Why is Google still serving dodgy ads?
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作者最近在 YouTube 应用中遇到一则伪装成 iOS 系统提示的欺骗性广告，谎称其 iPhone 存储已满。尽管作者举报该广告为欺诈，平台的审核系统却反复回复称内容并未违反其政策。这一令人沮丧的经历凸显了 Google 自动化或人工监管流程与实际投放给用户的广告质量之间存在严重脱节。
有人或许会猜测平台对那些表现好、利润高的广告睁一只眼闭一只眼，即便它们具有欺骗性，但更可能的情况是现行的审核机制已不堪重负或根本不够完善。广告平台本就难以做到万无一失，恶意方不断改进手法以规避自动过滤器。然而，该广告屡次未被下架，说明评估创意素材的方法论存在根本性问题。
讽刺的是，Google 拥有能够瞬间识别此类诈骗的先进 AI 模型。当作者将该欺骗性广告输入 Google 的 Gemini 模型时，AI 立刻判定其不合规。模型还给出详细的违规分析，指出其模仿系统界面元素、使用欺骗性且不可操作的界面按钮，以及通过恐吓手段迫使用户点击等问题。
这表明，用于保护用户免受掠夺性广告侵害的技术已经可用且非常有效。 Google 的审核过程未能得出与其自家 AI 相同的结论，说明在运营执行上存在失误。如果通用大型语言模型能在几秒钟内识别出明显违规，那么在多名用户举报后平台仍继续投放该广告就难以自圆其说。
作者呼吁更负责任地利用现有 AI 工具来弥合这一差距。将这些先进的分类能力整合到广告审核流程中，能使公司超越当前易出错的验证方法。当高性能 AI 已能承担内容审核重任时，仅依赖人工审核或过时的过滤系统已不再足够。
The author recently encountered a deceptive advertisement within the YouTube app that mimicked an official iOS system alert, falsely claiming that their iPhone storage was full. Despite reporting the advertisement as fraudulent, the platform's review system repeatedly returned messages stating the content did not violate their policies. This frustrating experience highlights a significant disconnect between the automated or human oversight processes at Google and the actual quality of the advertisements being served to users.
While one might speculate that the platform turns a blind eye to high-performing, profitable ads even when they are deceptive, it is more likely that current review protocols are simply overwhelmed or inadequate. Ad platforms are notoriously difficult to police perfectly, as malicious actors constantly refine their tactics to slip through automated filters. However, the recurring failure to remove this specific ad suggests that the current methodology for evaluating creative assets is fundamentally broken.
The irony is that Google possesses sophisticated AI models capable of identifying such scams in an instant. When the author fed the deceptive ad into Google's own Gemini model, the AI immediately classified it as disapproved. The model provided a detailed breakdown of policy violations, citing the mimicking of system UI elements, the use of deceptive, non-functional interface buttons, and the deployment of fear-based tactics designed to coerce user clicks.
This demonstrates that the technology to safeguard users from predatory advertising is already available and highly effective. The refusal of Google's review process to reach the same conclusion as its own AI model points to a failure in operational implementation. If a standard large language model can detect a blatant violation in seconds, there is little excuse for the platform to continue serving the ad after it has been flagged by multiple users.
Ultimately, the author calls for a more responsible use of existing AI tools to bridge this gap. By integrating these advanced classification capabilities into the ad review pipeline, companies could move beyond the limitations of current, error-prone verification methods. Relying on human reviewers or outdated filtering systems is no longer sufficient when high-performance AI is ready and able to perform the heavy lifting of moderating digital content.
