AI Scams in the USA

Jun 6, 2026, 19:23
USTechnology
A2

AI Scams in the USA

美國的 AI 詐騙

Introduction

Many people in the USA lost a lot of money. Bad people used AI to steal this money.

許多美國人損失了大量金錢。不法分子利用 AI 來盜取這些錢財。

Main Body

The FBI says people lost 900 million dollars in 2025. Bad people use AI to make fake videos and voices. They pretend to be family or government workers. This makes the lies look real.

FBI 表示 2025 年人們共損失了 9 億美元。不法分子利用 AI 製作虛假影片和聲音，偽裝成家人或政府職員，讓謊言看起來非常真實。

Young people are now targets too. People under 20 years old have more problems now. AI helps bad people send thousands of fake messages every minute.

現在年輕人也成了目標。20 歲以下的人目前面臨更多問題。AI 幫助不法分子每分鐘能發送數以千計的虛假訊息。

Some people want the government to punish the companies that make AI. The FBI says you must check who is calling you. Do not put too much personal information online.

有些人希望政府懲罰開發 AI 的公司。FBI 提醒您必須核實來電者的身分，不要在網上公開過多個人資訊。

Conclusion

AI scams are growing. Everyone must be very careful and report these crimes.

AI 詐騙正持續增加。每個人都必須非常小心並舉報這些犯罪行為。

Vocabulary Learning

🔍 Focus: 'Action Words' for the Present

In the text, we see words like lost, used, and says. Let's look at how we talk about things happening now versus things that already happened.

The Pattern: Now vs. Then

  • Right Now (Present):
    • The FBI says... →\rightarrow (This is a fact today)
    • AI helps... →\rightarrow (This happens every day)
  • Finished (Past):
    • People lost money... →\rightarrow (It happened already)
    • Bad people used AI... →\rightarrow (The action is over)

🛠️ Word Building: 'The-Word' and 'A-Word'

Notice how the writer uses these small words to point at things:

  1. A / An (Any one) →\rightarrow a lot of money, a fake video
  2. The (A specific one) →\rightarrow the USA, the FBI, the companies

Quick Tip: Use 'the' when the other person knows exactly which thing you are talking about!

Vocabulary Learning

scams (n.)
Dishonest plans to get money from people
Example:Be careful of phone scams that ask for your bank details.
pretend (v.)
To act like someone or something you are not
Example:The bad person tried to pretend he was a police officer.
targets (n.)
People or things that are attacked or chosen
Example:Young people are often targets for online scams.
punish (v.)
To make someone suffer for doing something wrong
Example:The judge will punish the thief with a fine.
personal information (n.)
Private details about a person, like a home address
Example:Do not share your personal information with strangers.
report (v.)
To tell the police or an official person about a crime
Example:You should report the crime to the FBI immediately.
B2

The Rise of AI-Powered Financial Fraud in the United States

美國 AI 驅動金融詐騙崛起

Introduction

Recent data shows a significant increase in financial losses for American citizens because criminals are now using artificial intelligence in their scams.

最近的數據顯示，由於犯罪分子現在在詐騙中使用了人工智慧，美國公民的財務損失顯著增加。

Main Body

The FBI reported that AI-driven scams caused losses of approximately $900 million in 2025, with over 22,000 reports filed. This shows a shift from basic digital fraud to a more advanced method where generative AI creates realistic fake media. For example, criminals use deepfake audio and video to impersonate family members, famous people, and government officials, which makes their fake requests seem more believable.

FBI 報告指出，2025 年 AI 驅動的詐騙造成了約 9 億美元的損失，共有超過 22,000 份報告被提交。這顯示了詐騙手法已從基本的數位詐騙轉向更進階的方法，即利用生成式 AI 創造逼真的虛假媒體。例如，犯罪分子使用深偽 (deepfake) 音訊和影片來冒充家人、名人以及政府官員，使他們的虛假請求看起來更具可信度。

Analysis shows that these scams are targeting a wider range of people. While older people were previously the main targets, the FBI noted a 74 percent increase in complaints from people under 20 between 2024 and 2025. This suggests that being comfortable with technology does not protect someone from being tricked. Furthermore, AI allows criminals to send tens of thousands of automated messages per minute, making the attacks much larger in scale.

分析顯示，這些詐騙針對的對象範圍更廣。雖然以往主要對象是年長者，但 FBI 注意到 2024 年至 2025 年間，20 歲以下人士的投訴增加了 74%。這顯示對科技的熟悉程度並不能保護一個人免於被騙。此外，AI 讓犯罪分子每分鐘能發送數萬條自動化訊息，使攻擊規模大幅擴大。

In response, organizations are focusing on public education and corporate responsibility. A petition signed by 75,000 people was sent to the Federal Trade Commission, demanding that developers of voice-cloning technology be held responsible. Meanwhile, the FBI and banks have advised people to use strict identity verification and limit the personal information they share online to reduce the risk of being impersonated.

