AIM & SCOPE

A two-sided study area, Green and Sustainable AI refers to the use of artificial intelligence (AI) and machine learning (ML) technology to address sustainability and environmental challenges.

On one side, Green AI focuses specifically on creating AI and ML systems and algorithms that are environmentally friendly, increasing resource efficiency, and providing cleaner technologies. This includes developing energy-efficient algorithms and hardware to reduce carbon footprints and covers a wide range of significant uses, including supply chain optimization, traffic flow management in big cities, waste reduction in agriculture, and optimizing energy use in buildings and factories.

On the other side, Sustainable AI aims to develop AI and ML algorithms and systems that utilize hardware with low processing, storage, and power requirements. This approach is essential for enabling AI/ML algorithms to run on resource-constrained edge devices or in edge-cloud computing systems while minimizing the carbon footprint during AI operations. Additionally, Sustainable AI embraces a broader scope of sustainability by aligning with human-centered values and promoting technology that upholds the principles of fair, trustworthy, and responsible AI. These principles include transparency, accountability, safety, robustness, reliability, non-discrimination, inclusive and sustainable development, and interpretability.

The main goal of this workshop is to bring together scholars from various disciplines to examine the nexus between Green and Sustainable AI.