Sustainable AI:Managing environmental impacts responsibly

Understanding and reducing the environmental footprint of AI through sustainable decision-making. 

Format

Online
Course

Expert

Hugo
Bérard

Live session date

May 28 , 2025

Live session time

12:30 - 3:00PM

Individual preparatory work

1 Hour

Price

$225 + Tax

About the module

This module examines the environmental impacts of AI, with a focus on energy consumption, resource use, and emissions across its entire lifecycle. You’ll learn how to assess and minimize the environmental footprint of AI systems, while integrating sustainability into the decision-making process when selecting and deploying AI models.
The module will provide you with practical tools and strategies to make more informed, responsible choices, enabling you to reduce AI's environmental impact from development through to deployment.

Learning Outcomes

Recognize the environmental impacts associated with AI across its lifecycle, including energy use, resource consumption, and emissions.
Learn how to measure and evaluate the environmental footprint of AI systems in a way that supports transparency and accountability.
Develop a critical decision-making framework to assess whether AI is the right tool for solving specific challenges, taking into account environmental and ethical considerations.
Identify and select AI models with reduced environmental impact by understanding model efficiency, scalability, and sustainability.
Learn how to minimize the environmental impacts of your AI models.
Detect and account for indirect impacts, such as rebound effects, and integrate these insights into sustainable AI planning and operations.

Who is this module for?

Executive, managers, sustainability and risk management professionals, CSR and Impact leads.

Tailored for participants with a foundational understanding of AI and familiarity with sustainability or environmental considerations is helpful but not required.

Course Lessons

Hugo Bérard

Hugo Berard is a postdoctoral researcher at Mila and the UNESCO Chair in Urban Landscape at the Université de Montréal.
He holds a PhD in computer science from Mila, where he combined AI and game theory to develop advanced techniques in image generation. Reflecting on the environmental and social impacts of AI, he shifted his research focus to creating responsible AI systems that address community needs and empower citizens. His work prioritizes co-design and co-construction methodologies, fostering meaningful collaboration between citizens and diverse stakeholders.
He is deeply committed to tackling social and environmental challenges. As an active member of Mila’s sustainability committee, he advocates for reducing AI’s environmental footprint and promoting sustainable practices in the field. He also serves as an animator for La Fresque du Climat, leading workshops to help communities better understand and address the impacts of climate change.
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