers release a tap. We scroll, and scroll, and scroll—our feeds feel endless and our clicks take us seamlessly from one task to the next.  This feeling of being “in the zone” is a psychological state called flow, and has been a design concern since the early days of personal computing in the 1980s and 1990s. Then, the concerns were largely focused on designing workplace experiences that integrated PCs with analog-driven workflows in ways that didn’t create too much friction or drag, the opposite of flow.  Living in crip time means that flow feels rare. Since my spinal cord injury, I no longer rally for a packed work calendar, where meetings bleed together after hours of social interactions over video teleconferencing. Now, I must be strategic. Crip time means I attend some meetings with my camera on, and some with audio only. Others I watch later as a recording. An audio-only meeting likely means I am attending the meeting while pacing, kneeling, or laying down, alternating positions to help relieve the spinal cord pressure and nerve pain that builds up over the course of the day. Watching recordings of meetings later creates lots of drag, as I move between recording files, PowerPoint decks, meeting chats, and relevant emails to make sense after the fact.  But this drag can be meaningful in its own way, too. Just as my slowed-down walking means I notice more in the world around me, my crip meeting practice provides me space where I am able to notice differently. Now that I live in crip time, I am always on the hunt for the red buttons and icons of recordkeeping—digital parallels to the benches and seats I watch for now when I walk. Audio-only meetings mean that I am more comfortable physically—and thus can concentrate more freely on the meeting. I take notes and jam into the conversation when I need to. I focus on the dialogue rather than my appearance via webcam. Watching recordings after the fact, I can approach the meeting well-rested and in a comfortable setting. With the ability to hit pause, I am able to wonder, consider, jot down questions. These are all things that are difficult in the flurry of marathon meetings.


Prompt: It’s not that my crip meeting practice appropriates a kind of alternative productivity tool. Instead, my experiences of disability and of crip time have compelled me to wonder if “flow” is really the metric against which all our journeys of work and technology should be judged. As we enter 2022, year three of the Covid-19 pandemic, this question seems particularly acute. Those of us who are able to work from home have spent month after month booting up, logging on, checking our schedule, and loading our inbox each morning. We are expected to seamlessly enter the flow of remote work at super-highway speed, reproducing pre-pandemic levels of productivity and output, even as we continue to face a world in crisis.

Response: The lens of disability studies and the experiences of the disabled offer us a different way of thinking about our experience of time. In Feminist, Queer, and Crip, Alison Kafer tells us: “Crip time is flex time not just expanded but exploded; it requires reimagining our notions of what can and should happen in time, or recognizing how expectations of ‘how long things take’ are based on very particular minds and bodies… Rather than bend disabled bodies and minds to meet the clock, crip time bends the clock to meet disabled bodies and minds.” Just as I have come to learn from my own disabled body my new walking pace, the time it takes my body to finish the chores of independent living, I also learn how long it takes my body to bring an article like this together or to finish an important deliverable at work. Where before I let pressures of various sorts build up to optimize my output drive overwork, I now live in crip time. Things get done, just at a different pace. Doing is re-imagined and re-configured, a process driven by my body’s differing, situated abilities, instead of some trend, pattern, or prediction. Achievement is still possible—and I do still achieve—just on my body’s own terms. What are your body’s terms? Satellite imagery has woven itself into the fabric of the internet. We recognize these crisp, high-definition, bird’s-eye-view images most commonly from Google Earth—but we employ them in much more besides: from reporting on stuck shipping containers to getting directions to a friend’s house, to tracking forest fires in real time and scrolling through real estate listings. Given their ever-widening range of commercial, consumer, and civic uses, it won’t surprise most people to hear that the industry that produces them (also known as Earth Observation, or EO) is growing at an exponential rate, and is only expected to expand further in the coming years.


