AIPolicyTracker
Menu

MIT AI Risk Repository · Risk Sub-Category · 15.02.05

Environmental

Category: Second-Order Risks

Open the MIT Risk Navigator All entries from Tan2022

Description

The risk of harm to the natural environment posed by the ML system.

From The Risks of Machine Learning Systems (Tan2022), as extracted by the MIT AI Risk Repository (CC BY 4.0).

Classification

Causal entity
AI
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

  • Natural resource depletion

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

  • Excessive water consumption

    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)

  • Excessive landfill

    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)

  • 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 Tan2022