對此，相關機構正將重點放在公眾教育與企業責任上。一份由 75,000 人簽名的請願書被提交至聯邦貿易委員會，要求聲音複製技術的開發者承擔責任。同時，FBI 和銀行建議民眾使用嚴格的身份驗證，並限制在網上分享的個人資訊，以降低被冒充的風險。

Conclusion

The current situation is defined by a growing number of advanced AI scams targeting all age groups, which means people must be more careful and report these crimes immediately.

目前的狀況是針對所有年齡層的高階 AI 詐騙日益增加，這意味著人們必須更加小心，並立即舉報此類犯罪。

Vocabulary Learning

🚀 The 'Cause & Effect' Jump

To move from A2 to B2, you need to stop using only simple words like because and so. You need to show how one thing leads to another using sophisticated transitions.

The Pattern: "A leads to B"

Look at this sentence from the text:

"AI allows criminals to send tens of thousands of automated messages per minute, making the attacks much larger in scale."

Instead of saying: "AI allows criminals to send many messages, so the attacks are larger," the author uses a comma + -ing structure. This is a classic B2 move. It connects the action to the result instantly.

🛠️ Level-Up Your Vocabulary

In A2, we use basic adjectives. In B2, we use precise modifiers to describe trends. Let's steal these from the article:

  • Significant increase →\rightarrow (Don't just say "big increase").
  • Wider range →\rightarrow (Don't just say "more people").
  • Strict verification →\rightarrow (Don't just say "good checking").

🧠 Logic Shift: The 'Contrast' Bridge

Notice this phrase:

*"While older people were previously the main targets..."

Using "While" at the start of a sentence is a powerful way to compare two different facts. It tells the reader: "I am about to give you two pieces of information that surprise each other."

Try thinking like this:

  • A2: Older people were targets. Now young people are targets too.
  • B2: While older people were once the primary targets, young people are now increasingly at risk.

Vocabulary Learning

significant (adj.)
Large or important enough to be noticed or have an effect.
Example:There has been a significant increase in the number of people working from home.
impersonate (v.)
To pretend to be another person by copying their voice or appearance.
Example:The fraudster tried to impersonate a bank manager to steal the client's password.
believable (adj.)
Something that is easy to accept as true or real.
Example:The actor gave a very believable performance as a historical leader.
automated (adj.)
Controlled by a machine or computer rather than a human.
Example:Many factories now use automated systems to assemble products quickly.
corporate responsibility (n.)
The idea that businesses should act in a way that benefits society and the environment.
Example:The company's corporate responsibility program focuses on reducing plastic waste.
verification (n.)
The process of proving that something is true, accurate, or legal.
Example:The app requires a phone number for identity verification before you can log in.
C2

The Proliferation of Artificial Intelligence-Enhanced Financial Fraud in the United States

美國人工智能強化金融詐騙的激增現象

Introduction

Recent data indicates a substantial increase in the financial losses incurred by American citizens due to the integration of artificial intelligence into fraudulent schemes.

最近的數據顯示，由於人工智能被整合至詐騙計劃中，美國公民所遭受的財務損失大幅增加。

Main Body

The Federal Bureau of Investigation (FBI) has documented a fiscal loss of approximately $900 million in 2025 attributed to AI-driven scams, with over 22,000 reports filed via the Internet Crime Complaint Center. This escalation represents a shift from traditional digital fraud to a more sophisticated paradigm where generative AI facilitates the creation of high-fidelity synthetic media. The deployment of deepfake audio and video has enabled the impersonation of familial relations, public figures, and government officials, thereby enhancing the perceived legitimacy of fraudulent solicitations.

聯邦調查局（FBI）記錄到 2025 年因 AI 詐騙而造成的財政損失約 9 億美元，而透過網路犯罪投訴中心提交的報告超過 22,000 份。這種升級代表著從傳統數位詐騙轉向一個更複雜的模式，而生成式 AI 促進了高保真合成媒體的創建。深偽（deepfake）音訊與影片的部署，使得冒充親屬、公眾人物及政府官員成為可能，從而提升了詐騙請求的感知合法性。

Stakeholder analysis reveals a diversification in target demographics. While technological fraud historically targeted older populations, the FBI reports a 74 percent increase in complaints from individuals under the age of 20 between 2024 and 2025. This trend suggests that digital fluency does not equate to immunity from social engineering. Furthermore, the operationalization of AI has permitted the rapid scaling of fraudulent communications; experts note a transition from sporadic incidents to the dissemination of tens of thousands of automated messages per minute.

