Final Call for Innovators: Join the AI Environmental Footprint Hackathon
Amsterdam, Tuesday, 26 August 2025.
Participants have a last chance to join the hackathon by August 27, 2025, aiming to reduce AI’s carbon and water impact, with top solutions featured at COP30 in Brazil.
A Global Initiative for Sustainability
The AI Environmental Footprint Measurement Hackathon, set to close its application window on August 27, 2025, invites global participation in addressing the ecological impacts of artificial intelligence. Organized by AI for Good, this initiative underscores the importance of developing metrics and tools that can effectively measure and reduce AI’s carbon and water footprints. Training large AI models is equated to emitting as much CO₂ as five car lifetimes, highlighting the critical need to address sustainability in the tech sector [1][2].
Key Goals of the Hackathon
With AI technologies expanding at a rapid pace, the hackathon challenges participants to craft solutions focusing on carbon emissions from AI processes and tracking water usage within data centers. Participants are also tasked with creating real-time monitoring systems and lifecycle assessments for AI systems, bolstering transparency and sustainability in AI development [1][2][3].
Incentives and opportunities
The stakes are high, with winning entries being presented at COP30 in Belem, Brazil, reinforcing this platform as a critical space for global dialogue on environmental issues within technological domains. The hackathon not only promises visibility at an international stage but also offers mentorship and resources from experts in AI, sustainability, and environmental science to the shortlisted teams [1][3].
Timeline and Evaluation
Participants must complete registration by August 27 and submit initial proposals by August 29, 2025. The prototype development phase, facilitated with expert guidance, spans from September 1 to September 30, with final presentations scheduled for October 15. Evaluation of entries will focus on innovation, feasibility, impact, and usability, aiming to cultivate concrete advancements in AI’s environmental stewardship [1][3].