Kurs ist beendet

Sustainability in the digital age: Environmental Impacts of AI Systems

Angeboten von Vanessa Parli

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Welcome to the "Sustainability in the Digital Age" series

Artificial Intelligence (AI) offers transformative potential across industries, but its development and deployment come with environmental costs. The course covers topics such as the carbon footprint of AI models, methods for measuring and reporting environmental impacts, and challenges in estimating the sustainability of AI technologies. Students will gain insights into energy and carbon accounting, along with case studies demonstrating how AI’s environmental footprint is assessed. The course aims to provide a comprehensive understanding of the relationship between AI and the environment, equipping learners with knowledge to contribute to more sustainable AI practices.


This course is part of the Sustainability in the Digital Age series, a collaborative project between colleagues from Stanford University, SAP and the Hasso Plattner Institute.

Seit 18. März 2025 im Selbststudium
Kurssprache: English
Deutsch, English
Beginner, Big Data and AI

Kursinformationen

AI technologies drive innovation, yet every AI model consumes energy, leaving a carbon footprint. As the adoption of AI grows, so does its environmental impact. This course examines into the environmental impacts associated with artificial intelligence systems beginning with an overview of AI, including its core applications, and follows with a primer on energy and carbon accounting to establish a foundation for understanding AI's environmental footprint. Students will explore current methodologies for measuring and reporting the carbon emissions of AI models, including detailed case studies. Through this exploration, learners will gain insights into the key challenges faced by researchers and practitioners when attempting to quantify AI’s environmental impact.

In addition to reviewing current measurement practices, the course will offer recommendations for reducing its ecological footprint. Throughout the course, learners will engage with cutting-edge research from leaders in the field, encouraging reflection on how these issues are relevant to their work.

Scope:

The Sustainability in the digital age: Environmental Impacts of AI Systems course runs for two weeks with a total workload of approximately 6 hours. It includes around 12 videos (12-14 minutes each), followed by small self-tests. The final exam takes place in the second week.

All learning materials (videos, self-tests, and texts) are available from the start of the course. The final exam is activated at the end of the first week and remains open until the course ends, giving participants two weeks to complete the content and one week for the exam.

Prerequisites:

  • Basic understanding of Artificial Intelligence (AI)
  • Interest in sustainability, environmental science, or technology policy
  • No advanced technical or coding knowledge is required

Was Teilnehmende lernen werden

  • An introduction to AI and its core application areas
  • A primer on energy and carbon accounting.
  • Current methods to report and measure the carbon footprint of AI models
  • Case studies detailing how these measurements are conducted
  • Challenges and recommendations for estimating the environmental impact of AI
  • Future directions for reducing the impact of this technology

Für wen dieser Kurs gedacht ist

  • Researchers
  • Professionals
  • Policymakers

Für diesen Kurs einschreiben

Der Kurs ist kostenlos. Legen Sie sich einfach ein Benutzerkonto auf openHPI an und nehmen Sie am Kurs teil!
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Lernende

Aktuell
Heute
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Kursende
18. März 2025
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Kursstart
4. März 2025
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Anforderungen für Leistungsnachweise

  • Den Leistungsnachweis erhält, wer in der Summe aller benoteten Aufgaben mindestens 50% der Höchstpunktzahl erreicht hat.
  • Die Teilnahmebestätigung erhält, wer auf mindestens 50% der Kursunterlagen zugegriffen hat.

Mehr Informationen finden Sie in den Richtlinien für Leistungsnachweise.

Dieser Kurs wird angeboten von

Vanessa Parli

Vanessa hat fast 15 Jahre Erfahrung im Bereich der künstlichen Intelligenz in verschiedenen Branchen, von der Wissenschaft über die Biotechnologie bis hin zur Regierung und zu gemeinnützigen Organisationen. Vanessa hat einen Master of Science in Engineering Management und Computational Mathematics von der Johns Hopkins University und einen Bachelor of Arts in Industrial Engineering von der Arizona State University.