Increasing investment in artificial intelligence (AI) is prompting a larger discussion around sustainability, from the huge demand for electricity to power data centers to the life cycle emissions of hardware needed to enable this technology. Globally, companies and governments are preparing for significant increases in energy use and raw material extraction to meet demand. On the other hand, evolving technology and breakthroughs in AI optimization could lead to lower emissions than previously anticipated. Join us for a discussion about opportunities to decarbonize AI and learn how leaders in the field are navigating the uncertainty.
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Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Materials and critical minerals; Built environment and infrastructure
This study models the integration of AI data centers and cryptocurrency mining with shared renewable infrastructure to enable climate-neutral digital operations, showing potential for significant CO₂ reductions and advocating for supportive global policy frameworks.
ACS Publications
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Built environment and infrastructure
AI and ML optimize optoelectronic systems for sustainability by enhancing energy efficiency, renewable energy harvesting, environmental monitoring, and smart cities while also advancing ocean optics and photonics for marine ecosystem monitoring and climate change mitigation.
Library Progress International
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Built environment and infrastructure
Open access book assembling cutting-edge research exploring AI infrastructures and sustainability across media and communication, covering AI-driven media, energy consumption, climate change, and policies/ethics.
Palgrave Macmillan Cham
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Materials and critical minerals
This paper argues that AI's environmental impacts from energy consumption and water use to mineral extraction constitute a global climate justice concern that demands moving beyond efficiency metrics to center the unequal distribution of costs and benefits, particularly in the Global South.