Tech Giants Are Trying to Cover Up the Environmental Impacts of Their Data Centers – The Progressive

Report on the Environmental Impact of AI Data Centers and Alignment with Sustainable Development Goals

Introduction

The rapid development of data centers for artificial intelligence (AI) presents significant challenges to achieving the United Nations Sustainable Development Goals (SDGs). An analysis of recent events, particularly in the United States, reveals a pattern of high resource consumption and corporate efforts to conceal environmental footprints, directly conflicting with goals for sustainable water management, energy, community development, and institutional transparency.

Water Resource Management and SDG 6: Clean Water and Sanitation

The immense water requirements for cooling AI data centers pose a direct threat to the sustainable management of freshwater resources, a core target of SDG 6.

Case Study: Mount Pleasant, Wisconsin

• A new Microsoft data center is projected to consume over eight million gallons of water annually from Lake Michigan.
• Microsoft attempted to classify its water usage data as a “trade secret” to prevent public disclosure, an action that undermines transparent governance of a public resource.
• This attempt was challenged under the Great Lakes Compact of 2008, which mandates strict documentation of water diversions to protect one of the world’s largest surface freshwater systems.
• Public access to the information was only secured after a lawsuit was filed by the Midwest Environmental Advocates against the city of Racine.

Implications for SDG 6

This case highlights a critical conflict between industrial water use and the principles of SDG 6. The lack of transparency and the high volume of water consumption by data centers threaten the sustainable availability of water for communities and ecosystems.

Challenges to SDGs 7, 11, and 12: Energy, Communities, and Responsible Consumption

The operational demands of data centers strain local infrastructure and challenge the principles of affordable energy (SDG 7), sustainable communities (SDG 11), and responsible consumption and production (SDG 12).

Corporate Secrecy and Resource Obfuscation

In regions like Virginia, home to the largest concentration of data centers in the U.S., corporate practices actively hinder sustainable development efforts.

• Non-Disclosure Agreements (NDAs): Tech companies compel local governments and utilities to sign broad NDAs, prohibiting the disclosure of energy and water consumption data. This practice prevents public oversight and informed decision-making.
• Impact on Residents: This lack of transparency deprives the public of information regarding the impact of data centers on their water and electricity costs, undermining the goals of affordable utilities (SDG 7) and sustainable community planning (SDG 11).

Unsustainable Production and Consumption Patterns

The business model for data centers often involves leveraging significant tax revenue offerings to municipalities, which in turn build dedicated energy and water infrastructure. This can lead to increased utility prices for local residents, prioritizing corporate benefit over community welfare and contradicting the principles of responsible production outlined in SDG 12.

Governance and Institutional Integrity: A Conflict with SDG 16

The tactics employed by technology companies to conceal their environmental impact and influence policy represent a significant challenge to SDG 16: Peace, Justice, and Strong Institutions, which calls for transparent, effective, and accountable institutions at all levels.

Failure of Regulatory Oversight

State-level environmental impact assessments, a key tool for institutional oversight, have proven inadequate in holding data center operators accountable.

1. California Case: An environmental impact report for a Microsoft data center in San Jose contained minimal analysis of water usage, deferring the query to the local utility—the entity selling the water to Microsoft. This creates a clear conflict of interest and represents a failure of regulatory duty.
2. Wisconsin Precedent: A forthcoming assessment for an $8 billion data center in Wisconsin is at risk of repeating this failure by deferring to local utilities, thereby avoiding a comprehensive state-level audit of industrial water use.

Corporate Influence on Policy

The integrity of public institutions is further compromised by corporate lobbying. In Virginia, Dominion Energy has spent over $67 million on elections since 2020 while lobbying to restructure electricity rates to maximize profit from the increased demand created by data centers. Such actions undermine democratic processes and prioritize corporate profit over public interest, in direct opposition to the spirit of SDG 16.

Conclusion: The Unsustainable Trajectory of Generative AI

A New Scale of Environmental Demand

The current wave of data centers, built to power generative AI systems, operates on a scale of “near endless scaling” with unprecedented energy and water needs. This distinguishes them from previous generations of data infrastructure and poses a more acute threat to global sustainability targets.

