Chapter 09 · Sustainability & AISustainability & AI
Multimodal AI
Definition
AI models that process and relate multiple types of data — text, images, audio, video, sensor streams — within a single system.
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
Multimodal models learn shared representations across data types; OpenAI's CLIP (2021), which jointly embeds images and text, was a landmark. The approach allows a model to answer questions about an image, caption a chart, or cross-reference a report with satellite evidence.
How it is used
Sustainability applications exploit complementary evidence: combining field photographs with acoustic records and satellite scenes for biodiversity assessment, or cross-checking textual claims against imagery in supply-chain due diligence.
Why it matters
Environmental reality is multimodal — it is seen, heard, measured and described. Models that integrate these channels enable richer monitoring, but also make it harder to trace which evidence drove a conclusion.