The term 'deepfake' combines 'deep learning' and 'fake.' Initially, deepfakes required substantial computational resources and expertise; today, smartphone applications can generate convincing face-swaps in seconds. The vast majority of deepfake content found online is non-consensual sexual material featuring women. Research from Sensity AI has found that 96% of deepfake videos are non-consensual pornography.

Key facts about this term

  1. Deepfakes use generative AI to create realistic likenesses Modern deepfakes employ diffusion models or GANs to produce highly realistic images or videos. A single photograph of a person can be sufficient to generate thousands of synthetic intimate images.
  2. Deepfake intimate imagery is a growing concern AI-generated and synthetic intimate images can depict individuals without their consent, impacting many victims.
  3. Biometric detection identifies deepfakes across platforms ScanErase utilizes facial recognition and image fingerprinting to discover deepfake content featuring your likeness, even when the AI output has been altered, compressed, or re-uploaded.

Frequently asked questions

Do I need an original intimate image to have been targeted by a deepfake?

No. Deepfakes require only a photo of your face, which is often publicly available on social media for most individuals. Your face can be placed onto someone else's body without any intimate image of you ever being present.

How can I tell if an image of me is a deepfake?

Common indicators of deepfakes include unnatural skin texture, lighting discrepancies, blurred edges around the hairline, and facial geometry errors. However, high-quality deepfakes may be indistinguishable to the naked eye. ScanErase's detection system employs biometric analysis rather than visual inspection.

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