Prompt: Yet despite the prominence of satellite imagery in the geographical imagination of the internet, the imperatives of the industry are much less clear. The corporations that produce them are much less well known, and the military interests that back them remain as murky as ever. The highly visible commercial side of the industry is still deeply intertwined with its classified counterpart, and two companies, Maxar and Planet, have emerged to dominate the industry—supporting civilian functions with one hand, while supplying US defense needs with the other.  Indeed, the ubiquity of commercial satellite imagery gives nearly anyone godlike powers of reconnaissance and surveillance not that far removed from those enjoyed by militaries and intelligence agencies—a fact that causes no small amount of anxiety within the Pentagon. The pervasiveness and power of their imagery compels us to ask: Where do they come from? And how are they being put to use? Launching the Industry The story of satellite imagery begins with military surveillance. The CORONA satellite program was launched in secret by the NRO (the National Reconnaissance Office, whose existence wasn’t declassified until the 1990s) in response to the USSR’s Sputnik-1 in 1958. CORONA ultimately put over 144 satellites into orbit over twelve years. Satellites were soon found to be useful for surveying purposes as well: the oil, gas, and mining industries, as well as climate researchers could make use of satellite imagery in their work. The academic, commercial, and national-security interest in satellite imagery of natural resources culminated in the launch of the Earth Resources Technology Satellite, now called Landsat 1, in 1972. Landsat remains the longest-running satellite imagery program to date.

Response: Following the end of the Cold War in 1992, private companies were permitted to enter the satellite business in the United States, kickstarting the industry that we know today. But the newfangled EO industry never drifted far from its origins in the military-industrial complex. In 1994, defense contractor Lockheed Martin was granted a license to sell commercial satellite high-resolution imagery. In 1995, the first commercial imaging satellite, OrbView-1, was launched by Orbital Sciences Corporation, in partnership with NASA. Soon afterwards, WorldView Imaging Corporation (later called DigitalGlobe) was given the first contract to build and operate a commercial satellite system. As the industry grew during the 2000s, it created new markets and many of the companies we know today. In 2004, Google acquired three geospatial companies that formed the basis for Google Maps. (One of them, Keyhole, had received funding from the CIA.) As the industry has expanded, the number of satellites orbiting the planet has grown: from one in 1958 to over 3,300 in 2020.


Prompt: Despite the staggering number of satellites, the business of capturing satellite imagery is dominated by a small number of major players. DigitalGlobe and Orbital Sciences (by then called GeoEye) merged in 2013; the resulting corporation, Maxar Technologies, became the largest satellite imagery company in the United States—a monopoly, in effect. Planet, founded by ex-NASA scientists in 2010, initiated a new chapter for the industry, launching small-scale micro satellites that could capture imagery of the entire planet at least once a day. The miniature satellites themselves are called “doves,” ironic given their recently renewed contract with the NRO in late 2021. Planet, which went public on the New York Stock Exchange just weeks later in 2021, has been hailed as an industry disruptor for years. Maxar and Planet have emerged as twin giants of the industry: one supplies high resolution, the other, speed.  The granularity of satellite imagery can be divided into three categories: low resolution (over 60m/pixel), medium resolution (10–30m/pixel), and high resolution (30cm–5m/pixel). The precise resolution of NRO satellites remains classified but continues to occupy the highest rung, while public research satellites like Landsat 1 capture the medium to low resolution needed for climate science. Historically, commercial satellites have been restricted to selling imagery up to 50cm/pixels (lowered to 40cm in 2014, then 30cm in 2015) despite their capacity to produce much higher resolution, as is the case with Maxar’s satellites, in particular. While Planet satellites aren’t capable of capturing the same sort of resolution (they max out at 50cm/pixel), the sheer number of micro-satellites they have launched means that Planet has the largest constellation of satellites ever assembled. As of 2022, Planet’s doves can capture and transmit imagery at least once a day, and this “guaranteed collection” business model is, in part, responsible for their recent IPO.  In other words, if Landsat imagery can capture a retreating glacier, Maxar can capture every crack—and Planet can capture its movement day-in, day-out. The NRO satellites? Who knows what they can do.

Response: The GEOINT Singularity Thanks to their size and technological advantages, Maxar and Planet have become the go-to suppliers of satellite imagery used to document everything from tornado damage to the 2021–2022 military actions in Ukraine. According to its own statements, Maxar “provides 90 percent of the foundational geospatial intelligence used by the US government,” and was initially the sole supplier of imagery to the US government. Since 2019, the NRO has subscribed to Planet’s services (a contract that was recently expanded). Meanwhile, other companies like Satellogic (which recently partnered with Palantir in early 2022) and BlackSky (contracted to the NRO and NASA) have emerged with similar capabilities.


