Deepfake Dangers: The Marissa Tomei Case Study

Key findings include identification of primary crime categories linked to deepfakes, such as pornography, fraud, and information manipulation, alongside challenges like trust. Key findings show that participants have a hard time distinguishing a deepfake from a related authentic video, and that the deepfake's content distance from reality is a more likely. Deepfakes, an emergent type of threat falling under the greater and more pervasive umbrella of synthetic media, utilize a form of artificial intelligence/machine learning (ai/ml) to create. As deepfake technology continues to advance, it is likely to become even more difficult to distinguish between real and fake media. As deepfakes threaten to hit the mainstream across a range of harmful activity, from online child sexual exploitation and abuse (csea) to fraud and election interference, there is a.