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.
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.
Reviews
No public critique yet.
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}
}More from AI Collusion Research Sprint
- View project: Collusion, Competion and Collapse
Collusion, Competion and Collapse
Atelier Alex Cline
Do AI traders collude when nobody tells them to? We built agora, a six-market benchmark with exact competitive and collusive benchmarks, and ran seven open-weight 2-4B models in 590 completed games under five …
- View project: Making AI Guardrails Understandable and Testable: A Framework Illustrated by a Simulated Bond Market
Making AI Guardrails Understandable and Testable: A Framework Illustrated by a Simulated Bond Market
Rogue Agents in Jail 🕵️🕵️♀️👮♂️
In order to advance AI safety research into shaping public policy, the development of technical controls needs to have a clear purpose, evidence, and limitations that are understandable for the people responsible for …
- View project: Extending Information-Theoretic Collusion Detection to Large Language Model Agents
Extending Information-Theoretic Collusion Detection to Large Language Model Agents
Gamma Ray
We test whether the information-theoretic collusion detector of Bonjour et al, validated on scripted agents, works on LLM agents. Gemma, Mistral and Qwen played 1000 rounds of three-player Rock-Paper-Scissors in three …