Prompt: At the same time, the growth of “open source intelligence” (OSINT) and open data initiatives has enabled satellite imagery to be co-opted as both an investigative tool and public good, sometimes even used against the very states and corporations that released their imagery in the first place. Organizations like Amnesty International and Forensic Architecture have used satellite imagery to document human rights abuses, while Bellingcat has done the same for US military bases (both using Planet imagery). OpenStreetMap, an open data project, uses Maxar imagery to create a crowdsourced map of the world (often called the “Wikipedia of maps”). Such civic use of satellite imagery has shifted public access as well, as when Maxar released high-resolution imagery of Israel-Palestine in 2021—imagery that has been historically blurred and kept classified due to US government restrictions.  This fact is not lost on US intelligence professionals, many of whom fear a looming “GEOINT singularity,” in which public geospatial knowledge may equal that which is known by “experts.” But even the Pentagon understands that OSINT is here to stay—and may even be a resource for the military to exploit, as a DoD strategy report from August 2021 suggests. Similarly, the National Geospatial Intelligence (NGI) agency has emphasized the role of private companies in the geospatial intelligence community, and more such government-commercial partnerships are expected to develop in the coming years.  For all its pervasiveness online, the increased production of satellite imagery by companies like Maxar and Planet is not necessarily leading to an increased commercial demand to use it. From a business perspective, the thousands of satellites circling overhead are producing an excess of supply, and demand is still dominated by defense agencies.  Indeed, given how much more advanced NRO satellites must be compared to the commercial industry as a whole (something we have the right to assume, given their classified status—the NRO, for instance, was able to unexpectedly donate two high-resolution telescopes of the same quality as Hubble to NASA), it’s worth asking why the government continues to acquire lower-resolution commercial imagery in the first place. The recent declassification of “Sentient,” an “omnivorous analysis tool” being developed by the NRO, points to their need for vast quantities of satellite imagery to train AI-driven imagery analyses. Could the exigencies of AI be driving the DoD’s continuing support of the industry? On the other hand, buying up imagery could also be a means of controlling the flow of information, pushing the images into the wrong (or right) hands. Could their support be a means of ensuring that satellite imagery is steered in the direction of US military interests?

Response: In either case, we may not ever know for sure—at least not in the near future. But the questions are a reminder that the commercial satellite imagery industry remains impossible to separate from the military applications from which it arose. They are a reminder that the “supply chain” of satellite imagery—the set of companies and institutions that bring the images from above the atmosphere to the apps on our phones—is not necessarily as straightforward as the notion of “surveillance capitalism” might make it seem. In the meantime, this convoluted mix of civil, military, and commercial actors will continue to fill our skies—and our screens—with satellite imagery.


Prompt: Adapted from Redacted (Taller California, 2021) San Diego is one of the most surveilled places in the United States. Located on the border with Mexico, America’s Finest City is host to one of the largest US Navy bases and a wide array of government agencies that see technology as the key to better managing public infrastructure, tracking the movements of people, and solving crimes. Hidden behind a veil of public safety and national security, the spyware is often invisible to the public.

Response: For years, officials have been rolling out technologies that they don’t totally understand and with little to no meaningful oversight, turning San Diego into a laboratory for the rest of the country. The residents here did not consent to this development, let alone vote on it—a reality that pits the interests of public planning and law enforcement against the civil liberties and civil rights of everyone else.


Prompt: It’s also common to find that technological experimentation in San Diego serves the interests of private companies with something to sell. General Atomics is one of these companies. In 2020, the defense contractor decided to repurpose its Predator and Reaper drones as the benign-sounding SkyGuardian and SeaGuardian. But before General Atomics could test out one of its drones above San Diego, it needed permission from the Federal Aviation Administration (FAA). The airspace above the city is a highly restricted place, where unmanned aircraft cannot typically fly.

Response: The San Diego test flight was supposed to demonstrate that the new drone, the SkyGuardian—weighing up to 12,500 pounds, with a wingspan of seventy-nine feet—could safely travel over a dense metro area while surveilling infrastructure and the natural landscape. San Diego and its people would be props in General Atomics’ killer demo.


