Digital Platforms, AI, and the Climate Information Environment
uOttawa InfoLab · 2025-10-27
What people see, search, and share about climate is increasingly shaped by digital platforms and AI systems whose design, algorithms, and business models prioritize engagement and profit over accuracy. This panel examines how these infrastructures influence visibility and trust, sustain mis/disinformation and greenwashing, and carry their own material footprint through rising energy and resource demands. Panelists will explore the risks and opportunities these systems create, and what they mean for democratic participation, climate communication, and effective climate action.
uOttawa InfoLab. 2025-10-27. Digital Platforms, AI, and the Climate Information Environment. https://www.youtube.com/watch?v=RIaUsZVV4AM (AI & Environment Resource Hub; record pod-0166; collection snapshot 2026-09-15).
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Shared topics: Cross-cutting sustainability; Energy and electricity; Climate and greenhouse gases; Materials and critical minerals; Built environment and infrastructure
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.
youtube.com
Shared topics: Cross-cutting sustainability; 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; Energy and electricity; Climate and greenhouse gases; Materials and critical minerals; Built environment and infrastructure
Matthew Riemland examines how translation professionals can confront the environmental costs of AI, including carbon emissions, water consumption, and rare mineral extraction, through 'eco-translation practice.' He argues these harms stem from structural power imbalances rather than individual choices, and proposes vocational and structural strategies of resistance, from supporting data center activism to demanding transparency from AI developers.
Encounters in Translation
Shared topics: Cross-cutting sustainability; Energy and electricity; Climate and greenhouse gases; Built environment and infrastructure
By the end of this course, you will be able to explain how data centers power AI‑driven decarbonization across the global economy and why sustainable digital infrastructure is foundational to achieving net‑zero goals. You will learn how AI, enabled by cloud and edge data centers, supports clean energy grids, optimizes buildings and manufacturing operations, and accelerates electrified, efficient transportation systems
