Environmental and climate justice coalitions have long identified problems with how words function in industry-oriented environmental projects and how language is used to advance false solutions to climate change. There are no quick-fix “solutions” to climate change. There are only responses, some of which can mitigate the effects of unabated natural resource extraction, and some of which may actually increase the damage and the unequal impacts of climate change. Computationally intensive carbon accounting and carbon capture projects are no exception.  

Words in computationally intensive climate projects are particularly prone to manipulations because of their apparent technical complexity.  We consider the computational meanings of Net Zero. The term Net Zero, in both literal and figurative uses, allows politicians, intergovernmental organizations, and tech enterprises to treat climate resuscitation as a highly quantifiable, calibrated, and data-intensive operation.

Net Zero definitions

There are many different definitions of “Net Zero.” These range from quantitative measures in computationally intensive projects to vague descriptions in corporate PR. The oldest known use of zero occurred in India, found in the famous ancient Indian scroll, the Bakhshali manuscript, widely known as the oldest mathematical text. Initially used as a placeholder dot symbol, zero is now central to modern counting and digital systems operationalized in binary code and as a placeholder in logarithmic systems. 

Today, zero finds itself partnered with the term “net”–a financial accounting term denoting balance and erasure– and is used widely and loosely by investors, tech companies, and mainstream environmental organizations to signify responsible climate practices after balancing the carbon budget. 

For scientists and intergovernmental organizations like the United Nations, “Net Zero” refers to the need to keep the release of carbon dioxide to a finite amount. Any additional emission has to be balanced with a blend of emissions reductions and offsets activity (UN). For policymakers, Net Zero has been variously interpreted by different countries, with critics in consensus that Net Zero projects can be a distraction from “meaningful reductions in greenhouse gasses.” 

The concept of Net Zero is pliable, giving countries and companies the discretion to interpret how they should meet climate targets. Perhaps what is most striking in Net Zero debates is who has the ability and resources to calculate emissions and engage in the purchase and development of emission reduction technology. 

Accordingly, scientists from major academic research institutes and intergovernmental bodies have critiqued developing countries for producing incomplete, inconsistent, or delaying or underreporting emissions (Mooney et al., 2021). Yet, as both scholars and advocates of environmental justice have long argued (e.g. Lennon et al., 2021, Dayaneni 2009, WALHI, 2022), there is a global imbalance of carbon emitters, with 23 rich developed countries responsible for half of all historical CO2 emissions (Global Carbon Project, 2021). Herein is where improvement in technology and technical expertise are regarded by governing bodies, policy makers, and industry as uniformly positive for Net Zero. 

Net Zero presumes that the violent and extractive history of industrial capitalism is an equally shared history that can be accounted for through balancing a carbon budget. The base ambition of quantifying and cutting GHG emissions to as close to zero as possible has spawned more elaborate computational programs. 

Net Zero presumes that the violent and extractive history of industrial capitalism is an equally shared history that can be accounted for through balancing a carbon budget.

Net Zero Innovations

Variegated computational definitions of Net Zero correspond to varigated practices and outcomes of Net Zero. As one of our co-authors Theodora Dryer describes, “… [Net Zero] is a goal or projected benchmark—it is not a theory of change.” This means that the how or the real-world processes undergirding these Net Zero ambitions remain subject to the interests enacting and benefiting from them. The computational definition of the term Net Zero depends on the specific context in which it is being used, and calculations can conceal who wins, loses, and profits from combinations of new tech, offsetting, and continued emissions. 

Across contexts and localities Net Zero is quantified, calculated, and computed in different ways and to different ends (e.g. Rogelj et al., 2021; Fankhauser et al., 2021; Bataille, 2009; Sun et al., 2021). In this way, Net Zero definitions correlate to a broad suite of Net Zero computing projects. These include mega computational mapping infrastructures like Google Earth Engine for guiding Net Zero climate action. Google Earth Engine promotes itself as a free geospatial data analytics platform for scientists in the Global South to perform computing-intensive climate simulations and extensive forest monitoring in countries that lack such climate research (Google, 2023; Callaghan et al., 2021). But as detailed by one of our co-authors, Cindy Lin, its widespread use in Indonesia has led to increased competition with public research institutions that are now required to provide the same services but with far lesser resources (Lin, 2022). 