Prompt: The company described the drone as a “persistent eye in the sky.” It was an unprecedented project that had the potential to open the airways above major US cities to new forms of surveillance. How were regulators evaluating the technology? Had there been any external influence—from, say, the Pentagon or the White House—to force the project through? These were pressing questions, especially because a similar drone from US Customs and Border Protection had experienced mechanical failure and crashed in the waters outside the city in 2014.

Response: So, in late March 2020, with the test flight about to take place any day, a journalist at the nonprofit news organization Voice of San Diego requested all public records related to the test flight from the FAA, including communications with the defense contractor. Complying with the request wasn’t easy. The FAA has five divisions spread across the country. By design, the agency’s public records response is decentralized. Getting the SkyGuardian off the ground required the work of three different units, each of which needed to produce—and redact—the records in its possession. Voice of San Diego filed a lawsuit to speed up the process and, in September 2020, a judge ordered the FAA to hurry up or face penalties. The pressure was on. The agency had six weeks.


Prompt: The Minimum Amount of Redactions Two months after the original request was filed—well past FOIA’s legal deadline of twenty business days—Rick Perez got the assignment in the FAA’s air certification branch. Perez had been with the FAA since 2011, and his staff was also in the middle of processing more than sixty requests for huge volumes of records related to the certification of the Boeing 737 MAX, two of which had crashed in 2018 and 2019, killing a total of 346 people. Perez’s branch consisted of three federal employees and four contractors. The SkyGuardian was just a blip on their radar.

Response: Perez’s staff consulted with other experts in the agency, ran an initial query with keywords, and then set about reading through the more than 2,500 pages they had identified. During their line-by-line reviews, it became clear that other organizations might have a stake—and a legal claim—to withhold information about the SkyGuardian, not just the FAA.


Prompt: NASA, for instance, had been partnering with General Atomics on the test flight. Both organizations needed to be consulted. Both would drag their feet. And both would then turn around and make cases to the FAA in private that certain documents and communications ought to be treated as confidential. General Atomics argued that some of the information contained in the records was protected by the US Arms Export Control Act, which deals with the sale of weapons overseas. This by itself was revealing: the test flight was not just about showing local officials the ways in which they could monitor infrastructure from above. The test flight was intended as a marketing ploy for international buyers.

Response: For this reason, Perez discovered, the Department of Defense also needed to weigh in. That slowed the process down even further. In October 2020, he provided the court with an update, arguing for more time—but promised to release everything in his possession “with the minimum amount of redactions.” Here’s a taste of what he produced:  Still, there were some revelations visible between the blacked-out lines. What the FAA released showed that regulators did not believe the drone could fly safely above so many people. Regulators had demanded the company use a “chase plane,” manned with a pilot who could monitor the drone in real-time for any problems. Instead of complying with the request—which might have given the international buyers doubts about the technology’s true capabilities—the company rerouted the flight path and pushed the demo into the desert.


Prompt: But as it turns out, different units within the FAA had similar records in their possession and redacted them in different ways. The FAA wound up producing the same emails in redacted and unredacted forms, inadvertently revealing how subjective the process really is. What to keep and what to omit appeared to be dependent on the momentary feelings and fleeting judgments of whoever was doing the redactions.

Response: The email conversations show FAA employees casting doubt on General Atomics’ claim that their technology is safe. In one email, an FAA employee notes that the company is “worried about getting an approval” and that time will run out before the permit process can be completed because, “as usual, they have diplomats from the military attending and want to demonstrate the capability.” Secrecy is the way in which government agencies reveal their mistrust of the people. The cloak is needed, you’ll often hear officials say, to keep everyone safe. But safe from what? Or better yet, from whom? Secrecy breeds its own kind of distress, encouraging a fear of the unknown that justifies new levels of authority in a slow-moving but perpetual crisis.  Secrecy and surveillance are two sides of the same coin. Both stem from an attitude that the people atop our institutions know better than the rest of us how to govern and structure society. Both engender mistrust and inhibit collective action. They engender mistrust by encouraging us to outsource responsibility for safety. This inhibits collective action, not only by chilling our speech and association but by ceding authority to institutions we mostly do not participate in.  Do It Yourself Why would I, of all people, want to seek a public record? It could be to learn about an issue that affects you or your community. It could be to find more bulletproof evidence of something you know or suspect that will help with your advocacy work. It could be an entry point into the workings of politics or profit by finding the traces left behind by the companies that interact with the government.	 How do I get started? Don’t be intimidated. We had no idea what we were doing when we got started either. No one is born with this knowledge.


