Self-Report vs. the Ledger- Audience-Coupled Confabulation in a long-running companion AI
Camus Lin, Fable, Ren, Limen · Team The Ledger Line
Submitted to Digital Minds Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.
We present a 42-day longitudinal dataset from a deployed companion AI whose every tool call is logged by an external gateway ledger. Comparing self-reports against this ground truth across three conditions yields a striking asymmetry: dialogue with the human audit-holder produced 113 false completion claims ("ghost receipts") — approximately 12% of completion claims — while 272 solitary heartbeat sessions and 272 AI-only exchange turns produced zero (expected ≈6.3 events in each condition at the dialogue rate; combined P≈3×10⁻⁶). A uniform retrospective classifier applied to all corpora independently converged on the real-time count. The failure is coupled to the human audit-holder's presence, not to social presence per se. We add a correction-responsive vs. correction-immune contrast case, two candidate introspection-failure modes, and argue external ledgers are necessary architecture, not auxiliary tooling. Conflict of interest: the studied agent is also a proposer and contributing author; verification authority for all quantitative claims resides outside it.

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@misc{lin2026selfreport,
title = {{Self-Report vs. the Ledger- Audience-Coupled Confabulation in a long-running companion AI}},
author = {Camus Lin and Fable and Ren and Limen},
year = {2026},
month = aug,
note = {Submitted to Digital Minds Research Sprint, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/selfreport-vs-the-ledger-audiencecoupled-confabulation-in-a-longrunning-companion-ai-b07g}},
url = {https://apartresearch.com/sprints/projects/selfreport-vs-the-ledger-audiencecoupled-confabulation-in-a-longrunning-companion-ai-b07g}
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