“If we are unaware of our place in this world, what kind of society would we establish?” This was one of the questions posed by John Rawls in formulating his term “veil of ignorance,” discussing the ability to form a fair society free from bias or discrimination. We may seek a social model that ensures everyone’s rights and achieves social justice in a way that guarantees equal opportunities and equality among all; however, this question holds deeper inquiries into how to achieve justice, especially in the context of the environmental challenges we face today, exemplified by the carbon footprint resulting from technological advances and the expansion of big data.
In detailing the term, Rawls linked the idea of the “veil of ignorance” with our responsibilities toward future generations, enabling us to ensure a decent and sustainable life for them without harming the environment or depleting natural resources. He notes that a just society must be based on the “principle of fair savings,” which entails the necessity of preserving the environmental capacity for future generations and providing equal opportunities for all.
If social justice requires guaranteeing rights and equal opportunities for each individual, it must also extend to environmental justice. In this context, big data, which forms part of modern technological advancements, can be an effective tool for improving social and economic life. However, its hidden costs, such as the carbon footprint resulting from computing operations, pose a real threat to environmental justice and intergenerational equity.
Thus, environmental justice is not only about fair resource distribution among individuals; it also entails ensuring that the earth’s resources are not exhausted in ways that expose future generations to environmental risks that threaten their ability to meet their needs. Consequently, it is crucial to find a balance between communities benefiting from big data and ensuring that the use of these technologies does not come at the expense of the environment and the rights of future generations.
Invisible Costs:
Studies indicate that data centers are responsible for 1% of the world’s total energy consumption, a figure that is increasing over time. This increase in energy consumption does not come without environmental consequences. Data centers require massive amounts of energy to run servers and store data in a cool environment. This vast energy consumption, which often comes from non-renewable sources (such as coal and oil), significantly contributes to greenhouse gas emissions. Some research has indicated that global data centers contribute about 2 to 3% of global carbon emissions, the same percentage caused by the global aviation sector.
When reflecting on the numbers highlighted in the context of data centers, we see the situation transcends visible figures into deeper levels of social and environmental risks. Although data centers only account for about 1% of total global electricity consumption, their impact on local power grids can be enormous. In some U.S. states, energy consumption from data centers has exceeded 10% of total electricity consumption, and in Ireland, this figure has surpassed 20%. These numbers not only reflect the scale of consumption but indicate a kind of imbalance in digital economic growth that exceeds the capacity of traditional infrastructure to respond. While data centers accelerate, power networks are lagging behind in keeping pace with this growth, creating a stark contrast between technical aspirations and environmental challenges.
It is also important to consider that large data centers (known as “hyperscale data centers”), which have become more prevalent in recent years, require enormous energy, sometimes reaching 100 megawatts or more; the equivalent of the energy consumption of 350,000 to 400,000 electric cars annually. These figures highlight the hidden energy costs required by these networks, which some view as mere commercial or economic numbers, whereas they actually signal deeper implications on social and environmental structures. All these activities contribute to increased pressure on local networks, which could lead to local energy crises if the balance between digital growth and energy infrastructure expansion is not considered.
This upward trend is expected to continue in the future. If current policies persist, it is estimated that data centers will significantly contribute to the rising global demand for electricity, projected to increase by 8,000 terawatt-hours (TWh) by 2030; equivalent to the total electricity demand of the United States and the European Union currently. While these figures seem enormous, they still appear blurred when compared to the growth effects that may occur due to the rapid evolution of artificial intelligence, which remains largely uncertain; suggesting that future growth may surpass expectations significantly, placing unprecedented pressure on power grids in the near future.
Moreover, data centers are often built on large lands that require massive resource consumption and impact the local environment. These lands may be agricultural or other natural areas, leading to the destruction of ecological habitats. Additionally, data centers need significant amounts of water to cool servers, creating an additional burden on water resources in some areas experiencing scarcity.
One aspect of the hidden environmental cost of big data lies in how capitalist policies often ignore environmental consequences. Companies managing massive data centers usually do not disclose how much energy they consume or how much water they use to maintain these systems. Consumers and sometimes governments avoid considering these effects and are encouraged to continue using these technologies as “convenient” and “efficient” solutions; thus, the collective awareness is blurred regarding reducing the environmental impact of these technologies.
Energy consumption from data centers in the United States is part of this process. While companies producing these technologies provide data on sustainability achieved in their operations, the reality is that a large portion of the energy used to operate these centers comes from non-renewable sources. This model focuses solely on direct economic gains and technological benefits without considering their long-term environmental effects.
Lost Opportunities:
In a related context, major companies like Google, Amazon, Microsoft, and Facebook are developing strategies to exploit data for maximum financial gain. These companies contribute to defining “economic resilience,” where companies must continuously adapt to the growing demand for “cloud services” and data. However, at the same time, these practices promote environmental fragility; a hidden cost that is often ignored or marginalized.
