AI 智能体正以大量新请求涌入公共服务系统

随着 AI 让填写表格和提交投诉变得更加容易，全球公共服务机构正看到申请及其他请求数量大幅增长。

在英国，自 ChatGPT 推出以来，提交给住房监察专员的投诉数量增长超过一倍，从 2022 年的 2,600 件增至去年的略高于 7,000 件。美国消费者金融保护局（CFPB）同期收到的投诉增长了 5 倍。巴西的司法请愿和德国的议会请愿也出现了类似的跃升。

研究者 Chris Schmitz 正在追踪这一增长趋势，并将其视为他所称的“智能体洪泛”（agentic flooding）这一更广泛趋势的一部分。在一篇将于下月在 AI Ethics and Society conference 上发表的论文中，他考察了 11 个司法辖区内 84 个可能发生洪泛的不同案例，发现有广泛证据表明，AI 工具正在改变人们与公共服务互动的方式。

更棘手的问题在于应如何应对。虽然部分新增提交显然带有对抗性，但另一些则来自使用 AI 提交申请的正当申请人——如果没有 AI，他们原本可能会放弃申请。一些人或许会将这些新增申请视为 AI 生成的垃圾信息，但 Schmitz 认为，这是一次难得的机会，可以为 AI 时代重塑社会服务。

Schmitz 考察的服务范围从福利申请到正式司法上诉，但它们都提供了可由 AI 助手访问的在线服务。（完整数据集可参考此处。）出于方法论原因，Schmitz 的论文并未直接断言 AI 是新申请人激增的原因。但在这 84 个案例中，大多数呈现出同样的基本轨迹：2022 年前提交量大致持平，随后随着 AI 技术普及而以不断加快的速度增长。关键在于，大多数案例尚未看到这种增长放缓，这意味着其在未来数年可能仍会持续攀升。

在 Schmitz 看来，AI 能力和可用性的持续提高会带动使用量增加，这一点不难理解。

“人们正在发现这是可以做到的事，而且它正一点点变得更容易……以前，可能需要汇集大量背景信息，并非常精确地提示 ChatGPT 3.5；如今，可能只需要在 Claude app 中粘贴一封信，或拍下这封信的照片，就能一次性获得相当不错的回复，”他说。

这种数量上的跃升，类似于许多漏洞赏金服务去年经历的情况：企业发现自己的收件箱被由 LLM 生成的低质量报告淹没。这些报告很少包含重大安全问题，但企业仍有义务在报告到达后进行核验，因此带来了显著的资源消耗。公共服务机构也很容易面临类似问题：它们需要在相同预算下处理 5 倍于以往的申请人。

但与漏洞赏金项目遭遇的大量无价值提交不同，Schmitz 表示，公共服务中的大多数新增申请都来自拥有正当诉求的真实用户。

“在我们发现的绝大多数案例中，都是有权就某件事提出申请的人，正在为那件事提出申请，”他告诉 TechCrunch。

如果这些人此前没有申领相应福利，原因可能是申请工作过于令人望而却步——政策领域将此称为行政负担。如今 AI 能够减轻这种负担，这或许是以更适配 AI 的方式重塑许多此类服务的机会。

这是一项重大任务，而我们大多数人尚未真正着手应对；但 Schmitz 将其视为保持乐观的理由。

“让 AI 取得良好结果的重要部分，是能够具体描绘出事情理想状态下应有的样子。任何曾用 ChatGPT 报税的人都知道，这里存在一种好的版本：你能够获得帮助，”Schmitz 说，“这可能是一个契机，让我们说：‘我们需要重新思考这个流程几乎所有方面的形态。’”

As AI makes it easier to fill forms and file complaints, public services around the world are seeing enormous jumps in applications and other requests.

In the United Kingdom, complaints to the housing ombudsman more than doubled since the introduction of ChatGPT, rising from 2,600 in 2022 to just over 7,000 last year. The United States’ Consumer Financial Protection Bureau (CFPB) saw 5x growth in complaints over the same period. There were similar jumps in Brazilian judicial petitions and German parliamentary petitions.

Researcher Chris Schmitz is tracking this rise as part of a broader trend he called “agentic flooding.” In a paper set to be presented next month at the AI Ethics and Society conference, he looks at 84 different cases of potential flooding across 11 jurisdictions, finding broad evidence that AI tools are changing the way people interact with public services.

The harder question is what to do in response. While some of the new filings are clearly adversarial, others are the result of legitimate applicants using AI to file claims that would otherwise be abandoned. While some might see the new applications as AI-generated spam, Schmitz sees it as a rare opportunity to remake social services for the AI era.

Schmitz looked at services ranging from welfare applications to official judicial appeals, but they all have online services that could be accessed by an AI assistant. (The full dataset is hosted here, for reference.) For methodological reasons, Schmitz’s paper stops short of saying AI is directly causing the surge of new applicants. But most of the 84 cases follow the same basic arc, where submissions were roughly flat before 2022, then rose at increasing speed as AI technology diffuses. Crucially, most cases have not seen that growth slow down, suggesting it will likely keep rising for years to come.

For Schmitz, it’s easy to see how the increasing skills and availability of AI would drive increased usage.

“People are finding out that this is something one can do, and incrementally, it is just getting easier to do it … before it might have been a question of a lot of dragging context together and prompting ChatGPT 3.5 very precisely, it may now be a question of just pasting or taking a photo of a letter with your Claude app and getting a pretty good response in one shot,” he said.

The jump in volume is similar to what many bug-bounty services also experienced last year, as companies found their inboxes flooded with low-quality reports generated by LLMs. The reports rarely contained significant security issues, but companies were still obligated to vet the reports as they came in, presenting a significant drain on resources. It’s easy to imagine public services facing a similar problem, as they manage 5x more applicants with the same budget.

But where the bug bounty programs were flooded with worthless submissions, Schmitz says most of the new applications to public services are coming from real people with legitimate claims.

“The vast majority of cases we find are people who are entitled to claim for something, claiming for that thing,” he told TechCrunch.

If those people weren’t claiming the benefits before, it may have been because the work of applying was too forbidding — something known in the policy world as administrative burden. Now that AI can lift that burden, it could be an opportunity to remake many of these services in a more AI-friendly way.

It’s a major task, which we mostly haven’t begun to tackle, but Schmitz sees it as reason for optimism.

“A big part of making AI go well is being able to detail out what the good version of things looks like. And anyone who’s ever used ChatGPT to do the tax return knows that there’s a good version here where you’re being helped,” Schmitz says. “This could be the moment to say, ‘we need to rethink pretty much everything about how this process looks.’”