Green AI - AI for Sustainability and Sustainability of AI (GREENAI)- Verantwortliche/Verantwortlicher
- N.N.
- Angaben
- Seminar
2 SWS, benoteter Schein, ECTS-Studium, ECTS-Credits: 5
für FAU Scientia Gaststudierende zugelassen, Sprache Englisch, There are no more free places in the SS 2022.
- Studienfächer / Studienrichtungen
- WPF INF-MA ab 1 (ECTS-Credits: 5)
WF MT-MA ab 1 (ECTS-Credits: 5)
WPF AI-MA ab 1 (ECTS-Credits: 5)
WPF INF-BA-SEM ab 5 (ECTS-Credits: 5)
WPF CE-MA-SEM ab 1 (ECTS-Credits: 5)
- ECTS-Informationen:
- Title:
- Green AI - AI for Sustainability and Sustainability of AI
- Credits: 5
- Prerequisites
- 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.
The grade will be based on a written report (40%) and scientific talk (60%). Active participation in discussions will be rewarded with a bonus.
- Contents
- 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
- Literature
- 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.
- Zusätzliche Informationen
- Erwartete Teilnehmerzahl: 15, Maximale Teilnehmerzahl: 20
- Verwendung in folgenden UnivIS-Modulen
- Startsemester WS 2022/2023:
- Green AI - AI for Sustainability and Sustainability of AI (GREENAI)
- Institution: Lehrstuhl für Maschinelles Lernen und Datenanalytik
Kurse
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