A new study published on September 24 in PLoS One has shown that average listeners can no longer reliably tell apart AI-generated “deepfake” voices from real human voices. Study Findings: AI vs. Human Voices Voice Cloning vs. From-Scratch AI: While generic AI voices made from scratch can still be spotted by most listeners (only 41% fooled), AI voice clones trained with real human samples are nearly indistinguishable : 58% of these deepfake voices were rated as genuine, compared to 62% for actual human voices. Minimal Data Needed: Researchers created convincing voice clones using as little as four minutes of audio and basic commercial software, requiring minimal expertise and cost. Security and Ethics Risks: Sophisticated deepfake voices make it easy for criminals to bypass voice authentication systems at banks, impersonate loved ones, or even fabricate public statements from politicians and celebrities. Example: A victim gave $15,000 after being tricked by a “daughter’s...
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