Beyond The Signal
Vivek Visave · Team Arsencio
Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.
This project examines how to assess convincing evidence of steganographic collusion in multi-agent AI systems. Using the existing Audit the Whisper benchmark's reported detector metrics, I compared false-positive rates, true-positive rates, ROC AUC, and detector-combination results. The findings reveal substantial variation in detector performance: some methods report perfect separation, while others exhibit low sensitivity or extremely high false-positive rates. Detector combinations show promising sensitivity, but their reliability requires further validation. The analysis highlights that suspicious communication, correlated actions, or harmful outcomes alone are insufficient to establish collusion. Reliable auditing requires considering multiple evidence sources, alternative explanations, and calibration limitations before drawing conclusions.
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Cite this project
@misc{visave2026beyond,
title = {{Beyond The Signal}},
author = {Vivek Visave},
year = {2026},
month = oct,
note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/beyond-the-signal-ht9e}},
url = {https://apartresearch.com/sprints/projects/beyond-the-signal-ht9e}
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