Record summary
A quick snapshot of what this page covers.
Risk profile
How this risk is described and categorized.
"Even when a victim of targeted, AIgenerated harms successfully identifies a deepfake creator with malicious intent, they may still struggle to redress many harms because the generated image or video isn’t the victim, but instead a composite image or video using aspects of multiple sources to create a believable, yet fictional, scene. At their core, these AI-generated images and videos circumvent traditional notions of privacy and consent: because they rely on public images and videos, like those posted on social media websites, they often don’t rely on any private information."
Suggested mitigations
Defenses that may help with related attacks.
Use Multi-Modal Sensors
Deepfake Detection
User Training
Control Access to AI Models and Data at Rest
Sanitize Training Data
Verify AI Artifacts
Maintain AI Dataset Provenance
Use Ensemble Methods
Validate AI Model
Code Signing
AI Model Distribution Methods
Source
Research source for this risk, when available.
Included resource
Generating Harms: Generative AI's Impact & Paths Forward
Original source
MIT AI Risk Repository
Open the public repository used for AI risk records and taxonomy fields.