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Trump is giving data centers a pass to pollute

The Verge · AIby Justine Calma ()4 min read3 · 1 read
AI summary · glm-5.3-flashSummaries by Vani AI

Former EPA officials warn that Trump-era deregulation to speed AI data center construction worsens pollution, citing 30 federal policy changes.

The Environmental Protection Network, a group of former EPA employees, released a report identifying 30 federal actions since January 2025 — 17 of which specifically mention AI or target data centers — that they say increase health risks from data center pollution. Trump's July 2025 AI Action Plan recommended streamlining regulations under the Clean Air Act, Clean Water Act, and Superfund law to expedite data center and chip factory permitting. A cited study from UC Riverside, Caltech, and Rochester Institute of Technology projects AI-related air pollution could cause up to 1,300 premature deaths and more than $20 billion in public health costs by 2028.

Key facts
  • Report catalogs 30 federal actions since January 2025; 17 mention AI or target data centers
  • AI Action Plan recommends easing Clean Air Act, Clean Water Act, and Superfund rules for data centers
  • Cited study projects up to 1,300 premature deaths and $20 billion in health costs by 2028
  • Former officials propose a 'Data Center Health Protection Pledge'
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From the original article

4 min read at theverge.com

President Donald Trump is weakening environmental regulations in the name of speeding up the construction of AI data centers, raising health risks for Americans, a cadre of former EPA officials said this week in a briefing and new report. They are urging - perhaps futilely - the president to adopt a "Data Center Health Protection Pledge" to signal that the administration is taking the environmental threat seriously.

The Verge · AI

By Justine Calma · theverge.com

Read the full article at The Verge · AI

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.