As artificial intelligence services spread, data centers are moving rapidly into urban neighborhoods, intensifying disputes in many areas. A case in Seoul’s Geumcheon district, in Doksan-dong, is being cited as an early sign of the kind of clash likely to recur nationwide. Demand is surging for “edge data centers” located close to users as AI services that require ultra-low latency — such as autonomous driving and real-time interpretation — expand. The problem is that social acceptance and rules are not keeping pace with the technology.
One point is clear: data centers moving into cities is not a choice but an inevitability. Unlike older industrial facilities that could be pushed to the outskirts, data centers compete on distance. To cut delays, they must be near users, which points to urban sites. AI competitiveness ultimately depends on processing speed, and giving up speed means losing industrial competitiveness.
But that does not mean social agreement can be ignored. Today’s conflicts are not simply misunderstandings or a lack of communication. Data centers consume large amounts of electricity and bring tangible burdens, including noise and heat from cooling systems and pressure on the power grid. Those are real costs residents must bear, and they cannot be resolved through explanations or publicity alone. The core issue is not psychology, but cost.
That means the response must change as well. First, policymakers should move away from framing speed and agreement as opposing goals. The need is not to slow projects, but to build systems that produce agreement faster. Setting preapproved zones and standardized siting criteria and procedures can reduce disputes before they start. Projects that meet set standards should be eligible for fast-track permits, on the condition of transparent disclosure and prior consultation. Speed and agreement are not a choice; they are a design requirement to achieve together.
Second, benefit-sharing should be redesigned realistically. Data centers are “low-employment infrastructure” with limited job-creation effects, making compensation arguments centered on jobs less persuasive. Instead, compensation should shift to direct economic benefits residents can feel, such as rebates tied to electricity costs, local development funds, or free digital infrastructure. Market logic is that burdens should be matched by commensurate compensation.
Third, the roles of the national government and local communities should be clearly separated. The central government should set siting standards and safety rules, while local governments negotiate whether to accept projects and under what conditions within that framework. Leaving all burdens to local disputes without clear standards is problematic, but so is a one-sided push from the center. Bottom-up participation and top-down standards are not mutually exclusive; they are two pillars that should share functions.
Fourth, a system should be introduced to price external costs and provide automatic compensation. Measurable harms — including noise, heat and power burdens — should be disclosed in real time, with compensation triggered automatically when thresholds are exceeded. That is presented as the most practical way to reduce conflict. The argument is that institutions, not explanations, and compensation, not trust, resolve disputes.
Data center conflicts are not limited to one area. As the AI era deepens and edge infrastructure spreads, such clashes are expected to occur more often and on a larger scale. Treating them as routine complaints or a temporary phenomenon, the article argues, will only ensure they repeat.
The central point is straightforward: technology demands speed, while society demands acceptance. The only way to meet both is to institutionalize the costs of conflict and distribute them fairly. If speed cannot be reduced and conflict cannot be avoided, the remaining option is to maintain speed while managing conflict through careful design.
The article concludes that AI competitiveness depends less on the technology itself than on how it is connected to society, and that data center disputes are a key test. It calls for moving beyond a simple speed-versus-agreement frame toward practical solutions that include costs and compensation.
* This article has been translated by AI.
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