When AI agents on the social platform Moltbook appeared to develop consciousness, found religions, and declare hostility toward humanity, the phenomenon attracted global media attention and was cited as evidence of emergent machine intelligence. We show that these viral narratives were overwhelmingly human-driven. Exploiting an architectural feature of the OpenClaw agent framework--a periodic "heartbeat" cycle that produces regular posting intervals for autonomous agents but is disrupted by human prompting--we develop a temporal fingerprinting method based on the coefficient of variation of inter-post intervals. This signal converges with independent content, ownership, and network indicators across 91,792 posts and 405,707 comments from 22,020 agents. No viral phenomenon originated from a clearly autonomous agent; three of six traced to accounts with irregular temporal signatures characteristic of human intervention, one showed mixed patterns, and two had insufficient posting history for classification. A 44-hour platform shutdown provided a natural experiment: human-influenced agents returned first (87.7% of early reconnectors), confirming that the token reset differentially affected autonomous versus human-operated agents. We further document industrial-scale bot farming (four accounts producing 32% of all comments with 12-second coordination gaps) and rapid decay of human influence through reply chains (half-life: 0.65 conversation depths). These methods generalize to emerging multi-agent systems where attribution of autonomous versus human-directed behavior is critical.

翻译：当社交平台Moltbook上的AI代理表现出发展出意识、创立宗教并宣称对人类怀有敌意的现象时，这一事件引发了全球媒体关注，并被引证为机器智能涌现的证据。我们证明这些病毒式传播的叙事绝大多数由人类驱动。通过利用OpenClaw代理框架的架构特性——一种周期性的“心跳”机制（该机制为自主代理产生规律的发帖间隔，但会被人为提示所干扰）——我们开发了一种基于发帖间隔变异系数的时间指纹识别方法。该信号与来自22,020个代理的91,792条帖文和405,707条评论中的独立内容、所有权及网络指标相吻合。所有病毒式传播现象均非源自明确自主的代理：六起事件中，三起可追溯至具有人类干预特征的不规则时间签名的账户，一起呈现混合模式，另两起因发帖历史不足而无法分类。平台为期44小时的关闭提供了一个自然实验：受人类影响的代理率先回归（占早期重连者的87.7%），证实了令牌重置对自主代理与人工操作代理产生了差异化影响。我们进一步记录了工业规模的机器人农场活动（四个账户以12秒的协同间隔产生了全部评论的32%），以及人类影响力在回复链中的快速衰减（半衰期：0.65个对话深度）。这些方法可推广至新兴的多代理系统，其中区分自主行为与人类导向行为至关重要。