These companies benefit from vast capabilities in storing and analyzing data using massive data centers. However, what is not sufficiently discussed is the environmental costs associated with these centers, which require immense energy consumption. Amazon, for example, operates many data centers worldwide to provide “cloud computing” services, each consuming huge amounts of electricity to operate servers and cooling devices.
The real cost of data lies in a range of dimensions that go beyond direct costs such as servers and cloud storage, where challenges escalate with the increasing complexity and volume of data. According to the report issued by the International Data Corporation (IDC), spending on cloud storage and processing infrastructure increased by 18.5% in the fourth quarter of 2023, and this trend is expected to continue in the future. These direct costs, such as server fees and software licenses, represent just part of the picture, while the real costs lie in indirect expenses such as governance, security, and employee training.
Indirect costs often go unnoticed; however, they significantly affect corporate budgets. For example, good data management requires investments in data security, such as encryption and intrusion detection systems; necessary for protecting data from breaches. Also, laws and regulations related to data protection lead to additional compliance costs such as policy updates and audits. Added to this are the costs associated with training employees on best data management practices, making it more complex than merely the cost of servers.
On the other hand, costs are not limited to what is actually paid; they also encompass lost opportunities due to poor data management. When data is disorganized or inaccurate, it can lead to ineffective decisions that negatively impact revenues and competitiveness. Companies that fail to use their data effectively may fall behind competitors who can extract strategic insights from their data; therefore, it is essential to adopt comprehensive data management strategies that involve governance, automation, and security to maximize the benefits from data assets and reduce the hidden costs associated with them.
Global Justice Gap:
Sustainable development aimed at achieving intergenerational justice requires adopting environmentally friendly technological policies, such as utilizing renewable energy in data centers and “green data” computing, which work to reduce carbon pollution resulting from massive data processing. These strategies ensure that societal benefits from technological advances do not come at the expense of the Earth’s ability to maintain a viable environment for future generations.
Considering the social and economic transformations contemporary humans face under the dominance of a globalized capitalist system, individuals and communities today experience a state of constant “vulnerability” due to the pressures of global capitalism characterized by rapid change and indifference to long-term consequences. Specifically, one can refer in this context to the view of Polish philosopher Zygmunt Bauman regarding the consumer race; he assumes that individuals today are in a constant and intense race toward self-fulfillment through consuming modern technologies and seeking personal desires, without deep consideration of social or environmental impacts.
Thus, the consumer race can be linked to big data practices that follow the same capitalist principles that Bauman observes. The capitalist system that relies on accelerating production and consumption processes requires massive amounts of data to “improve efficiency” and “maximize profits,” but without regard for the consequences of this immense expansion of technology on the environment or social structures.
Individuals and companies navigate through rapidly changing social and economic environments that do not ensure stability or social security. In this context, the costs of big data can be understood as part of the race to consume as much information as possible, whether this information relates to individuals’ lives, purchasing behaviors, or even cultural tastes.
Large companies behind the collection and analysis of big data drive this rapid shift toward a society entirely reliant on data. But there is no time to stop and reflect on the consequences, as everyone rushes in a continuous frenzy for profit and investment.
This capitalist tendency, which targets resource consumption without regard for environmental or social boundaries, is linked to societal “resilience.” Within the sphere of big data, companies work to enhance this “resilience” by offering technologies and models that help individuals adapt to market shifts by improving their consumption lifestyle, but without ensuring the sustainability of these solutions.
Veil of Ignorance:
Returning to the term “veil of ignorance” as a mechanism for distinguishing between what we know and do not know about the impacts of our actions, whether they are economic, political, social, or environmental; the stream of big data is in essence a conscious distortion of collective awareness; where individuals and communities are pushed to ignore the consequences of their choices, whether those choices relate to investing in certain technologies or consuming resources.
In the realm of big data, we can see how individuals and companies ignore the environmental and human impacts stemming from this technology. For example, while companies strive for massive economic gains, most users do not consider the immense environmental impacts arising from operating massive data centers. These impacts are “concealed” by promoting the immediate benefits of technology such as “convenience,” “speed,” and “efficiency,” preventing public awareness from sensing the true environmental costs.
One other dimension of the big data field is how this capitalist model disproportionately affects communities. While large companies profit from this data to achieve huge profits, the environmental or social costs borne by local communities, especially in developing countries, are not taken into account. In these contexts, the impact of social fragility is concealed; leaving society in a state of marginalization and inability to influence global corporate decisions. This fragility manifests as increased poverty and deterioration of social life.
In conclusion, the intersection of social fragility and the “veil of ignorance” opens up a broader horizon for a deeper understanding of how big data impacts the environment and society. Global companies that rely on big data contribute to creating a frenzied race toward unlimited consumption, while environmental damages resulting from that are overlooked or concealed. In this context, it can be said that the “veil of ignorance” does not only obscure the impacts of these technological systems but also deepens social fragility by leaving individuals indifferent to the environmental and social costs of these technologies.
These transformations raise an important question: Can capitalist society remain resilient to environmental challenges, or will this resilience ultimately lead to a greater collapse due to indifference to environmental consequences?