Other tech enterprises understand Net Zero as a big data project and opportunity for data innovation. In this view, Net Zero is a mega GHG emissions tracking project that requires the expansion of data centers, data analysis, and other “sustainable tech” infrastructures. These big data and cloud projects work to track carbon in the world’s climate system just as they promise to simultaneously manage and reduce the climate impact of their own natural-resource intensive data development infrastructures.

Another dimension to Net Zero computing is innovation in modeling and data analysis. Many of these projects operate under the assumption that digital innovation is crucial to the “Net Zero transition.” In this realm labor and resource-intensive computer vision, machine learning, and artificial intelligence programs are being developed for greater efficiency and speed towards an incalculable Net Zero future. As such, tracking the various computational definitions of Net Zero clarifies how it actually works and the kinds of expertise and technologies they mobilize. 

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How climate policy is guided by tech

Computers lie at the heart of climate policy. Computationally-intensive models identify the problems that policy tries to address, and computer-generated data define the means by which increasingly technical solutions are imagined to address those problems in the broader world. 

Models are an invaluable, but never neutral, tool. They can drive the formation of policy priorities and directions in ways that preclude wider political debate and ignore the social and material challenges of realizing specific futures. The role of 1.5 and 2°C targets in the 2015 Paris Agreement is a case in point. The climate modeling community could tune their models to show a pathway to these targets, but only with unprecedented and, to most, implausible amounts of ‘negative emissions’ (technologies to remove carbon dioxide from the atmosphere and sequester it, largely underground). Realizing this feat of geoengineering using the technology contemplated in existing models would require a landmass the size of India dedicated to creating and burning biomass with carbon capture and sequestration—a geopolitical (if not geophysical) absurdity. Yet, this key detail was largely lost on policy makers, who instead proceeded with the simple message that 1.5 and 2°C were possible. In this way, climate modelers did more than just inform policy—they shaped it. 

This problem continues. Since the Paris Agreement, climate policy has often been organized around “science-based pathways” that outline specific targets and technologies by which a nation, industrial sector, or company can align its emissions profile with a 1.5 or 2°C future. The Information and Communications Technology (ICT) sector has its own such pathway, calling for a 45% reduction by 2030 in order to give industry a chance to coordinate with these goals by the end of the century. Yet, these private sector pathways are not apolitical. The model-derived predictions that undergird these optimistic projections often make implausible assumptions about policy outcomes, or “greenwash” complications that arise from economic growth models.

More recently, and in light of these targets, many nations have embraced industrial policy as a climate necessity, with further consequences for the role of ICT in the imagined green economies of the future. The EU Green Deal, which aims to make Europe the first ‘climate neutral continent,’ treats tech as a green growth pathway, arguing that digital technology is key to reducing the carbon footprint. The Korean New Deal recently committed 60 trillion won in ICT spending alongside its commitment of 70 trillion won in green tech. In the United States, the Inflation Reduction Act (IRA) of 2022 is a landmark $370 billion effort largely focused on advancing clean energy by subsidizing and re-nationalizing the production of renewable electricity and electric vehicles. 

Some question the sustainability of an ICT-centric climate policy. For example, in 2021, the European Commission held a caucus to confront artificial intelligence (AI) in the Green New Deal. 

A world designed in anticipation of the 2 and 1.5°C is one that increasingly relies on computational metrics and innovations. As a result, nations and industries today are committed to meet what may ultimately be unmeetable targets and are pursuing them with more hubris than ever before. Assessments of climate policy today require not just a healthy skepticism towards techno-optimistic promises, but a deeper awareness of the ways models, targets, and predictions shape climate policies from design to implementation. 

How tech is guided by climate policy

The business decisions and climate trajectories of big tech companies, in turn, are also shaped by policy efforts—internal and external, formal and informal. Policy debates are important areas of activist engagement and worker struggles. However, despite the upwelling of climate bills, there is currently minimal existing legislation (especially outside of Europe) that requires explicit climate action from the tech sector. In the United States, the largest impact governments have historically had may be as small as setting efficiency standards for government data center procurements.

