๐Ÿ”AI RiskAtlas
โ† Risk Taxonomy
#4

Environmental sustainability impact

Risk taxonomy

Definition

Environmental impact of running LLMs, especially increased carbon emissions which impact the corporate social responsibility and ESG outcomes for the organisation.

Controls & guardrails that address this

4

Grouped by control function, with the AI lifecycle stage(s) to apply each and the other risks it addresses. Filter by control category below.

Control category
Preventive ยท 3
Compute carbon footprint assessment at intake

Include compute carbon footprint assessment in use case intake. Set energy efficiency thresholds as intake criterion.

Lifecycle stage1 โ€“ Use Case Context & Design
Algorithm selection for power efficiency

Select model architecture based on energy efficiency profile. Prefer lighter architectures where accuracy requirements permit.

Lifecycle stages1 โ€“ Use Case Context & Design3 โ€“ Onboarding, Build & Review
Use of pre-trained models

Use a pre-trained foundation model rather than training from scratch to reduce carbon cost.

Detective ยท 1
Test prioritisation

Track compute consumption and energy use in production against declared thresholds. Escalate when carbon budget is breached.

Open these in the Control Library โ†’

Other risks in Ethics

AI RiskAtlas is an educational model of how GenAI & agentic systems work and fail. Architectures and payloads are illustrative and simplified for learning โ€” not operational guidance. Real-world cases are summarised from public reporting.

Sources & further reading โ†’ยทBuilt by Shi Yuan โ†—