Why is Google still serving dodgy ads? | atomic14

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Why is Google still serving dodgy ads?

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TLDR:
AI is really good at detecting deceptive adverts - why isn’t Google using it?
A couple of months ago I noticed this advert popping up in the YouTube app. The main reason I noticed it is that I accidentally clicked it - I knew I was running out of space on my iPhone and a minor lapse of concentration caught me out.

These things can slip through even the best review processes, so I did my internet duty and reported the advert.
The response I got back was less than satisfactory:

Again, sometimes things slip through the net and people don’t always check things properly, so I reported it again. And got the same response.
In fact, multiple people have reported this advert and received the same:

We found that the ad doesn’t go against Google’s policies, which prohibit certain content and practices that we believe to be harmful to users and the overall online ecosystem.

I’m a big fan of Hanlon’s razor.

Never attribute to malice that which is adequately explained by stupidity

However, if you were being uncharitable, you do have to question whether it’s in Google’s interest to remove adverts that get lots of clicks. After all, these adverts are probably performing well and bringing in lots of lovely 🤑.
A simpler explanation is that the people reviewing adverts cannot properly review everything so things get missed.
You can’t help thinking that AI should come to the rescue here. Given Google has some pretty good models - surely it can put them to use?
Here’s what Google’s Gemini has to say about the advert:

Classification: DISAPPROVED
Policy Violations:

Misrepresentation: Misleading Ad Design
Misrepresentation: Unreliable / Deceptive Claims

Detailed Reasons for Disapproval
1. Mimicking System Alerts / UI Elements (Misleading Ad Design)

The Violation: Google Ads policy strictly prohibits advertisements that imitate operating system dialogs, system warnings, error messages, or interactive system notifications.
The Evidence: The banner embedded inside the ad explicitly mimics an iOS system alert modal (“iPhone Storage is Full”) complete with standard iOS typography, container styling, and mock system buttons (“Yes” / “No”). This trick visually deceives users into believing their device is throwing a native system-level alert, coercing them to click.

2. Non-Functional / Deceptive UI Components

The Violation: Ads cannot feature non-functional or misleading interactive elements, such as fake dialog options, false close buttons, or radio choices that do not perform their implied system function.
The Evidence: The “Yes” and “No” options inside the graphic image are static visuals designed to capture clicks anywhere on the ad banner to trigger a store/landing page redirect, rather than acting as true system controls.

3. Deceptive Fear-Based Tactics & Unverified Claims

The Violation: Advertising policies forbid using deceptive claims or scare tactics to induce panic and force immediate user action.
The Evidence: Stating “If you don’t free up space soon, some features may not work properly” inside a fake system popup fabricates a urgent state of failure on the user’s personal device, misleading them about their hardware status to drive app installs.

Required Action
Disapprove the ad creative immediately. Issue a policy violation warning/disapproval flag to the advertiser account under Misrepresentation (Misleading Ad Design). Repeated violations of this nature may result in full account suspension for deceptive practices.

Google’s own model rejects the ad in seconds, yet Google’s review process approved it twice.
Come on, meatbags - use some of the amazing AI tools you have access to.

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« Detecting Claude and ChatGPT using letter counting.

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Chris Greening

Published 13 Sep 2026

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atomic14
A collection of slightly mad projects, instructive/educational videos, and generally interesting stuff.
Building projects around the Arduino and ESP32 platforms - we'll be exploring AI, Computer Vision, Audio, 3D Printing - it may get a bit eclectic...

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The author addresses the persistent issue of deceptive advertisements served by Google, focusing on the inadequacy of current review processes and proposing the utilization of artificial intelligence to combat this problem. The author recounts an experience where they noticed a deceptive advertisement on the YouTube app, which they reported, but subsequently received unsatisfactory responses. This led the author to question why such advertisements continue to appear, particularly when instances of deception are clearly visible.

The central argument posits that artificial intelligence is well-suited to detecting deceptive advertisements, suggesting that Google’s existing models, such as Gemini, are capable of identifying these violations. The author points to a specific example where Gemini classified an advertisement as disapproved due to several policy violations, specifically misrepresentation and deceptive claims.

These violations are detailed through specific examples of the deceptive ad's design. First, the advertisement mimicked operating system dialogs and user interface elements, specifically imitating an iOS system alert modal, complete with authentic typography and mock system buttons like “Yes” and “No.” This imitation is deemed a violation because it visually deceives the user into believing the advertisement originates from a native system-level alert, thereby coercing a click. Furthermore, the ad utilized non-functional or misleading interactive components, such as static graphic elements masquerading as functional dialog options, which do not perform the implied system function of system controls. Finally, the advertisement employed deceptive fear-based tactics by fabricating an urgent state of failure, such as claiming that features would malfunction if space was not freed immediately, to induce panic and force immediate user action.

The author criticizes the discrepancy between Google’s own AI disapproval and their manual review process, noting that the system rejected the ad in seconds while the human review process approved it twice. This observation suggests that the human review process is insufficient at catching these sophisticated deceptive practices. The text concludes by asserting that the failure to employ advanced AI tools, which Google possesses, to review advertisements undermines efforts to maintain the integrity of the online ecosystem, implying that relying on artificial intelligence is a necessary step for effective policy enforcement against deceptive advertising.