The grade will be based on a written report (40%) and scientific talk (60%). Active participation in discussions will be rewarded with a bonus.

In this seminar, we will develop and discuss future perspectives of AI for sustainability, considering the sustainability of AI itself. Current advances in machine learning, particularly deep learning, are enabling new applications but are accompanied by an exponential increase in computational cost and thus significant carbon emissions (Schwartz et al., 2020; Vinuesa et al., 2020). In this seminar, we will learn about important aspects of improving the sustainability of machine learning algorithms.

This seminar offers a different perspective on machine learning as taught in other courses, namely its role in global climate change. This aspect is becoming increasingly important in research, but also in industry. Therefore, this seminar provides the following items:

• Introduction to ``Green AI'' versus ``Red AI''

• Guests talks on related research topics

• Group discussions on future prospects of AI, specifically machine learning

• Best practices for literature review and scientific presentations

• Literature review on Green AI in certain areas in groups

• Scientific talk of each student on one specific topic

• Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., ... & Nerini, F. F. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature communications, 11(1), 1-10.

• Schwartz, R., Dodge, J., Smith, N. A., & Etzioni, O. (2020). Green ai. Communications of the ACM, 63(12), 54-63.