Chapter 09 · Sustainability & AISustainability & AI
Fine-tuning
Definition
Additional training that adapts a pre-trained model to a specific domain, task or style using a smaller, targeted dataset.
References
This source provides part of the technical or institutional basis for the definition.
This source supports the explanation of how the term is applied, measured or governed in practice.
Overview
What it means
Fine-tuning updates some or all of a foundation model's weights on specialised examples — sustainability disclosures, legal texts, ecological recordings. It is far cheaper than training from scratch, and alternative lightweight methods (adapters, low-rank updates) reduce cost further.
How it is used
Organisations fine-tune general models to classify reports against frameworks, extract indicators in their own formats, or recognise domain-specific imagery — trading modest compute for substantial task accuracy.
Why it matters
Fine-tuning is the point of adaptation where generic AI becomes a specific tool — and therefore the point where domain data quality, bias and validation become the deploying organisation's responsibility.