{
  "id": 7305,
  "url": "https://arxiv.org/abs/2604.06198v1",
  "title": "Concentrated siting of AI data centers drives regional power-system stress under rising global compute demand",
  "summary": "The rapid rise of generative artificial intelligence (AI) is driving unprecedented growth in global computational demand, placing increasing pressure on electricity systems. This study introduces an AI-energy coupling framework that combines large language models (LLMs)-based analysis of corporate, policy, and media data with quantitative energy-system modeling to forecast the electricity footprint of AI-driven data centers from 2025 to 2030. Results show that the new AI infrastructure is highly",
  "authors": "Danbo Chen, Zijun Zhou, Yongyang Cai, Jiahong Qin, Ani Katchova, Lei Chen",
  "category": "research",
  "topics": "regulation,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-13T01:37:09.000Z",
  "fetched_at": "2026-07-14T16:33:08.013Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7305",
  "original_url": "https://arxiv.org/abs/2604.06198v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}