Alignment with Sustainable Development Goals

To mitigate the negative impacts and align the industry with the SDGs, the following actions are necessary:

• Enhance Transparency: Mandate public disclosure of water and energy consumption for all data center operations to support SDGs 6, 7, and 12.
• Strengthen Regulatory Frameworks: Empower state and federal agencies to conduct rigorous, independent environmental impact assessments, preventing conflicts of interest and upholding SDG 16.
• Promote Corporate Accountability: Hold corporations accountable for their environmental footprint and ensure that economic development does not come at the cost of sustainable resource management and community well-being.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

• SDG 6: Clean Water and Sanitation

  The article’s primary focus is on the massive water consumption of data centers. It explicitly mentions that a new Microsoft data center “will require more than eight million gallons of water each year” from Lake Michigan, which contains “20 percent of the Earth’s surface freshwater.” This directly connects to the sustainable management of water resources.

• SDG 7: Affordable and Clean Energy

  The article highlights the significant energy needs of data centers and the resulting impact on local communities. It notes that building infrastructure to power these centers can raise “electricity costs” for residents and discusses how Dominion Energy is lobbying to “reform electricity rates structures for large power users to account for the rapid spread of data centers.”

• SDG 11: Sustainable Cities and Communities

  The issues discussed are deeply rooted in local governance and community impact. The article describes how tech companies coerce “small towns into relinquishing control of public resources” and how municipalities build “transmission lines and water infrastructure to power data centers, even if it raises the prices of these goods for residents.” This relates to sustainable urban planning and resource management at the municipal level.

• SDG 12: Responsible Consumption and Production

  This goal is relevant due to the article’s focus on the unsustainable resource consumption patterns of the tech industry. The “unprecedented needs in terms of water and energy use” for generative AI data centers represent a production model with a significant environmental footprint that companies are actively trying to “cover up.”

• SDG 16: Peace, Justice, and Strong Institutions

  A central theme of the article is the lack of transparency and accountability. Tech companies use “non-disclosure agreements, or NDAs,” and argue for “trade secrets” to hide their environmental impact. The article points to failures in governance, where local governments sign these NDAs and state environmental agencies “abdicate their responsibility to audit data centers,” undermining transparent and accountable institutions.

2. What specific targets under those SDGs can be identified based on the article’s content?

• Under SDG 6:

  • Target 6.4: By 2030, substantially increase water-use efficiency across all sectors and ensure sustainable withdrawals and supply of freshwater to address water scarcity. The article’s focus on the millions of gallons of water required by a single data center directly challenges the goal of water-use efficiency.
  • Target 6.5: By 2030, implement integrated water resources management at all levels. The conflict over the use of Great Lakes water, protected by the Great Lakes Compact, and the attempts by companies to bypass public accounting highlight the need for robust and transparent water resource management.

• Under SDG 12:

  • Target 12.2: By 2030, achieve the sustainable management and efficient use of natural resources. The article details the massive consumption of water and energy by data centers, which is a clear example of the challenge in achieving efficient use of these natural resources.
  • Target 12.6: Encourage companies, especially large and transnational companies, to adopt sustainable practices and to integrate sustainability information into their reporting cycle. The article provides a counter-example, showing how companies like Microsoft and Amazon are “fighting desperately and creatively across the country to cover up the environmental footprint of their generative AI data centers” instead of reporting on it.

• Under SDG 16:

  • Target 16.6: Develop effective, accountable and transparent institutions at all levels. The article critiques the lack of transparency, citing how “at least twenty-five municipal governments that had entered NDAs with data center operators,” which prevents public oversight and accountability.
  • Target 16.10: Ensure public access to information and protect fundamental freedoms. Microsoft’s attempt to classify its water usage as a “trade secret” and the widespread use of NDAs are direct efforts to limit public access to information about the use of public resources like water and energy.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

• For SDG Target 6.4 (Water-use efficiency):

  A direct quantitative indicator is mentioned: the volume of water withdrawal. The article states that the Microsoft data center in Mount Pleasant “will require more than eight million gallons of water each year.” This figure serves as a specific data point for measuring industrial water consumption and tracking water-use efficiency.

• For SDG Target 12.2 (Sustainable management of natural resources):

  The article implies indicators related to resource consumption. Besides the “eight million gallons of water,” it mentions the need for “fifty megawatts of power per year” for a single buyer. These figures can be used as indicators of the material and energy footprint of the data center industry.

• For SDG Target 16.10 (Public access to information):

  A clear, though negative, indicator is provided. The article states that “The Virginia Mercury identified at least twenty-five municipal governments that had entered NDAs with data center operators.” The number of such NDAs in force can be used as an indicator to measure the restriction of public access to information, showing a lack of progress toward this target.

4. Summary Table of SDGs, Targets, and Indicators

Source: progressive.org