AIPolicyTracker
Menu

MIT AI Risk Repository · Risk Sub-Category · 66.12.02

Excessive energy consumption

Category: Environment

Open the MIT Risk Navigator All entries from Li2025

Description

"Excessive energy use resulting in energy bottlenecks and shortages for communities, organisations and businesses"

From A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents (Li2025), as extracted by the MIT AI Risk Repository (CC BY 4.0).

Classification

Causal entity
Other
Timing
Other

Subdomain definition: The development and operation of AI systems causing environmental harm, such as through energy consumption of data centers, or material and carbon footprints associated with AI hardware.

Real-world incidents in this subdomain

Browse all incidents in this subdomain

How other frameworks describe this risk

  • Excessive water consumption

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Electronic waste

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Excessive energy consumption

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Natural resource depletion

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Excessive landfill

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Carbon emissions

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Biodiversity loss

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Pollution

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

Other entries from Li2025