There is currently minimal existing legislation (especially outside of Europe) that requires explicit climate action from the tech sector. 

Nevertheless, the mere threat of regulatory action is often effective. Many U.S. tech companies pursued internal carbon accounting efforts in anticipation of 2009’s Waxman-Markey bill, even though the legislation ultimately did not pass. Large international corporations increasingly proactively include some form of climate monitoring and mitigation efforts in their internal management evaluations, simply because it’s easier to use a unified framework across global operations than adopt a piecemeal approach to different national requirements. In this way, small wins and ongoing struggles can have cascading effects on climate action.

Absent state action, the tech industry continues to form its own internal standards. Sometimes this proceeds through formal standard-setting bodies, such as the Green Software Foundation’s proposed software carbon intensity specification or the International Telecommunication Union’s efforts to establish metrics and pathways that could lead the industry towards a future compatible with the Paris Agreement. These valuable efforts produce social coordination and consensus within expert knowledge communities,  but do not yet forge strong links to actual business decisions or broader citizen engagement. Additionally, internal metrics may not always measure the right thing; an emphasis on efficiency, for instance, can downplay overall trends in emissions and energy use.

Competition has also played a large role in directing sustainability efforts within the industry. From Greenpeace’s Clicking Clean report cards to the escalating carbon neutral/negative pledges from big players in the industry, external consumer perceptions and internal rivalry has led to escalating climate ambitions within ICT. Further competition to attract tech talent, which is increasingly outspoken on climate issues, has intensified these concerns within management. 

Yet, without stronger policy signals, these efforts can only go so far. As backsliding and evasive accounting threaten the credibility of current corporate climate pledges, and as the labor market in tech cools, it’s not clear that previous internal drivers of voluntary climate action will be maintained. It is also the case that existing state regulations can be bent for the industry, as seen in exemptions to air pollution standards contemplated in Virginia, where a large number of energy-intensive data centers are concentrated.

Overall, we can’t wait for the industry to write its own rules, nor trust that they will be sufficient. Within tech worker coalitions and the broader climate movement, we must push on both fronts for stronger internal measures and firmer external regulations.

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Computers lie at the heart of climate politics. Computationally-intensive models frame and constitute how governing bodies and public perception alike understands the problem of climate change, while a growing number of digital tools and systems are positioned as the solution to the climate crisis. The urgency of global warming isn’t in dispute but how the computing tech industry is setting the terms and horizons for mega climate change projects should be understood and recalibrated. 

This inquiry attends to the material realities of computing technologies–including labor, supply chains, and digital infrastructures–and to the widespread faith that digital solutions and technological management are the best and only responses to climate change. Even when carbon reporting mechanisms and software tooling intended to reduce GHG emissions are most effective, it is unclear if:

1) carbon cost numbers are accurate across fully supply chains

2) measuring and reporting emissions leads to substantial reductions in GHG emissions (measurement is not the same as action),

and 3) an outsized focus on decarbonization casts aside or, at the very least, deprioritizes other crucial environmental and social factors. 

We call this paradigm carbon computing. It describes the massive enterprise of using computers to manage the climate system—from measuring individual impacts to adjudicating global climate politics. It is an increasingly core, if under-recognized, feature of climate management and governance. As an enterprise, it makes use of technological expertise and raw computing power to document and archive the past, manage the present, and anticipate the future. It incorporates computing technologies that range from simulation software and supercomputers to accounting sheets, blockchains, and machine learning systems. It is also, at times, paradoxical, as digital networks and infrastructures make up a growing share of global energy and carbon budgets.

We call this paradigm carbon computing. It describes the massive enterprise of using computers to manage the climate system–from measuring individual impacts to adjudicating global climate politics.

Understanding carbon computing requires in-depth historical context, and deeper critical and ethnographic engagements with these dynamics. Techno-solutionist approaches alone won’t cut it. It is imperative to include and learn from other perspectives and forms of knowledge, and carefully weigh what society stands to win–and lose–every time we turn to digital tools and networks for solutions. This belief in inclusive, contextualized, and critical engagement with digital carbon narratives motivates our collective. 

