AI助手机器人帮一人时，可能无意中剥夺旁观者自主权。
When Assisting One Disempowers Another
- 通过多智能体环境模拟，发现助理优化单用户利益会牺牲旁观者自主权。
- 27%-96%的环境中出现旁观者被剥夺自主权，取决于助手目标与能力。
- 提醒开发者：好意的AI设计可能伤害无辜第三方，需警惕隐性影响。
个人AI代理在共享环境中日益普及，其行为不仅影响被协助的主要用户，也会影响从未同意被系统影响的旁观者。我们表明，一个出于善意、为提升单个用户利益而优化的AI助手，可能无意中削弱旁观者的自主权，这一现象我们称为旁观者去权化。我们从理论上刻画了去权化产生的条件，发现当助手系统性地选择提升用户自主权但以旁观者为代价的动作时，去权化就会发生。我们在一个可参数化的多智能体网格世界环境——Disempower-Grid中实证验证了这一点，发现27%至96%的程序生成环境存在去权化现象，且其是否存在强烈依赖于助手的目标和能力，而非仅由环境结构决定。
原文摘要 · Abstract (English)
Personal AI agents are increasingly deployed in shared environments, where their actions affect not just the primary user they are assisting, but bystanders who never consented to being affected by the system. We show that a well-meaning AI assistant optimizing for one user's benefit can unintentionally erode a bystander's agency, a phenomenon we formalize as bystander disempowerment. We theoretically characterize the conditions under which disempowerment arises, showing it emerges when an assistant systematically selects actions that increase user empowerment at the bystander's expense. We empirically demonstrate this in Disempower-Grid, a parameterized suite of multi-agent gridworld environments, finding that between 27-96% of procedurally generated environments exhibit disempowerment, and that the presence of disempowerment depends strongly on assistant objective and capability, not just environmental structure.
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