By Slobodan Kovrlija, Diplo | Fact-checked by Irfan Ahmad
Artificial intelligence is usually experienced as something that appears on a screen. In rural Finland, it recently appeared as a cleared forest. Reports describe the clearing of hundreds of thousands of trees for Google data-center sites in Muhos and Otanmäki, followed by an order from Finland’s Licensing and Supervision Authority to halt environmentally significant preparatory work pending environmental assessments. Google disputes characterizations of the clearing as illegal and says it acted in accordance with Finnish forestry requirements. The controversy is about more than one company or one country. It shows how AI governance is becoming local infrastructure governance: a question of land, water, electricity, public consent, and who is allowed to know the full cost of building AI.
The Finnish case may be unusually dramatic, but it is not an outlier. Across the United States and Europe, data centers are generating conflicts over electricity, water, land, noise, public subsidies, and local consent. Regulating AI models is no longer enough. We also need to ask who is allowed to know what AI infrastructure consumes, where it is built, who benefits from it, and who pays for its grid upgrades.
AI is physical infrastructure
AI is often discussed as if it were weightless: a model, an app, a service available anywhere. Yet every query, generated image, and training run depends on physical infrastructure such as servers, cooling systems, electricity grids, water supplies, land, and transmission capacity.
Data centers are the most visible part of that material base. They require large amounts of electricity, and their cooling systems can also require substantial water. The OECD notes that AI compute infrastructure consumes water both directly, for cooling, and indirectly, through electricity generation. As AI deployment expands, these demands collide with local water scarcity, energy planning, and land-use decisions.
This is why AI governance cannot remain confined to questions of model behavior, safety testing, copyright, or platform regulation. A data center is not simply a private building containing computers. It is utility-scale infrastructure. Its effects extend beyond its fence: it can alter electricity demand, strain water systems, change landscapes, generate noise, and require public investment in grids and other infrastructure.
When a community learns about these effects only after construction has begun, permits have been granted, incentives negotiated, and land cleared, the result is predictable: distrust, opposition, and political conflict.
The transparency gap
Like any major infrastructure, data centers consume resources. The concern is that the public often has too little information to assess the bargain. In many US communities, developers have used nondisclosure agreements, limited public reporting, and opaque ownership structures. Residents may be asked to accept a project without knowing its expected electricity demand, water consumption, cooling technology, ownership, tax treatment, or the full cost of grid upgrades. Even local officials can struggle to obtain a complete picture.
This lack of visibility creates three governance problems:
➣ It undermines planning. Regulators need credible information about peak electricity demand, water use, and infrastructure needs to make sound decisions. Without facility-level data, they are asked to approve projects whose consequences they cannot fully measure.
➣ It raises distributional concerns. Data centers may bring investment and tax revenue. Still, they can also impose costs on communities: higher electricity demand, pressure on water supplies, noise, land-use change, and the risk that ordinary households subsidies infrastructure upgrades through their bills. These costs and benefits should not be assessed in the dark.
➣ Secrecy weakens democratic legitimacy. Communities are not merely stakeholders to be informed after the fact. They live with local impacts and the long-term infrastructure consequences. When decisions are made through confidential agreements and incomplete disclosures, opposition is a reasonable response to exclusion, not a rejection of AI itself.
These concerns are already visible in public comments on data-center proposals across the United States, where water use is among the most common issues raised. Residents in rural Utah, Idaho, Georgia, and elsewhere have raised worries about water pressure, electricity supply, noise from cooling systems and backup generators, and their limited role in decisions that could reshape their communities.
Governments are beginning to respond
The good news is that policymakers are beginning to treat data centers as infrastructure that requires public accountability.
California has enacted a package of laws designed to give communities more information about proposed data centers. The measures require reporting on energy consumption and efficiency, as well as disclosure of water use and land-use impacts. The state’s approach does not ban data centers; it tries to make their resource demands visible before permits are approved and construction begins.
Texas has taken a different route. Governor Greg Abbott ordered a pause on approvals for data centers seeking grid interconnection. At the same time, state agencies audit projected electricity demand, water use, tax incentives, ownership, cooling technology, and measures that impact the community. The pause signals that grid capacity and public costs are now central to assessing AI infrastructure.
Virginia has also moved in this direction. Its 2026 executive order on data-centre accountability emphasizes that communities should have meaningful, timely information and a genuine role in decisions about proposed developments. That language reframes data-centre governance as a question of public participation, not merely technical permitting.
In Europe, the issue is also becoming one of access to information. Lighthouse Reports has filed an Aarhus Convention complaint against the European Commission, arguing that EU rules prevent the public from seeing energy and water use by individual data centers. The complaint frames the issue in familiar democratic terms: people cannot meaningfully participate in decisions about infrastructure whose environmental footprint is hidden from them.
These developments show that data centers are no longer being treated only as investment projects or symbols of technological ambition. They are increasingly treated as politically sensitive infrastructure, closer in governance terms to power plants, water systems, and transmission networks than to ordinary commercial buildings.
What transparency should look like
Transparency does not mean publishing every technical detail or compromising legitimate security interests. Data centers do have genuine security needs, and commercial confidentiality can sometimes be legitimate. But there is a wide difference between protecting sensitive operational information and hiding information the public needs to evaluate a project’s impact.
Building on measures introduced in Virginia and California, a reasonable transparency agenda would include:
- Standardised reporting of electricity consumption, water use, cooling systems, onsite generation, and backup fuel use.
- Disclosure of ownership structures, especially where public incentives, tax breaks, or public infrastructure are involved.
- Publicly available assessments of grid impact, water availability, and environmental effects before irreversible construction work begins.
- Clear information about who pays for grid upgrades, road improvements, water infrastructure, and other public costs.
- Meaningful community consultation, with enough time and information for residents to understand the trade-offs.
- A clear boundary between security-sensitive details and information required for democratic accountability.
This agenda would not slow AI development for its own sake. It would make development more legitimate by ensuring that communities, regulators, and investors can see the real costs and benefits before decisions become irreversible.
AI’s legitimacy problem is physical
The debate about AI governance has often focused on what models say, what they predict, and how they might be misused. Those questions remain important. But the Finnish forest-clearing controversy, water concerns in Georgia, noise disputes in rural America, and grid strain in Texas point to another dimension of AI governance.
AI has a physical footprint. It consumes electricity and water. It occupies land. It changes local environments. It can require public infrastructure and public money. And when its resource use is hidden behind nondisclosure agreements or incomplete reporting, it creates a democratic deficit.
Data centre development should be governed in ways that allow communities to understand, scrutinise, and shape it. If AI is to earn public trust, its infrastructure cannot remain a black box. The public needs to see the utility bill.
Editor's Note: The article's content may be AI-generated or AI-assisted. Its authorship and use of AI tools have not been independently confirmed.
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