<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Sustainability on AI and Society Course</title><link>https://msucerl.org/cmse101/tags/sustainability/</link><description>Recent content in Sustainability on AI and Society Course</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Thu, 21 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://msucerl.org/cmse101/tags/sustainability/index.xml" rel="self" type="application/rss+xml"/><item><title>5.2 The Carbon Cost of AI</title><link>https://msucerl.org/cmse101/use-cases/5-2-carbon-cost-of-ai/</link><pubDate>Thu, 21 May 2026 00:00:00 +0000</pubDate><guid>https://msucerl.org/cmse101/use-cases/5-2-carbon-cost-of-ai/</guid><description>&lt;h1 id="the-carbon-cost-of-ai"&gt;The Carbon Cost of AI&lt;/h1&gt;
&lt;h2 id="context--systems-architecture"&gt;Context &amp;amp; Systems Architecture&lt;/h2&gt;
&lt;p&gt;The rapid integration of artificial intelligence into daily digital infrastructure is frequently presented as a clean, virtual shift that saves human labor and carbon footprint. This framing hides a massive, highly material physical reality: AI runs on an incredibly resource-intensive global network of factories, power grids, and cooling infrastructure. The expansion of generative AI and LLM clusters has triggered an unprecedented surge in electricity demand, forcing tech conglomerates to expand fossil-fuel dependencies and directly undermining global carbon reduction mandates.&lt;/p&gt;</description></item></channel></rss>