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• Google 的广告基础设施被大量恶意、以诈骗为目的的广告占据，涵盖虚假系统警报、钓鱼链接和欺诈性消费产品。
• 自动化广告账户通过循环使用子域名和新建账号来规避黑名单，绕过平台防护；而 Google 的内部审核机制要么无视问题，要么放任不管。
• 巨额收入驱动了这一现象：诈骗广告主常以高于正规公司的出价竞得优质广告位，造成盈利动机与用户安全之间的直接冲突。
• 在 Section 230 等法律框架下缺乏明确责任，促成了大型广告平台的消极、不道德立场——它们把短期广告收入置于用户体验和平台完整性之上。
• 举报机制常被认为无效，许多用户反映投诉遭到忽视，甚至有情况下平台为保证广告投放周期而屏蔽针对特定恶意内容的举报功能。
• 技术对抗（如检测广告拦截器及反制技术）引发"军备竞赛"，使得网络对那些优先考虑安全与理性、而非持续暴露于掠夺性营销的用户愈发不友好。
• 诈骗广告的普遍性已将广告拦截从一种个人偏好转变为基本安全需求，尤其对于更容易被复杂心理操控欺骗的弱势群体而言更为重要。
• 尽管 AI 具备强大的恶意内容检测能力，但常被用于优化广告定向和创收，而非清理生态系统中的欺骗性或诈骗性创意内容。
• 对 Google 审核声明持专业怀疑的人认为，公司在制度上可能无力作为或不愿牺牲来自恶意行为者的高额收入。
• 消费者权力受到严重削弱，YouTube 和 Google Search 等平台占据主导地位，用户几乎没有其他选择，无法脱离依赖激进、以数据挖掘为核心且常含欺诈性的广告模式。
总体而言，讨论呈现出广泛共识：数字广告生态已从根本上崩溃，平台把来自欺诈活动的短期经济利益置于用户安全和平台诚信之上。参与者强调审核机制的系统性失败，并指出即便 AI 有能力识别诈骗，企业也选择不充分部署这些工具，因为其商业模式本质上依赖于高出价的恶意行为者所带来的收入。普遍情绪是对企业道德的无奈，许多人认为只有通过严格的法律责任和政府干预，才能迫使平台进行必要改革，保护消费者免受日益恶化且掠夺性的在线环境侵害。 • Google's ad infrastructure has become heavily saturated with malicious, scam-oriented advertisements, ranging from fake system alerts and phishing links to fraudulent consumer products.
• Automated ad accounts exploit the system by cycling through subdomains and new accounts, effectively bypassing blocklists while Google's internal moderation remains either indifferent or intentionally lenient.
• Significant revenue incentives drive these platforms, as scam advertisers often outbid legitimate companies for premium ad slots, leading to a direct conflict between profitability and user safety.
• The current lack of legal liability under frameworks like Section 230 allows large ad platforms to maintain a passive, amoral stance, prioritizing short-term ad revenue over the integrity of the user experience.
• Reporting mechanisms are frequently perceived as ineffective, with many users reporting that ad platforms ignore complaints or even remove the ability to report specific malicious content to ensure the ad cycle completes.
• Technical barriers, such as ad-blocker detection and "ad-blocker blockers," have created an arms race that makes the web increasingly hostile to users who prioritize security and sanity over constant exposure to predatory marketing.
• The pervasiveness of these scams has transformed ad-blocking from a preference into a fundamental safety necessity, particularly for vulnerable demographics who are more likely to be deceived by sophisticated psychological manipulation.
• AI, despite its high capability for detecting malicious content, is often repurposed to optimize ad targeting and revenue generation rather than cleaning the ecosystem of deceptive or fraudulent creatives.
• Professional skepticism toward Google's moderation claims suggests that the company is institutionally incapable or unwilling to sacrifice the high-margin revenue provided by bad-faith actors.
• Consumer power is significantly diminished, as the dominance of platforms like YouTube and Google Search leaves users with few alternatives that do not rely on aggressive, data-mining, and often fraudulent advertising models.
The discussion reflects a widespread consensus that the digital advertising landscape has become fundamentally broken, with platforms prioritizing short-term financial gains from fraudulent activity over user security or platform integrity. Participants highlight a systemic failure of moderation, noting that even when AI tools are capable of identifying scams, corporations choose not to deploy them effectively because their business models are inherently tied to the revenue generated by high-bidding malicious actors. The overall sentiment is one of resignation regarding corporate ethics, with many concluding that only strict legal liability and government intervention will force the necessary changes to protect consumers from an increasingly toxic and predatory online environment.