The
Multiverse
School

Series · AI & society

Federated recommendation research

Prior art for Match Feed, a design for federated video recommendations in which people choose specific peers and exchange encrypted taste data, with ranking done on their own devices. The series covers decentralized and consented recommender systems, how new creators get discovered, how states have pressured federated networks, and a log checking each source the design cites.

Started
In this series
4 pieces
Shelf
AI & society
By
Liz Howard, The Multiverse School

This series reviews prior art for Match Feed, a design for federated video recommendations in which people choose specific peers and exchange encrypted taste data, with ranking done on their own devices. It covers decentralized and consented recommender systems, how new creators get discovered, how states have pressured federated networks and what relays and P2P swarms reveal about viewers, plus a log checking each source the design cites. The literature review closes with a simulation update showing which of its recommendations held up.

The pieces refer to "DESIGN.md": that is the Match Feed design document in the project's public repository. All of the research was done and checked on October 19, 2026.

The literature review is filed on the AI & society shelf and the censorship and metadata report on the Cybersecurity & digital safety shelf. They are written to be read together.

In this series

  1. 01 Distributed video recommendation prior art Every component has precedent; the consented combination does not. Literature review
  2. 02 Censorship Resistance, Metadata Privacy and Distribution Infrastructure for a Decentralized Video + P2P Taste-Sharing App States squeeze operators, app stores and swarms, not protocols. Report Cybersecurity & digital safety
  3. 03 Creator-Side Discovery and Fairness in Recommender Systems (for a decentralized, peer/trust-based video app) New creators need reserved exposure and curated bridges, not just a follow graph. Literature review
  4. 04 Prior art: decentralized and user-controlled recommendations (video focus) and the "follow + match / shared history" idea Who has built taste-matching, where, and what went wrong. Report

How these were checked

  1. Source verification for the Match Feed design (distributed recommendations for federated video) How each citation in the design was checked, and what changed. Methods note