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手机上线AI换脸检测功能,好用吗?实测三品牌:均未识别
Nan Fang Du Shi Bao· 2025-05-09 04:10
Core Insights - The rise of AI-generated content, particularly "deepfake" technology, has led to an increase in fraud cases, prompting calls for legislative action to regulate AI face-swapping and voice imitation [1][3][4] - Several smartphone manufacturers have introduced AI detection features to combat these fraudulent activities, but initial tests show that these features have not been effective in identifying AI-generated content [5][7] Group 1: Fraud Incidents and Economic Impact - From 2022 to early 2024, nearly 100 fraud cases involving "AI face-swapping" have occurred in China, resulting in economic losses totaling approximately 200 million yuan [3] - The Ministry of Industry and Information Technology has indicated that it is collaborating with mobile device manufacturers to launch risk alert features for AI face-swapping scams [3] Group 2: AI Detection Features by Manufacturers - Multiple smartphone brands, including Honor, Xiaomi, and OPPO, have integrated AI detection capabilities into their operating systems to identify potential AI-generated content during video calls [3][4] - Honor's MagicOS 9.0 includes an AI detection module for video calls, while Xiaomi's HyperOS 2.0 provides alerts for potential AI face-swapping and voice forgery risks [3][4] Group 3: Testing and Effectiveness of AI Detection - Tests conducted on Honor, Xiaomi, and OPPO smartphones revealed that none successfully identified AI-generated videos or audio during simulated fraud scenarios [5][7] - Honor's detection feature prompted a user alert but ultimately failed to detect any AI manipulation, while Xiaomi and OPPO provided minimal feedback during the tests [7] Group 4: Expert Recommendations and User Awareness - Experts suggest that manufacturers should focus on promoting AI detection features as supplementary tools rather than definitive solutions, emphasizing the need for users to remain vigilant [8] - There are concerns regarding the responsibilities of manufacturers in ensuring user privacy and the effectiveness of their fraud detection claims, as well as the potential risks associated with ineffective detection [8]