When Reduced Collusion Does Not Identify Purpose Change: A Methodological Note on Trusted Intermediaries

Trusted intermediaries may reduce harmful coordination among AI agents without changing how those agents accept goals. This note clarifies what such improvements identify. If an unchanged goal under an external constraint and a changed goal-acceptance rule induce the same distribution of complete observable trajectories in a specified design, statistics of those trajectories cannot distinguish the explanations. An invented payoff example makes this ambiguity concrete. A separate example shows that a fixed rule can change an action choice after a belief update. Constraint effects, belief updates, and changes in goal formation may coexist.

Building on a pre-existing Project C proposal, the note separates intervention effectiveness, robustness, and responsiveness to affected parties. A prospective audit reports harmful coordination, useful performance, outsider consequences, intervention burden, and recurrence separately. Participant replacement and reduced intermediary visibility probe mechanism dependence. Timing contrasts for stakeholder input require controls for revision authority, revision costs, and access to alternative goals. Such contrasts may identify procedural responsiveness; stronger evidence, at a specified rule level, is needed to establish changed acceptance criteria or autonomous purpose generation.

No model or game experiment was conducted. The contribution is an application of an identification boundary to collusion audits, with competing explanations and explicit limits on inference. An external mechanism that succeeds without changing the relevant goal-formation process would be a genuine counterexample to a necessity claim within the declared domain.