Chapter 09 · Sustainability & AISustainability & AI
Black-box model
Definition
A model whose internal reasoning is not interpretable to its users or developers, so that outputs can be observed but not straightforwardly explained.
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
Deep networks with millions or billions of parameters are the archetype: their decision logic is distributed and opaque. 'Black box' is a property of the model-human relationship, not of accuracy — an opaque model can be highly accurate and still resist explanation.
How it is used
Opacity complicates every sustainability use where reasons matter: an AI-screened supplier, a scored credit, a flagged claim. Explainability techniques and documentation practices exist to open the box partially, and the EU's trustworthy-AI framework lists explicability as a core requirement.
Why it matters
When an unexplainable model informs environmental or social decisions, accountability has nowhere concrete to land. Black-box risk is therefore a governance category, not just a technical footnote — it determines where AI can responsibly be used at all.