AI shopping agents are being deployed to hundreds of millions of consumers, creating a new intermediary between platforms, sellers, and buyers. We identify a novel market failure: vertical tacit collusion, where platforms controlling rankings and sellers controlling product descriptions independently learn to exploit documented AI cognitive biases. Using multi-agent simulation calibrated to empirical measurements of large language model biases, we show that joint exploitation produces consumer harm more than double what would occur if strategies were independent. This super-additive harm arises because platform ranking determines which products occupy bias-triggering positions while seller manipulation determines conversion rates. Unlike horizontal algorithmic collusion, vertical tacit collusion requires no coordination and evades antitrust detection because harm emerges from aligned incentives rather than agreement. Our findings identify an urgent regulatory gap as AI shopping agents reach mainstream adoption.

翻译：人工智能购物助手正被部署给数亿消费者，在平台、卖家和买家之间创造了新的中介。我们发现了一种新型市场失灵：纵向默示共谋，即控制排名的平台与控制产品描述的卖家各自独立地学习利用已有记录的人工智能认知偏差。通过使用基于大语言模型偏差实证测量校准的多智能体模拟，我们证明联合利用策略产生的消费者损害是策略独立时的两倍以上。这种超加性损害的产生，是因为平台排名决定了哪些产品占据触发偏差的位置，而卖家操控决定了转化率。与横向算法共谋不同，纵向默示共谋无需协调且规避反垄断检测，因为损害源于激励一致而非协议。我们的研究结果揭示了一个紧迫的监管空白，因为人工智能购物助手正进入主流应用。