Many elderly residents in the United States have fallen victim to AI-driven scams. According to the Federal Trade Commission (FTC), scammers are utilizing AI technology to clone the voices of individuals known to the victims, resulting in a staggering loss of US$1.6 billion (Rp 24.6 trillion) throughout 2022.

Senator Elizabeth Warren has suggested that the actual losses may be higher, as many victims are reluctant to report the scams due to feelings of embarrassment. The proliferation of AI-driven scams is attributed to lax policies governing the implementation of such technology.

These scam cases have prompted members of the US Congress to expedite the passage of legislation regulating AI and other advanced technologies. This is aimed at safeguarding consumers from these highly convincing scams.

During a committee hearing, the top 10 shared scam categories included identity theft, financial fraud, robocalls, computer fraud, catfishing on dating apps, identity theft, and others. The most prominent AI-driven scam involves mimicking the voice of a known individual to call victims, family members, or loved ones to request money.

Testimonies during the hearing revealed instances where individuals received calls that sounded exactly like their loved ones in distress, injured, or held captive. One elderly couple received a call from someone they believed to be their daughter, who sounded distressed and in need of help.

Gary Schildhorn, a lawyer who fell victim to an AI voice cloning scam, nearly sent US$9,000 to the scammer until he confirmed with his daughter-in-law that it was an extortion attempt. The scammer, posing as a lawyer, called Schildhorn requesting funds to bail out his son from jail after causing a car accident and failing a breathalyzer test.

Tahir Ekin, PhD, Director of the State of Texas Data Analysis and Science Center, who testified at the hearing, stated that deliberate identity mimicry strategies would exploit their trust and emotional appeal. Therefore, prioritizing increased AI literacy and data among elderly Americans and actively involving them in prevention and detection efforts is crucial.