U.S. News
Over $1 billion stolen from elderly in 2022 through AI-powered scams
By Jake Beardslee · November 20, 2023
In brief…
- Over $1 billion lost by seniors to largely AI-enabled scams in 2022
- Scammers used AI to impersonate family members begging for money
- Victims urged new laws to address unregulated AI voice cloning tech
- Elderly disproportionately targeted by online fraud according to FTC
- Many victims unwilling to report due to embarrassment
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A new report from the Senate Special Committee on Aging reveals that older Americans lost over $1 billion to scams in 2022, many of which utilized artificial intelligence (AI) to impersonate victims’ loved ones. As Senator Bob Casey (D-PA), chairman of the committee, stated, “As a parent and grandparent, I relate to the fear and concern these victims must feel.”
The annual report highlights the top 10 categories of scams reported last year, with “financial impersonation and fraud” taking the top spot. The most prevalent method was using AI to mimic familiar voices and make urgent pleas for money. As witness Dr. Tahir Ekin explained, cloning a victim’s loved one’s voice “catapults [the scams’] believability and emotional appeal.”
One couple featured in the committee hearing received a distraught call from who they thought was their daughter, begging for help between sobs. “It sounded exactly like her,” said victim Terry Holtzapple, according to Fox News Digital. Similarly, attorney Gary Schildhorn nearly wired $9,000 before confirming with his daughter-in-law that the call from his “son” requesting bail money was a hoax. “There was no doubt in my mind that it was his voice on the phone - it was the exact cadence with which he speaks,” remarked Schildhorn.
With law enforcement unable to take action when no money is exchanged, Schildhorn urged new legislation to address these AI scams. As Senator Elizabeth Warren (D-MA) noted, reported losses are likely an underestimate due to victims’ reluctance to come forward. The Federal Trade Commission states that seniors are disproportionately targeted by online fraud.