Sustainability & AI
Recommender system
Algorithms that rank and suggest content or products, shaping information exposure and consumption patterns at scale.
Definition
Software that ranks and suggests items — products, content, connections — to users based on predicted preference, typically learned from behaviour at scale.
Quick reference
At a glance
- Subject
- Sustainability & AI
- Editorial status
- Editorial draft
- Definition status
- Established
- Last updated
- 21 August 2026
References
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Overview
What it means
Recommenders combine techniques such as collaborative filtering and learned ranking, surveyed comprehensively in the Recommender Systems Handbook. They mediate a large share of online consumption, attention and purchasing.
How it is used
Relevance to sustainability runs through consumption patterns: recommenders steer what people buy, watch and read. They can be tuned to surface lower-impact products or credible information — or to maximise engagement regardless of consequence, including amplifying misleading environmental content.
Why it matters
Recommenders are among the most consequential algorithms for sustainability precisely because they are invisible infrastructure of demand. Their objective functions — what they are optimised to maximise — are a legitimate object of sustainability scrutiny.
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