利害關係人分析顯示，目標對象呈現多元化。雖然科技詐騙歷史上主要針對高齡人口，但 FBI 報告指出 2024 年至 2025 年間，20 歲以下個體的投訴增加了 74%。這一趨勢表明，數位流暢度並不等同於對社交工程的免疫力。此外，AI 的操作化使得詐騙通訊能快速規模化；專家指出，詐騙已從零星事件轉型為每分鐘散布數萬條自動化訊息。

Institutional responses have focused on public education and the advocacy for corporate accountability. A petition involving 75,000 signatories was submitted to the Federal Trade Commission to establish liability for developers of voice-cloning technology. Concurrently, the FBI and financial institutions have recommended the implementation of rigorous identity verification protocols and the limitation of personal data exposure to mitigate the risk of synthetic impersonation.

機構回應重點在於公眾教育及倡導企業問責。一份包含 75,000 名簽署者的請願書已提交至聯邦貿易委員會，旨在為聲紋複製技術的開發者確立責任。同時，FBI 與金融機構建議實施嚴格的身份驗證協定，並限制個人資料外流，以降低合成冒充的風險。

Conclusion

The current landscape is characterized by an increasing volume of sophisticated AI scams targeting a broad demographic, necessitating heightened vigilance and systemic reporting.

目前的格局是以針對廣泛人口的複雜 AI 詐騙數量增加為特徵，因此需要提高警覺並建立系統性的報告機制。

Vocabulary Learning

The Architecture of Nominalization and Formal Precision

To ascend from B2 to C2, a learner must transition from action-oriented prose (verbs) to concept-oriented prose (nouns). The provided text is a masterclass in Nominalization, the process of turning verbs or adjectives into nouns to create a dense, objective, and academic register.

⚡ The C2 Pivot: From Event to Entity

Observe how the text avoids simple narrative descriptions in favor of conceptual nouns. This strips away the 'story' and replaces it with 'analysis'.

  • B2 Approach: AI is being used more, so more people are losing money. (Focus on action/people)
  • C2 Approach: "The proliferation of Artificial Intelligence-Enhanced Financial Fraud..." (Focus on the phenomenon)

Analysis of the 'Heavy' Nouns:

  • "Operationalization": This isn't just 'using' AI. It refers to the systemic process of making a concept or tool functional on a large scale.
  • "Dissemination": A precise alternative to 'spreading', implying a strategic or wide-scale distribution.
  • "Integration": Rather than saying 'they put AI into scams', the text uses integration to describe the seamless merging of two systems.

🛠️ Linguistic Deconstruction: The 'Noun Phrase' Chain

C2 English often employs long strings of nouns that act as adjectives. This creates a high information density that is characteristic of white papers and legal documentation.

*"...high-fidelity synthetic media"

Breakdown: High-fidelity (Modifier) →\rightarrow synthetic (Modifier) →\rightarrow media (Head Noun).

When you produce this, you are no longer describing an object; you are defining a category.

🎓 Strategic Application for the Student

To replicate this level of sophistication, target your verbs. Whenever you see a verb phrase, ask: "Can I transform this into a noun to make the sentence more objective?"

Instead of (B2/C1)Try (C2)
They are targeting more people.A diversification in target demographics.
The risk is getting worse.An escalation of the risk profile.
They want to make developers responsible.The advocacy for corporate accountability.

The C2 Rule of Thumb: The fewer pronouns (I, you, they) and the more abstract nouns (proliferation, operationalization, implementation) you use, the more you move toward the 'Academic Peak' of English proficiency.

Vocabulary Learning

proliferation (n.)
A rapid increase in the number or amount of something.
Example:The proliferation of smartphones has fundamentally changed how people communicate globally.
incurred (v.)
To experience something unpleasant, such as a loss, as a result of one's own actions.
Example:The company incurred massive debts during the economic downturn.
paradigm (n.)
A typical example or pattern of something; a model or a distinct set of concepts.
Example:The shift toward remote work represents a new paradigm in professional employment.
high-fidelity (adj.)
The high-quality reproduction of sound or visual data that is very close to the original.
Example:The studio used high-fidelity recording equipment to capture every nuance of the performance.
solicitations (n.)
The act of asking for or trying to obtain something from someone.
Example:The charity faced criticism for its aggressive solicitations for donations.
operationalization (n.)
The process of putting a plan, system, or concept into operation or making it functional.
Example:The operationalization of the new security protocol took several months to complete.
dissemination (n.)
The act of spreading something, especially information, widely.
Example:The rapid dissemination of the news via social media led to widespread public concern.
mitigate (v.)
To make something bad less severe, serious, or painful.
Example:The government implemented new drainage systems to mitigate the effects of seasonal flooding.
Practice All words in a crossword→