发表机构
Fleamily, Inc（Fleamily公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文研究带符号曝光下算法注意力的公平路由，证明曝光均等与负担均等无法同时成立，测量误差会隐藏负担转移，并基于约会平台数据量化权衡，提出可在线学习的负担均等策略。
AI 中文摘要
曝光公平性将算法注意力视为一种应公平分配的善物。但当自主智能体发起接触时，注意力是带符号的：它向愿意的接收者传递价值，同时给不愿意的接收者施加负担。我们形式化了带符号曝光下的路由问题，并表明注意力的公平分配未必是不想要的注意力的公平分配。我们的核心结果是一个不相容性：在带符号曝光路由中，曝光均等（各组间相等的接触率）和负担均等（相等的不想要的接触率）通常无法同时成立，两者之间存在一个随路由选择性增强而变宽的间隔带。第二个结果表明测量误差本身是一种公平机制：接收意愿评分中的组间差异噪声同时增加某组的曝光并降低其选择对象的质量，因此表面上的曝光公平增益是一种隐藏的负担转移。基于一个公共约会平台调查（n=2,499）进行校准，据我们所知，该调查独特地测量了接收方对对话智能体的接收意愿，我们发现曝光均等仅损失0.2%至2.3%的产出，却将人均负担比率提升至1.7倍：紧张关系存在于公平概念之间，而非公平与效率之间。最后，负担均等策略可通过二分法计算并在线学习：一个插件式学习器以2.3%的经验遗憾溢价恢复该策略。在带符号曝光市场中，操作性的设计选择不是效率与公平之间的权衡，而是选择哪种公平。
英文摘要
Fairness-of-exposure treats algorithmic attention as a good to be distributed equitably. But when an autonomous agent initiates contact, attention is signed: it delivers value to a willing receiver and imposes a burden on an unwilling one. We formalize routing under signed exposure and show that a fair distribution of attention need not be a fair distribution of unwanted attention. Our central result is an incompatibility: within signed-exposure routing, exposure parity (equal contact rates across groups) and burden parity (equal unwanted-contact rates) generically cannot hold at once, and the two are separated by a band that widens as routing grows more selective. A second result shows measurement error is itself a fairness mechanism: group-differential noise in receptivity scores simultaneously inflates a group's exposure and degrades whom it selects, so an apparent exposure-fairness gain is a hidden burden transfer. Calibrating to a public dating-platform survey (n=2,499) that, to our knowledge, uniquely measures receive-side receptivity to conversational agents, we find exposure parity costs only 0.2--2.3% of yield yet moves the per-capita burden ratio to 1.7 times: the tension is between fairness notions, not between fairness and efficiency. Finally, the burden-parity policy is computable by bisection and learnable online: a plug-in learner recovers it at a $2.3\%$ empirical regret premium. The operative design choice in signed-exposure markets is not efficiency versus fairness but which fairness.
