When Autonomous Agents Become Recommender System Users
_reachsumit · x · 2026-07-31
A position paper accepted at RecSys2026 points out that current recommender systems are designed exclusively for human users, a fundamental assumption challenged by the rise of autonomous agents.
The author argues that future recommender systems must distinguish between two types of agents:
- Embedded agents: Operating within the recommender platform itself.
- User-representing agents: Acting externally on behalf of human users to interact with the platform.
This distinction will profoundly impact both the architecture and the evaluation metrics of recommendation algorithms.
Related event: RecSys Paper: Recommendation Systems Must Serve Humans and AI Agents(2 posts)→
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