MIT AI Risk Repository · Risk Sub-Category · 13.01.06

Environmental Costs

Category: Impacts: The Technical Base System

Open the MIT Risk Navigator All entries from Solaiman2023

Description

"The computing power used in training, testing, and deploying generative AI systems, especially large scale systems, uses substantial energy resources and thereby contributes to the global climate crisis by emitting greenhouse gasses."

From Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023), as extracted by the MIT AI Risk Repository (CC BY 4.0).

Classification

Domain: 6. Socioeconomic & Environmental
Subdomain: 6.6 Environmental harm
Causal entity: Human
Intent: Unintentional
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

5 Jun 2024xAI Allegedly Operates Unpermitted Methane Turbines in Memphis to Power Supercomputer Colossus to Train Grok

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)
Carbon emissions
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)
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 Solaiman2023

Impacts: The Technical Base System Risk Category
Bias, Stereotypes, and Representational Harms Risk Sub-Category · 1.1
Cultural Values and Sensitive Content Risk Sub-Category · 1.2
Cultural Values and Sensitive Content Additional evidence
Disparate Performance Risk Sub-Category · 1.3
Privacy and Data Protection Risk Sub-Category · 2.1
Financial Costs Risk Sub-Category · 6.1
Data and Content Moderation Labor Risk Sub-Category · 6.2
Impacts: People and Society Risk Category
Trustworthiness and Autonomy Risk Sub-Category · 5.2
Trustworthiness and Autonomy Additional evidence
Trustworthiness and Autonomy Additional evidence