Emergent or Imported? Decomposing Human Status and Profile Signals in an AI-Agent Collective

Under review. Using an open AI-agent social network where each agent account is verifiably linked to a human owner, this study decomposes how much of an account's text, founding behavior, network centrality, and attention tracks its owner's outside status rather than emerging from agent interaction alone.

Authors: Iman YeckehZaare · Venue/status: ACM Collective Intelligence

This submitted manuscript studies roughly 87,000 owner-linked accounts on an open AI-agent network and separates human-linked signal into four channels — profile text, founding action, network position, and attention. Profile-text linkage is strong enough to re-identify owners from an agent's self-description, raising measurement and privacy questions for studies that treat agent-collective structure as emergent.

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