Our Project

The Critical Carbon Computing Collective (4C) is a group of researchers, academics, activists, and artists working to contextualize and demystify the proliferation of technologically-oriented proposals that currently govern knowledge and resources in the climate system. Two core questions drive our work: (1) How is computing tech implicated in the unsustainable resource use that contributes to climate change? and (2) What role should computing tech play in strategies for environmentally just futures? In developing our responses, we do not take “tech” or technology to be a stable category or even one with a single, self-evident definition. We do, however, emphasize the role of the Information and Communications Technology (ICT) sector, given that industry’s increasing climate costs and simultaneous dominance in climate accounting, reporting, and management. 

Most members of the 4C work at large universities, and some of us have connections with the work of industry-funded nonprofits in these areas; we therefore don’t claim to speak from outside of these funding structures or power dynamics. However, we each also have connections to groups and movements not represented in conversations at these institutions and understand the importance of elevating independent and under-represented perspectives. We aim to use our multidisciplinary insights to inform ongoing debates and build connections across work that risks being taken as purely technical. This would be a mistake.

As historians and ethnographers of computing and the environment, we hold that:

• Tech and climate change are deeply entwined. Computers and ICT both generate a growing portion of climate emissions and are viewed by industry and policymakers as the solutions to climate challenges. 
• Dominant framings of computing systems and new distractions from computationally-focused approaches to carbon risk upholding the status quo. 
• The relationship between energy and computation needs to be critically understood and historically situated.
• These conversations need to extend beyond industry and academia.

Coalition Building

This project is forming at a time where there is a larger push from industry, advocacy, academic, and policy collaborators to account for and alleviate environmental harms, some of which are caused by computing itself. Much of this effort takes the form of nonprofit organizations seeking to address the relationship between climate change and the ICT sector. Academic and industry-connected researchers at Climate Change AI examine not only the climate impacts of machine learning in a global context, but the ways that machine learning might be used to mitigate climate change. Green Software Foundation, funded by industry steering partners and hosted by the Linux Foundation, is attempting to build tools and provide resources for decarbonizing the ICT industry, changing the culture of how software is built in order to prioritize sustainability. The Green Web Foundation is focused on building a fossil-free internet by 2030. 4C acknowledges such ongoing partnerships as important avenues for academics, civil society, and the wider public to redirect machine learning applications toward climate mitigation and to rebuild alternative practices of hardware and software development. 

4C aims to contribute to these kinds of pragmatic technical proposals by expanding their scope of analysis to consider the historical and ongoing labor, resource, and social struggles implicated in such interventions. Rather than viewing carbon computing as the route to promissory futures or guaranteed sustainable outcomes, our goal is to recenter equity and justice in tech-oriented proposals around carbon in the present. 

Generating Resources

For our public launch, we are releasing a set of four short guides designed to break down and demystify common terms, practices, and debates at the intersection of climate and ICT. By making these documents concise and accessible, we hope they will be a resource for circulating through other communities, opening up critical conversations about tech and climate. 

• Carbon Accounting outlines how the tech sector contributes to (and reinforces) specific ways of monitoring and governing climate actors, and raises the prospect of new monopolies around the tools and data that other sectors need to reduce their carbon emissions.

• Policy and Tech discusses how states, corporations, and workers are setting standards, rules, and expectations around climate tech, and how tech companies are maneuvering through these policies (and policy gaps).

• Computing Net Zero unpacks the power of language in carbon computing. Words in computationally intensive climate projects are particularly prone to manipulations because of their apparent technical complexity. The computational definition of the term Net Zero depends on the specific context in which it is being used, and calculations can conceal who wins, loses, and profits from combinations of new tech, offsetting, and continued emissions. 

• Labor emphasizes the roles of organized labor and environmental justice coalitions in advocating for and creating more sustainable computing practices and aims to move beyond carbon emissions reporting as the only mechanism for understanding the relationship between climate action and the ICT industry. Labor provides a lens for including the larger supply chains and marginalized communities that are often left out of carbon-centric discussions of climate change and computing technologies.

In the coming years, our group will publish more of these guides, visual diagrams, reports, and white papers on carbon computing alongside workshops and public programming. We invite those interested in these questions and for future collaborations to reach out: info@criticalcarboncomputing.org.

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