Google Shows When AI Makes Ads
Google Shows When AI Makes Ads
Google 將顯示 AI 生成的廣告標記
Introduction
Google now tells people when AI makes or changes an advertisement.
Google 現在會告知使用者，哪些廣告是由 AI 生成或修改的。
Main Body
Companies use AI to make ads. This saves money and time. But some people cannot tell if a photo is real. Now, Google will show a label on these ads in Search, YouTube, and Discover.
公司使用 AI 製作廣告，這樣可以節省金錢與時間。但有些人無法分辨照片是否為真實。因此，Google 現在會在搜尋、YouTube 和 Discover 的這些廣告上顯示標記。
Users can find this information in 'My Ad Center'. They click a small icon to see 'how this ad was made'. This tells them if AI helped make the picture.
使用者可以在「我的廣告中心」找到此資訊。他們點擊一個小圖示即可查看「此廣告是如何製作的」，藉此了解照片是否由 AI 協助製作。
Google labels ads made with its own AI tools automatically. But if a company uses a different AI tool, the company must add the label. Google does not check every ad.
使用 Google 自身 AI 工具製作的廣告將被自動標記。但如果公司使用其他 AI 工具，則必須由公司自行添加標記。Google 並不會檢查每一則廣告。
Other companies like Meta also do this. Google uses new tools to find fake videos and photos. This helps people know what is real.
其他公司如 Meta 也是如此。Google 使用新工具來偵測偽造的影片與照片，幫助人們辨別真實內容。
Conclusion
Google now asks all advertisers to show if they use AI.
Google 現在要求所有廣告主都必須標示是否使用 AI。
Vocabulary Learning
🛠️ Action Words (Verbs)
Look at how we describe things happening right now. We use simple words to explain a process:
- Use Companies use AI. (They employ a tool)
- Show Google will show a label. (To make something visible)
- Find Users can find information. (To discover something)
💡 Word Connections
In English, we often put a 'helper' word before a main action to change the meaning. Check these pairs from the text:
| Helper Word | Action | Meaning |
|---|---|---|
| Can | tell | It is possible to know |
| Will | show | It happens in the future |
| Must | add | It is a rule/necessary |
Vocabulary Learning
Google Introduces New AI Disclosure Rules for Advertisements
Google 推出廣告 AI 揭露新規定
Introduction
Google has launched a new system to inform users when advertisements have been created or changed using artificial intelligence.
Google 推出了一套新系統，當廣告使用人工智慧（AI）創建或修改時，將會通知用戶。
Main Body
Using generative AI in ads helps companies lower the costs of product photography and create a wider variety of images. However, because customers might be confused about whether a product image is real, Google has decided to create a standard way to disclose AI use. While these rules previously only applied to political ads, they now cover all commercial content on Google Search, YouTube, and Google Discover.
在廣告中使用生成式 AI 有助於公司降低產品攝影成本，並創造更多樣化的影像。然而，由於顧客可能會對產品圖片是否真實感到困惑，Google 決定建立一套標準方式來揭露 AI 的使用情況。這些規定先前僅適用於政治廣告，現在則涵蓋 Google 搜尋、YouTube 和 Google Discover 上所有的商業內容。
Users can find this information in the 'My Ad Center' by clicking the information icon or the three-dot menu. In the 'how this ad was made' section, Google explains if AI was used to produce or edit the ad. Google will automatically label content made with its own AI tools; however, advertisers must manually label content made with external tools, as Google will not verify the origin of the media. Furthermore, in some countries, these labels will appear directly on the ad to follow local laws.
用戶可以在「我的廣告中心」中，透過點擊資訊圖示或三個點的選單來找到此資訊。在「這則廣告是如何製作的」區塊中，Google 會說明是否使用 AI 來製作或編輯廣告。若內容是使用 Google 自家 AI 工具製作的，Google 將自動標記；但廣告主必須手動標記使用外部工具製作的內容，因為 Google 不會驗證媒體的來源。此外，在某些國家，為了遵守當地法律，這些標記將直接顯示在廣告上。
This change follows a general trend in the industry, similar to the 'AI info' labels used by Meta. Additionally, Google is expanding its use of SynthID and C2PA labels, which are tools designed to help people detect deepfake media.
此項變動符合行業的整體趨勢，類似於 Meta 所使用的「AI 資訊」標記。此外，Google 正擴大使用 SynthID 和 C2PA 標記，這些工具旨在幫助人們偵測深偽（deepfake）媒體。
Conclusion
Google has now extended its AI disclosure rules to all advertisements, using both automatic and manual labeling to increase transparency.
Google 現已將 AI 揭露規定擴展至所有廣告，透過自動與手動標記來增加透明度。
Vocabulary Learning
🚀 Moving Beyond 'But' and 'And'
To move from A2 to B2, you need to stop using simple connectors and start using Contrast & Addition markers. This makes your English sound professional and fluid rather than like a list of sentences.
🌓 The Power of 'However' & 'While'
In the text, we see: "However, because customers might be confused..."
At A2, you would say: "But customers might be confused." At B2, we use However to signal a shift in logic. It creates a sophisticated pause.
The 'While' Trick: "While these rules previously only applied to political ads, they now cover all commercial content..."
Instead of saying "These rules were for politics, but now they are for everyone," using While at the start of the sentence allows you to balance two opposing ideas in one breath. This is a hallmark of B2 fluency.
