Scott Logic: Technology Carbon Standard Update – 4th September 2025

Sep 4, 2025

—

Source URL: https://blog.scottlogic.com/2025/09/04/technology-carbon-standard-update-4-sept.html
Source: Scott Logic
Title: Technology Carbon Standard Update – 4th September 2025

Feedly Summary: The Scott Logic sustainability team has recently been updating the open-source Technology Carbon Standard website to better reflect evolving challenges of carbon accounting in the tech sector.

AI Summary and Description: Yes

Summary: The text discusses updates to the Technology Carbon Standard, specifically addressing the carbon footprint of Large Language Models (LLMs) and the broader implications for AI-related emissions in the tech sector. This is highly relevant for professionals in AI and cloud computing as it outlines significant steps in measuring and reducing carbon impact.

Detailed Description:
The text outlines recent efforts by the Scott Logic sustainability team to enhance the Technology Carbon Standard with a focus on the environmental impact of technology, particularly in the realm of AI. This initiative is significant for security and compliance professionals as the awareness of carbon emissions in technology is increasingly tied to regulatory compliance and sustainability mandates.

Key points include:

– **Expansion of the Standard**: The Technology Carbon Standard now addresses the emissions associated with Large Language Models, recognizing the need for better evaluation as AI technologies develop.

– **New Categories**: Introduction of a “Content” category in Upstream Emissions, encompassing emissions related to both AI-generated and traditional content. This demonstrates how emissions are accounted for through their entire lifecycle.

– **Lifecycle Assessment (LCA)**: The document emphasizes the alignment of the Technology Carbon Standard with LCA methodologies, critical for organizations aiming to comprehensively assess the environmental impact of their tech operations.

– **Glossary Updates**: An expanded glossary to include AI-specific terms will aid in the standardization of language around AI emissions, promoting clearer communication.

– **Resource Development**: A listing of major AI cloud platforms and their emissions data will aid organizations in understanding their carbon impact based on their service providers.

– **Practical Guidance**: The standard aims to provide actionable strategies for organizations to reduce AI-related emissions, highlighting specific optimization techniques.

– **Emissions Focus in Upstream and Operational Categories**:
– **Upstream**: Highlights training phases of foundation models, emissions linked to hardware manufacturing, and the carbon footprint of data center operations.
– **Operational**: Introduces new sub-categories addressing machine learning operations and the environmental impact of high-performance computing hardware as demand increases.

– **Downstream Emissions Scope**: The emphasis on user interactions and the cumulative carbon cost of AI application usage highlights the importance of addressing emissions throughout the value chain, including data transfer and customer interaction.

– **Open-Source Collaboration**: The Technology Carbon Standard operates as an open-source project, encouraging community involvement to further refine practices and establish norms within the tech industry.

This initiative aims to guide technology professionals towards sustainable practices, aligning ESG targets with operational strategies, which is increasingly critical in today’s regulatory environment. By embracing this assessment framework, organizations can elevate their commitment to sustainability while addressing compliance obligations related to environmental impacts.

2 2025 4 5 a account accounting Act actions addresses age AGI AI AI technologies alignment All and app Application application usage art as assessment at ated aware awareness based Bi bot by C carbon carbon emissions carbon footprint carbon impact center operations chain challenge challenges CI CIA CleaR Cloud cloud computing cloud platform cloud platforms co Col collaboration commit commitment communication community community involvement compliance compliance obligations compliance professionals Computing content cost CoT critical custom Customer D data data center data center operations data transfer day de demand demo development document e environment environmental environmental impact evaluation exp Expansion fact fine for foundation model foundation models framework g Gen generated glossary Go guidance H hardware high high-performance high-performance computing Highlight HR http HTTPS impact implications in industry inter interaction interactions io Iron ite J k Key l Labor language language model language models large large language model large language models Large Language Models (LLMs) learning led Li life lifecycle assessment line Link linked llm llms lm logic M mac machine Machine Learning man manufacturing methodologies mission ML Mode model models N new no o of on ons open open-source operation operational operational strategies operations OPM opt optimization optimization technique optimization techniques organization organizations ory oS oss out per performance performance computing platform platforms point practices pre pro professionals project ps Q R rag rate RCE re real red regulatory regulatory compliance regulatory environment resource Ro s scope sec sector security security and compliance service service provider service providers Sig size sizes SoC source source collaboration source development source project source technology specific SSE SSO standardization strategies sustainability Sustainable Practices T target team tech tech industry tech sector techniques technologies technology technology professionals ted text the to Tor TP training UI under up update updates ups US usage use user user interaction user interactions V val Valuation Ware web website Wi x z