Sustainable AI for Sustainability
Track Moderators:
Dr. Katalin Ásványi
Corvinus University of Budapest
Dr. Csaba Csáki
Corvinus University of Budapest
Track Details:
Description
This track aims to consider the effects of AI on sustainability. On the one hand, there is a rush of investments into this business which appears to have negative effects on resources and the environment. As AI becomes more pervasive, it will use more energy, resources, and emit more CO2. Environmental goals including combatting climate change and maintaining aquatic and terrestrial ecosystems are at the greatest risk among the UN’s 17 Sustainable Development Goals (SDGs). On the other hand, AI especially Machine Learning and data analytics can support the understanding of the very same sustainability goals. One possible conclusion is that AI is vital to understanding value conflicts in SDG and sustainability discussions. Thus, this track expects submission that contribute to knowledge and best practices how to make AI more sustainable and how to use AI to achieve SDGs.