Climate change and machine learning

Réalisation : 11 mai 2021 Mise en ligne : 11 mai 2021
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With the increasing deployment of machine learning (ML) technologies across society, it is important to understand in which ways ML may accelerate or impede climate progress, and how various stakeholders can guide those developments. On the one hand, ML can facilitate climate change mitigation and adaptation strategies within a variety of sectors, such as energy, manufacturing, agriculture, forestry, and disaster management. On the other hand, ML can also contribute to rising greenhouse gas emissions through applications that benefit high-emitting sectors or drive increases in consumer demand, as well as via energy use associated with ML itself. In this talk, we will explore ML's multi-faceted relationship with climate change.


David Rolnick. Assistant Professor of Computer Science at McGill University.

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Citer cette ressource:
EcoInfo. (2021, 11 mai). Climate change and machine learning. [Vidéo]. Canal-U. (Consultée le 23 mai 2022)

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