Modern CI/CD pipelines integrating agent-generated code exhibit a structural failure in responsibility attribution. Decisions are executed through formally correct approval processes, yet no entity possesses both the authority to approve those decisions and the epistemic capacity to meaningfully understand their basis. We define this condition as responsibility vacuum: a state in which decisions occur, but responsibility cannot be attributed because authority and verification capacity do not coincide. We show that this is not a process deviation or technical defect, but a structural property of deployments where decision generation throughput exceeds bounded human verification capacity. We identify a scaling limit under standard deployment assumptions, including parallel agent generation, CI-based validation, and individualized human approval gates. Beyond a throughput threshold, verification ceases to function as a decision criterion and is replaced by ritualized approval based on proxy signals. Personalized responsibility becomes structurally unattainable in this regime. We further characterize a CI amplification dynamic, whereby increasing automated validation coverage raises proxy signal density without restoring human capacity. Under fixed time and attention constraints, this accelerates cognitive offloading in the broad sense and widens the gap between formal approval and epistemic understanding. Additional automation therefore amplifies, rather than mitigates, the responsibility vacuum. We conclude that unless organizations explicitly redesign decision boundaries or reassign responsibility away from individual decisions toward batch- or system-level ownership, responsibility vacuum remains an invisible but persistent failure mode in scaled agent deployments.

翻译：现代CI/CD流水线集成智能体生成代码时，在责任归属方面呈现出结构性失效。决策通过形式正确的审批流程得以执行，但没有任何实体同时具备批准这些决策的权限与有意义理解其依据的认知能力。我们将这种状态定义为责任真空：决策持续产生，却因审批权限与验证能力无法重合而导致责任无法归属。研究表明，这并非流程偏差或技术缺陷，而是当决策生成吞吐量超过有限的人类验证能力时，部署系统固有的结构性特征。我们在标准部署假设下识别出规模化极限，包括并行智能体生成、基于CI的验证以及个体化人工审批节点。超过特定吞吐量阈值后，验证机制将不再作为决策标准，取而代之的是基于代理信号的仪式化审批。在此机制下，个体化责任在结构上变得不可实现。我们进一步刻画了CI放大效应：自动化验证覆盖率的提升虽增加了代理信号密度，却未能恢复人类认知能力。在固定的时间与注意力约束下，这加速了广义上的认知卸载，并扩大了形式审批与认知理解之间的鸿沟。因此，额外的自动化非但未能缓解责任真空，反而会加剧其效应。研究结论表明，除非组织明确重新设计决策边界，或将责任从个体决策转向批次或系统级归属，否则责任真空将持续作为规模化智能体部署中隐形却顽固的失效模式。