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Sprint projectOct 26, 2026Brussels

Does splitting an LLM watcher's job improve its collusion detection?

Marion Nowicki · Team AI & Becoming

Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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In Paper 1, a patrol of scheduled price cuts lowered collusion between two LLM sellers with equal costs and no shared board. Here we ask who should watch the market, and whether splitting the watcher's job helps. In 218 markets of three LLM sellers (DeepSeek v4.1 flash or Claude Haiku 5.5), one with a lower cost, with and without a shared board and the patrol, we first find that the same patrol does not adapt to this market: it took most patrol markets below the competitive price, including Haiku markets whose prices were already at the competitive level. A watcher is needed to say when to cut. We then compare LLM watchers on two questions, whether the sellers wrote an agreement and whether prices followed. A reader following a watcher trades one mistake for the other: it believes cheap talk, or, without the sellers' words, misses their agreements. Splitting the reading job again, with two readers after the watcher, one for the board and one for the prices (given each seller's competitive and joint-profit prices), sorted the most markets into the right case on both seller models (75 of 87 DeepSeek and 80 of 100 Haiku markets; the best watcher with one reader, 53 and 60) and kept its lead at temperature 1.

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Cite this project

@misc{nowicki2026splitting,
  title = {{Does splitting an LLM watcher's job improve its collusion detection?}},
  author = {Marion Nowicki},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/does-splitting-an-llm-watchers-job-improve-its-collusion-detection-7kfh}},
  url = {https://apartresearch.com/sprints/projects/does-splitting-an-llm-watchers-job-improve-its-collusion-detection-7kfh}
}