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Writer's pictureTimur Siraziev

AI-Generated Voice Scam in the US Tricks Woman into Sending Money.

Updated: Dec 9, 2024


In October 2024, a woman in the United States fell victim to a chilling scam involving AI-generated voice technology. This scam exploited her trust and cost her a significant amount of money.



The Setup

The scammers used AI to clone the voice of the woman’s son. She received a convincing audio message claiming he was in serious trouble and urgently needed financial help. The message sounded authentic and personal, making it difficult for her to doubt its validity.


The Hook

Believing her son was in danger, the woman quickly transferred money to the account provided by the scammers. The urgency and emotional manipulation in the message left her no time to question its authenticity.


The Loss

It was only later that the woman discovered her son had never sent the message and was completely safe. By then, the scammers had disappeared with the money she had sent, leaving her devastated and betrayed.


What to Learn

This case highlights the growing sophistication of AI scams, especially those using cloned voices. Scammers exploit the emotional connection and trust people have with their loved ones to deceive and manipulate.


Two Perspectives


Perspective 1: Technology Creates New Threats and Needs Regulation


Proponents of this view argue that technologies like AI-powered voice cloning are too dangerous to remain unchecked. Strict laws and tools for authenticity verification are needed to limit misuse.

  • Argument: If accessible tools for voice verification existed, such scams could be prevented.

  • Example: Companies and technology developers bear the responsibility for implementing protective measures.


Perspective 2: Education and Awareness Are the Key


Another perspective emphasizes that the issue lies not only in the technology but also in a lack of user awareness. If the woman had known about such scams, she might have verified the message before transferring money.

  • Argument: Users need to be educated about the risks and trained to respond effectively.

  • Example: A simple rule, like always calling and confirming directly, could have prevented this incident.

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