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Energy Consumption of AI in Education: A Case Study

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2023

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Gesellschaft für Informatik e.V.

Zusammenfassung

Although the utilization of AI in education has grown considerably in the last decade, its environmental impact has been disregarded thus far. In this paper, we examine the energy consumption of Artificial Intelligence (AI) in education, which is employed, for instance, in adaptive learning. We measured the energy requirements of four AI implementations used on the student learning platform orthografietrainer.net. We found that two of the implementations have notably low energy and CPU demands in comparison to the baseline, while in two other implementations, these parameters are significantly higher. We conclude that more attention should be paid to whether the comparable performance of AI in education can be achieved with lower energy consumption.

Beschreibung

Bültemann, Marlene; Rzepka, Nathalie; Junger, Dennis; Simbeck, Katharina; Müller, Hans-Georg (2023): Energy Consumption of AI in Education: A Case Study. 21. Fachtagung Bildungstechnologien (DELFI). DOI: 10.18420/delfi2023-35. Bonn: Gesellschaft für Informatik e.V.. PISSN: 1617-5468. ISBN: 978-3-88579-732-6. pp. 219-224. Learning Analytics und Künstliche Intelligenz. Aachen. 11.-13. September 2023

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