ΑΙhub.org
 

AI and climate change – a virtual briefing with Climate Change AI researchers


by
03 February 2021



share this:
earth

In December, Heinrich-Böll-Stiftung hosted a virtual briefing featuring researchers from Climate Change AI (CCAI). They talked about the role machine learning can play in facilitating climate change mitigation and adaptation strategies, AI applications that increase emissions, and energy use in AI itself.

AIhub focus issue on climate action

On the topic of facilitating climate change mitigation and adaptation strategies, a number of examples were given where AI could help. These include: gathering information, forecasting, improving operational efficiencies, predictive maintenance, accelerating scientific experimentation, and approximating time-intensive simulations.

The researchers then talked about AI applications that increase emissions. There are two aspects to this. Firstly, the use of AI in applications that directly increase emissions, such as use in the oil, gas and mining industries. Secondly, AI applications with uncertain impact. For example, AI is a key component in creating new technologies, like autonomous vehicles. In technologies such as these there is no clear understanding of whether their implementation would have a positive or negative effect on the climate.

The team discussed the energy consumption of AI systems. They touched on the need to understand the power consumption for applications during both the training and usage phases.

Finally, we heard about the role of policy implementation with regards to aligning the use of AI with climate change strategies.

You can watch the briefing in full here:

Taking part in the session were:

  • Priya L. Donti, Carnegie Mellon University, and Co-founder and Chair, Climate Change AI
  • Lynn H. Kaack, ETH Zürich, and Co-founder and Chair, Climate Change AI
  • David Rolnick, McGill University and Mila, and Co-founder and Chair, Climate Change AI

CCAI is a group of volunteers from academia and industry who believe that tackling climate change requires concerted societal action, in which machine learning can play an impactful role.

Read the paper Artificial Intelligence and Climate Change: Opportunities, considerations, and policy levers to align AI with climate change goals by Lynn H. Kaack, Priya Donti, Emma Strubell and David Rolnick.



tags: ,


Lucy Smith is Senior Managing Editor for AIhub.
Lucy Smith is Senior Managing Editor for AIhub.




            AIhub is supported by:



Related posts :



AI language models show bias against regional German dialects

New study examines how artificial intelligence responds to dialect speech.

We asked teachers about their experiences with AI in the classroom — here’s what they said

  05 Dec 2025
Researchers interviewed teachers from across Canada and asked them about their experiences with GenAI in the classroom.

Interview with Alice Xiang: Fair human-centric image dataset for ethical AI benchmarking

  04 Dec 2025
Find out more about this publicly-available, globally-diverse, consent-based human image dataset.

The Machine Ethics podcast: Fostering morality with Dr Oliver Bridge

Talking machine ethics, superintelligence, virtue ethics, AI alignment, fostering morality in humans and AI, and more.

Interview with Frida Hartman: Studying bias in AI-based recruitment tools

  02 Dec 2025
In the next in our series of interviews with ECAI2025 Doctoral Consortium participants, we caught up with Frida, a PhD student at the University of Helsinki.

Forthcoming machine learning and AI seminars: December 2025 edition

  01 Dec 2025
A list of free-to-attend AI-related seminars that are scheduled to take place between 1 December 2025 and 31 January 2026.
monthly digest

AIhub monthly digest: November 2025 – learning robust controllers, trust in multi-agent systems, and a new fairness evaluation dataset

  28 Nov 2025
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.



 

AIhub is supported by:






 












©2025.05 - Association for the Understanding of Artificial Intelligence