Search engines increasingly display LLM-generated answers shown above organic links, shifting search from link lists to answer-first summaries. Publishers contend these summaries substitute for source pages and cannibalize traffic, while platforms argue they are complementary by directing users through included links. We estimate the causal impact of Google's AI Overview (AIO) on Wikipedia traffic by leveraging the feature's staggered geographic rollout and Wikipedia's multilingual structure. Using a difference-in-differences design, we compare English Wikipedia articles exposed to AIO to the same underlying articles in language editions (Hindi, Indonesian, Japanese, and Portuguese) that were not exposed to AIO during the observation period. Across 161,382 matched article-language pairs, AIO exposure reduces daily traffic to English articles by approximately 15%. Effects are heterogeneous: relative declines are largest for Culture articles and substantially smaller for STEM, consistent with stronger substitution when short synthesized answers satisfy informational intent. These findings provide early causal evidence that generative-answer features in search engines can materially reallocate attention away from informational publishers, with implications for content monetization, search platform design, and policy.

翻译：搜索引擎越来越多地显示由大语言模型生成的回答，置于自然链接之上，将搜索从链接列表转变为以答案优先的摘要。出版商认为这些摘要替代了源页面并蚕食了流量，而平台则主张它们通过引导用户访问所含链接而具有互补性。我们通过利用该功能的分阶段地理部署和维基百科的多语言结构，估算了谷歌AI概览（AIO）对维基百科流量的因果影响。采用双重差分设计，我们将暴露于AIO的英文维基百科文章与同一篇文章在未暴露于AIO的语言版本（印地语、印度尼西亚语、日语和葡萄牙语）中进行比较。在161,382对已匹配的文章-语言对中，AIO暴露使英文文章每日流量减少约15%。影响存在异质性：文化类文章的相对下降幅度最大，而STEM类文章则显著较小，这与当简短合成回答满足信息性意图时替代效应更强的现象一致。这些发现提供了早期因果证据，表明搜索引擎中的生成式回答功能可能实质性地将注意力从信息性发布者那里重新分配，这对内容变现、搜索平台设计和政策制定具有重要影响。