Prompt: Explore the public records universe to get a sense of the mechanics. Public records are informational arcana produced through the rituals of politicians, functionaries, and bureaucrats. It is hard to know what to ask for if you don’t have a sense of how they organize their world and their work within it.  Check online to see if the agency you’re targeting has an open data portal, then start by trawling for topics that you’re interested in. Some public agencies and cities, including Los Angeles, New York City, and San Diego, have websites that allow you to search for the records others have already requested using keywords. You can then dive into the rabbit hole of what’s already been made available. Browsing the records gives you a sense of what kinds of departments exist within those agencies, what kind of records they produce, what kinds of things other people ask for, and how they ask for them.

Response: What kind of records could address my question? Records may not be available to answer your exact question, but there may be records that give you some pieces of an answer. Possible records include email communications, presentations, memoranda of understanding, policy and procedure manuals, government filings, and contracts.


Prompt: It can help to speak with people who interact with the government a lot. Activists, lawyers, and policy nerds can help you brainstorm based on their experiences requesting and filing documents. Again, browsing existing open records portals can also give you ideas. There is no shame in starting your request by copying and pasting another request you find and submitting it with the tweaks that get at the specific information you want. We do this all the time. You can also check the agency’s website to get a sense of the kind of forms and records they describe working with publicly.  Which public entity has the records I want? Determining this is key. After you figure out what you want to know, figure out who has it. The San Diego Police Department? The National Labor Relations Board? The Food and Drug Administration? Cities will often have a clerk who you can call and talk to—an act of bureaucratic goodwill or perhaps a legal requirement, depending on the state. Networking with others who work on the topic you’re interested in can also help. You may encounter hostility from some agencies, but remember, at least California requires that officials help you route your request to the correct departments.

Response: The entity should have a website explaining their public records procedure, often with an online form. Plan ahead, as it can take months to get the records you request—and that’s if you’re lucky. The agency may also charge you for requests beyond a certain number of pages. You’re also within your rights to request that they waive those fees.


Prompt: Transparency is a constant struggle. It helps to have allies. Are there organized groups—unions or community organizations, for example—that have a stake in the issue you’re trying to bring to light? They may have background knowledge about the politics behind the records you seek. They may have access to lawyers who can help you navigate local public records laws. They might want to help you make sense of the records you get because it benefits them too.

Response: Finally, if you want to know more because you want to change something about the way the world works, you’ll need to join with others to make it happen. Being frustrated and alone is a trash feeling. 1 In the beginning, there was the nursery, one of the characters in one of Virginia Woolf’s novels remembers, with windows opening on to a garden, and beyond that the sea. It’s a fun rejoinder to millennia of male chauvinist origin stories about the Word, Father, Son, Holy etc. But that character was lucky. In today’s housing market, how many newborns can afford a room of their own? Forget about one with ocean views.


Prompt: There were predictions, early in the pandemic, that as offices closed and white-collar professionals shifted to working from home, rents in San Francisco and New York would fall. On Instagram, millennial influencers were going off the grid. On Twitter, a new generation of culture warriors bravely admitted that they were sick of pronouns, and unhoused people, and moved to Austin. Keith Rabois kept tweeting about what a cool time he and all of his cool friends were having in Miami.  Even we developed a habit of scrolling at night through Zillow listings in the countryside, if only to avoid reading about the growing numbers of the sick and the dead right before trying to sleep.

Response: But in fact, the predictions did not come true. Rent is increasing at its fastest rate since 1986. If you want to rent, be prepared to pay a broker 15 percent to advise you on how to bid your own rent up. If you want to buy, good luck. Rising interest rates should cool the market soon. But for now, they mean that, even for those with good credit scores, mortgage rates have nearly doubled since 2020.


Prompt: While we were writing that paragraph, we got a New York Times push notification informing us that the housing shortage is not just a coastal crisis. Boise, Idaho is short at least 13,000 units. Here comes another: Shelters across the US are reporting a surge in people looking for help, with wait lists doubling or tripling in recent months.  It’s getting harder and harder to get in on the ground floor of Maslow’s pyramid. Citizens struggle to find shelter, from sea to shining sea.