➕ Leveling Up Your Addition
Stop using 'And' or 'Also' every time you add information. Look at the professional alternatives used in the article:
- Furthermore: (Used when adding a point that is more important or detailed than the last).
- Example: "Google will label its own tools; furthermore, in some countries, labels appear directly on the ad."
- Additionally: (A cleaner, more academic way to say 'also').
- Example: "Additionally, Google is expanding its use of SynthID..."
🛠️ Quick Upgrade Map
| A2 (Basic) | B2 (Bridge) | Effect |
|---|---|---|
| But | However | Sounds more objective |
| Also | Additionally | Sounds more formal |
| And | Furthermore | Adds logical weight |
| But / And | While... | Creates complex sentence structures |
Vocabulary Learning
Implementation of Generative Artificial Intelligence Disclosure Protocols within Google Advertising Ecosystems.
在 Google 廣告生態系統中實施生成式人工智慧揭露協定
Introduction
Google has introduced a mechanism to notify users when advertisements have been synthesized or modified via artificial intelligence.
Google 推出了一項機制，用於在廣告經由人工智慧合成或修改時通知使用者。
Main Body
The integration of generative AI in commercial advertising facilitates the reduction of expenditures associated with physical product photography and the diversification of visual contexts. However, the potential for consumer disorientation regarding the authenticity of product imagery necessitates a standardized disclosure framework. Previously, the requirement for the identification of synthetic or digitally altered content was restricted to political advertisements; this mandate has now been extended to general commercial content across Google Search, YouTube, and Google Discover.
在商業廣告中整合生成式 AI 有助於減少與實體產品拍攝相關的支出，並使視覺場景更多樣化。然而，消費者可能會對產品影像的真實性產生誤導，因此需要一個標準化的揭露框架。此前，識別合成或數位修改內容的要求僅限於政治廣告；而現在此項要求已擴展至 Google 搜尋、YouTube 及 Google Discover 的一般商業內容。
Access to these disclosures is facilitated through the 'My Ad Center' interface, accessible via the information icon or the three-dot menu. Within this panel, the 'how this ad was made' section specifies whether AI was utilized in the production or editing of the asset. Regarding the mechanism of attribution, Google will automatically apply these labels to content generated via its proprietary AI tools. Conversely, for assets produced through external platforms, the responsibility for disclosure resides with the advertiser, as Google will not conduct independent verification of the content's origin. Furthermore, in specific jurisdictions, these labels may be displayed directly on the advertisement to ensure compliance with local statutory requirements.
使用者可透過「我的廣告中心」介面，經由資訊圖標或三點選單查看這些揭露資訊。在該面板中，「此廣告如何製作」部分會說明在素材的製作或編輯過程中是否使用了 AI。關於歸屬機制，對於使用 Google 專有 AI 工具生成的內容，Google 將自動套用這些標籤。相反地，對於透過外部平台製作的素材，揭露責任由廣告主承擔，因為 Google 不會對內容來源進行獨立驗證。此外，在特定司法管轄區，這些標籤可能會直接顯示在廣告上，以確保符合當地法定要求。
This strategic shift aligns Google with broader industry trends, mirroring the 'AI info' labels employed by Meta. The initiative is further augmented by the expansion of SynthID and C2PA content labels, which are designed to facilitate the detection of deepfake media.
這一策略轉移使 Google 與更廣泛的產業趨勢保持一致，呼應了 Meta 所採用的「AI 資訊」標籤。此舉透過擴展 SynthID 與 C2PA 內容標籤而得到進一步強化，旨在提升對深偽（deepfake）媒體的偵測能力。
Conclusion
Google has expanded its AI disclosure requirements to all advertisements, utilizing a combination of automated and manual labeling systems.
Google 已將其 AI 揭露要求擴展至所有廣告，結合了自動與手動標記系統。
Vocabulary Learning
⚡ The Architecture of Nominalization and Precision
To migrate from B2 (functional fluency) to C2 (academic/professional mastery), one must pivot from verb-centric descriptions to noun-centric conceptualization. The provided text is a masterclass in Nominalization—the process of turning verbs or adjectives into nouns to increase density and objectivity.
🔍 The Linguistic Shift
Compare these two versions of the same concept:
- B2 Style: "Google wants to stop users from being confused about whether a product image is real or not, so they made a system for disclosure."
- C2 Style: "The potential for consumer disorientation regarding the authenticity of product imagery necessitates a standardized disclosure framework."
In the C2 version, the action (confusing the user) becomes a concept (consumer disorientation). This allows the writer to manipulate the sentence structure with surgical precision.
🛠️ Deconstructing the 'C2 Power-Phrases'
| Nominalized Phrase | Source Verb/Adj | C2 Function |
|---|---|---|
| The integration of generative AI | To integrate | Transforms a process into a subject for analysis. |
| The diversification of visual contexts | To diversify | Elevates a simple action to a strategic objective. |
| Independent verification | To verify independently | Replaces a phrase with a compound noun for formal weight. |
| Local statutory requirements | Being required by law | Shifts from a description to a legal category. |
🎓 Masterclass Insight: The 'Necessitates' Pivot
Notice the usage of "necessitates." A B2 student would likely use "means that... is needed" or "requires."
By using necessitates, the author links a noun phrase (the potential for disorientation) directly to another noun phrase (a standardized disclosure framework). This creates a logical bridge that feels inevitable and authoritative, rather than merely descriptive. This is the hallmark of high-level academic and corporate discourse: removing the human agent to emphasize the systemic necessity.