Session
Organizer 1: Karen Mulberry, IEEE🔒
Speaker 1: Karen Mulberry, Technical Community, Western European and Others Group (WEOG)
Speaker 2: Maike Luiken, Technical Community, Western European and Others Group (WEOG)
Speaker 3: Anja Kaspersen, Technical Community, Western European and Others Group (WEOG)
Speaker 2: Maike Luiken, Technical Community, Western European and Others Group (WEOG)
Speaker 3: Anja Kaspersen, Technical Community, Western European and Others Group (WEOG)
Moderator
Karen Mulberry, Technical Community, Western European and Others Group (WEOG)
Online Moderator
Karen Mulberry, Technical Community, Western European and Others Group (WEOG)
Rapporteur
Karen Mulberry, Technical Community, Western European and Others Group (WEOG)
Format
Roundtable
Duration (minutes): 60
Format description: An open discussion with experts from technology, policy, and sustainability fields allows for diverse perspectives on AI's environmental impact. The interactive Q&A ensures audience engagement, while the 90-minute duration provides ample time for discussion and audience participation.
Duration (minutes): 60
Format description: An open discussion with experts from technology, policy, and sustainability fields allows for diverse perspectives on AI's environmental impact. The interactive Q&A ensures audience engagement, while the 90-minute duration provides ample time for discussion and audience participation.
Policy Question(s)
1. How can AI developers and policymakers integrate sustainability into the lifecycle of AI systems, from design to deployment?
2. What regulatory frameworks and industry standards can ensure AI contributes positively to environmental goals rather than exacerbating climate challenges?
3. How can AI infrastructure be optimized to reduce energy consumption while maintaining performance and accessibility?
What will participants gain from attending this session? • A deeper understanding of AI’s environmental impact and key sustainability challenges.
• Insights into emerging solutions for making AI infrastructure more energy- and resource-efficient.
• Knowledge of policy frameworks that promote sustainable AI innovation.
• Best practices and case studies from industry leaders and policymakers on balancing AI growth with environmental responsibility.
SDGs
Description:
The environmental footprint of AI is expanding, shaped by the increasing compute demands of data processing, model training, and large-scale infrastructure. This growth places significant pressure on energy resources, water usage, and hardware supply chains, raising critical sustainability challenges. While AI is being applied to address environmental issues, the systems supporting it often remain resource-intensive, creating tensions between digital expansion and ecological impact. This session examines the realities of AI’s environmental cost and explores strategies for mitigating its footprint—from optimising data centre efficiency and hardware sustainability to policy frameworks that align digital infrastructure with long-term environmental resilience. How can sustainability be integrated into AI development and deployment from the outset rather than as an afterthought?
The environmental footprint of AI is expanding, shaped by the increasing compute demands of data processing, model training, and large-scale infrastructure. This growth places significant pressure on energy resources, water usage, and hardware supply chains, raising critical sustainability challenges. While AI is being applied to address environmental issues, the systems supporting it often remain resource-intensive, creating tensions between digital expansion and ecological impact. This session examines the realities of AI’s environmental cost and explores strategies for mitigating its footprint—from optimising data centre efficiency and hardware sustainability to policy frameworks that align digital infrastructure with long-term environmental resilience. How can sustainability be integrated into AI development and deployment from the outset rather than as an afterthought?
Expected Outcomes
• Identification of best practices and policy recommendations for sustainable AI.
• A summary report outlining key insights and proposed actions from the session.
• Networking opportunities that foster collaborations for sustainable AI initiatives.
• Contributions to follow-up discussions and potential integration into future digital governance policies.
Hybrid Format: • Onsite and online moderation: A dedicated moderator will ensure smooth transitions between in-person and virtual interactions.
• Live polling and Q&A tools: Online participants can actively engage through live polls and virtual Q&A sessions.
• Possible Breakout discussions: Online and onsite attendees will have structured opportunities for smaller group discussions to foster collaboration.
• Social Media