Generative AI agents equate understanding with resolving explicit queries, an assumption that confines interaction to what users can articulate. This assumption breaks down when users themselves lack awareness of what is missing, risky, or worth considering. In such conditions, proactivity is not merely an efficiency enhancement, but an epistemic necessity. We refer to this condition as epistemic incompleteness: where progress depends on engaging with unknown unknowns for effective partnership. Existing approaches to proactivity remain narrowly anticipatory, extrapolating from past behavior and presuming that goals are already well defined, thereby failing to support users meaningfully. However, surfacing possibilities beyond a user's current awareness is not inherently beneficial. Unconstrained proactive interventions can misdirect attention, overwhelm users, or introduce harm. Proactive agents, therefore, require behavioral grounding: principled constraints on when, how, and to what extent an agent should intervene. We advance the position that generative proactivity must be grounded both epistemically and behaviorally. Drawing on the philosophy of ignorance and research on proactive behavior, we argue that these theories offer critical guidance for designing agents that can engage responsibly and foster meaningful partnerships.

翻译：生成式人工智能代理将理解等同于解决显式查询，这一假设将交互限制在用户能够明确表述的范围内。当用户自身对缺失、风险或值得考虑的内容缺乏认知时，这一假设便不再成立。在此类情境下，主动性不仅是效率提升的手段，更是认知层面的必然要求。我们将这种状态称为认知不完备性：在此状态下，进展取决于处理"未知的未知"以实现有效协作。现有的主动性方法仍局限于狭隘的预期性，即从过去行为中推断趋势并预设目标已被清晰界定，因而无法为用户提供有意义的支持。然而，揭示超出用户当前认知范围的可能性并非天然有益。不受约束的主动干预可能误导注意力、使用户不堪重负或带来伤害。因此，主动代理需要行为锚定：即对代理何时、以何种方式以及应在多大程度上进行干预设定原则性约束。我们主张生成式主动性必须在认知与行为两个维度上获得奠基。借鉴无知哲学与主动行为研究，我们认为这些理论为设计能够负责任地参与并培育有意义协作关系的代理提供了关键指导。