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#MyFirstSquarePost  您好，幣安廣場！

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U.S. Senators Inquire About FTC’s Position On AI Scams Affecting Senior Citizens #DATA Senators asked four pointed questions on the FTC’s data gathering techniques for AI scams in an effort to grasp the agency’s stance. In an effort to learn more about the FTC’s efforts to counteract the use of AI in scams aimed at the elderly, four senators from the United States have sent a letter to Chair Lina Khan, asking for details on these programs. Four senators—Robert Casey, Richard Blumenthal, John Fetterman, and Kirsten Gillibrand—stated that preventing fraud made possible by artificial intelligence must be a top priority. While writing to one another, the senators stressed the need to fully understand the scale of the AI-driven scam danger so that appropriate remedies may be developed. Their request was for the FTC to provide information about its AI-related scam data collection operations and the steps it takes to verify that the Sentinel database accurately represents these schemes. To aid federal, state, and local law enforcement in their fight against many types of fraud, the FTC has developed Consumer Sentinel, an investigative cyber tool. The senators wanted to know how the FTC collected data on AI scams, so they asked four pointed questions. Their first question concerned the FTC’s capacity to detect and correctly label AI-powered frauds in the Sentinel database. Additionally, they wanted to see whether the FTC could spot generative AI schemes that victims might miss. Additionally, the legislators sought an in-depth analysis of Sentinel’s data to determine the prevalence and effectiveness of different kinds of scams. This investigation is only one of Senator Casey’s many responsibilities; he also chairs the Senate Special Committee on Aging, which investigates problems faced by the nation’s senior citizens. In related news, fifteen countries, including the US, UK, and Australia, published worldwide recommendations on November 27 to prevent the manipulation of artificial intelligence (AI) models. Making sure AI models are “secure by design.” is emphasize

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