Green AI – AI for Sustainability and Sustainability of AI
Content:
Can we use AI to combat global climate change? How can advances in machine learning and data science help to monitor climate crises and to conserve nature? What is the role of AI in reducing greenhouse gas emissions in the manufacturing industries, transportation infrastructure, agriculture, and power sector?
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
EELISA Days Guest Lecture – Green AI: Image Analysis for Environmental Monitoring. By Dr. Behçet Ugur Töreyin (ITÜ)
Dr. Uğur Toreyin Behçet will give a lecture about state-of-the-art image analysis based systems for environmental monitoring. Specifically, wildfire detection and fish behavior analysis approaches will be reviewed.
He would also provide an overview of environmental monitoring related projects carried out by the “Signal Processing for Computational Intelligence Group – SPACING” of Informatics Institute at Istanbul Technical University, will be presented
Learning outcomes and competences:
Students will analyze
- the opportunities that AI offers to combat global climate change
- the negative impact of AI on global climate change
- current research topics in the field of "Green AI"
Students will be able to
- discuss and work in a group
- perform and write a literature review
- give a scientific presentation
Recommended literature:
Schwartz, Roy et al. (2020). “Green ai”. In: Communications of the ACM 63.12, pp. 54– 63.
Vinuesa, Ricardo et al. (2020). “The role of artificial intelligence in achieving the Sustainable Development Goals”. In: Nature communications 11.1, pp. 1–10.
Organisational:
Registration via email: eva.dorschky@fau.de
Participation requirements
Basic knowledge in machine learning is required to take part in the seminar. Students are expected to have completed one or more basic courses, such as PR, PA, IntroPR, DL, MTLS, or equivalent.
* If you would like to receive ECTS for your home degree program, please clarify credibility of the activity with your local study and degree coordinator beforehand.