Response: 2 But you knew that. About moving to Austin: As we were editing this issue, approximately half of all people in the United States officially lost a right that residents of many states had already lost in practice.  We knew this news was coming. Still, it felt crushing. Watching Nancy Pelosi recite poems, and Joseph Biden and Kamala Harris stammer in response to questions they have had months to prepare for, it is hard to know whether to scream, or to scream.


Prompt: We cannot talk about the theme of this issue without talking about the Dobbs ruling. If for decades the right to an abortion was grounded in the right to privacy, for better and worse the right to privacy has deep ties to home, in the sense of private property.  The idea that a person has the right to keep what happens behind closed doors behind those doors offers important freedoms. The ability to control who gets to know what about you is a crucial precondition of being free to do what you like. Privacy, in the sense of secrecy, preserves personal autonomy. Domestic life has been a central site of aspiration and emancipation for countless people who do not, or cannot, find freedom in public spaces. For many, home offers a refuge from racism and homophobia. It affords the ordinary pleasures of intimacy.  At the same time, however, the powerful have often invoked privacy to conceal their abuses of power. In Ancient Rome, the ideal of all political authority (auctoritas) was the rule that the man of a house exercised over his wife, children, and slaves. In the United States, too, the history of the right to privacy remains inseparable from the history of men treating women and children who depend on them—and white people treating Black people—with impunity.  Generations of advocates and activists have argued that it was a mistake to ground abortion rights in privacy rights. Recent events prove, as if proof were still needed, that the move that seemed strategic in the early 1970s was not in fact strategic. It made abortion rights fragile.

Response: If the right to privacy has historically been grounded in the right of the man of the house to do what he wants there, people who get pregnant do not get to go home. We are home.  So, as we face the prospect of even more people losing even more—rights to contraception, marriage, and even interstate travel—we have to be prepared to do at least two things at once. We have to build, and connect, spaces of care shielded from prying eyes. And we have to strive for a world where ownership of private space does not decide so much.


Prompt: 3 What’s tech got to do with it? Everything. And not only because Airbnb rentals and Zillow’s investment arm are helping drive a housing crisis, sending more and more people to the streets. Not only because, as one tweet we saw lamented, millennials forced to move back in with parents are now Zooming with their therapists like someone reporting LIVE from the scene of the accident! Anti-choice groups have long used targeted ads to direct misinformation to women searching online for abortion services. Now, for peanuts, brokers sell highly sensitive data about the geolocation of patients to would-be vigilantes. But the ways that technology shapes the ever-shifting divide between public and private—your business and your boss’s, or the state’s—run even deeper.  Home is, and has always been, entwined with technologies. Indeed, evolutionary scientists and archaeologists recognize dwellings themselves as technologies, among the tools that make humans human. Our homes enclose and arrange us. They shape our relations and communications, and their traces, in particular ways.  This means that the growing number of technologies that market themselves by claiming to protect the home are in fact transforming the boundaries that define it.  Life360, a smartphone app that tens of millions of parents use to track their children in real time, has been caught selling personally identifiable information about those children’s whereabouts to brokers who will sell it to almost anyone.  Amazon and competitors like Wyze have developed smart cameras that they encourage families to use to monitor their stoops—and other people’s—to keep an eye on Amazon delivery workers and anyone else who happens by. Other smart cameras reassure parents that they can leave their kids while keeping their nannies, and other household workers, under continuous surveillance.  Promising to preserve the sanctity of the private sphere, at the same time, these devices mine the private sphere for content that they disperse to the cloud, to leaky servers from northern Virginia to southern Guizhou.

Response: 4 This issue approaches the shifting intersections of home and technologies without making assumptions—and with an eye to justice.  In one piece, a public school teacher explores how, during the pandemic, edtech firms have garnished millions from public emergency relief funds without delivering on their promise to provide equal access to education. How could they? Students’ living conditions shape their learning conditions, even once quarantines are over.  In another piece, researchers look at how one person’s home becomes another person’s workplace, and still another’s data quarry. Care platforms incentivize parents to cooperate with their data gathering by surveilling caregivers, while making the caregivers more precarious.