This undergraduate seminar examines the interface between artificial intelligence (AI) and sustainability with a focus on the environmental impact. It introduces foundational concepts of sustainability, including the United Nations Sustainable Development Goals (SDGs) related to the environment. The course analyses the direct impact of AI computation load, and more broadly data centres, on the environment (including material and resource needs, water footprint, waste and pollution). The indirect impact of AI on environmental sustainability is another topic of the course, both on the positive side (e.g., the way AI is helping in new material discovery, biodiversity and environmental monitoring, advancing a circular economy and sustainable society) and negative sides (e.g., rebound effects, irresponsible digitalisation, e-waste, and negative externalities on health and natural ecosystems, etc.). The course briefly discusses the economy-wide implications of using AI and the indirect relations of that to sustainability. Finally, the course reviews some applications of Large Language Models (LLMs) for improving environmental sustainability. Subject to availability, 1–2 guest speakers will be invited to present recent developments relevant to the course topic.

By the end of the course, students will be able to:

• Define environmental sustainability and discuss relevant UN SDGs and indicators
• Explain and appraise AI’s direct and indirect impacts on environmental sustainability
• Discuss several AI-based methods for resolving specific problems related to the sustainability of the environment
• Synthesise relevant literature and case evidence into concise analytical briefs and seminar discussions
• Communicate findings in oral formats and collaborate effectively on group tasks

• Standard FS (=”Forschungsseminar”) attendance policy applies.
• Overall attendance for 80% of the time is required.
• Attendance in the first unit is mandatory (unqualified absence will result in deregistration from the course).

The course includes three main forms of delivery:

• Keystone lectures that establish shared foundations (including in-class short activities).
• The students will choose one topic of their interest and prepare a synthesis paper on that, followed by discussions.
• Invited seminars from experts in the field.

• Class activity: group work, exercises, and presenting one paper synthesis 30%
• Quizzes (short quiz after each lecture): 30%
• Group projects (in groups of max 3 students): 40% 

• Successful completion of course 1 (“Basics of ICT & AI” / “Grundzüge der IKT & AI”) of the specialization Responsible Management of Information Systems.
• It is strongly recommended to also have completed course 2 to 4 of the specialization before commencing with this course.
• If you hold a valid registration for the course but are unable to participate, please deregister during the open registration period in LPIS. Your spot can be granted to other fellow students.
• Spots are allocated on a first-come, first-served basis during the registration period.
• After completion of the registration period, available spots will be allocated to students on the waiting list who have no valid registration for the relevant curricula's point. Students will be ranked by their study progress as determined by the vice rectorat for teaching ("hardship principle"), not by their rank on the waiting list.
• Important Note: The participation in the first unit is mandatory; students who fail to come forfeit their place to students on the waiting list (in the sequence of the waiting list). Students can excuse themselves if the reason for missing the first unit is serious and will concern only the first unit.

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