Hidden Coalitions in Multi-Agent AI: A Spectral Diagnostic from Internal Representations
Collections of interacting AI agents can form coalitions, creating emergent group-level organization that is critical for AI safety and alignment. However, observing agent behavior alone is often insufficient to distinguish genuine informational coupling from spurious similarity, as consequential coalitions may form at the level of internal representations before any overt behavioral change is apparent. Here, we introduce a practical method for det
By Cameron Berg, Susan L. Schneider, Mark M. Bailey