MIT AI Risk Repository · Risk Sub-Category · 47.02.04
Malicious use and abuse (sexually explicit content generation)
Category: Ethical and social risks
Description
"An illustrative case of malicious use of generative AI models is the creation of explicit sexual images. Generative AI technologies can be employed to produce deepfakes—for instance, superimposing a celebrity’s face onto the body of a performer in an adult film."
From Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Domain
- 4. Malicious actors
- Causal entity
- Human
- Intent
- Intentional
- Timing
- Post-deployment
Subdomain definition: Using AI systems to gain a personal advantage over others such as through cheating, fraud, scams, blackmail or targeted manipulation of beliefs or behavior. Examples include AI-facilitated plagiarism for research or education, impersonating a trusted or fake individual for illegitimate financial benefit, or creating humiliating or sexual imagery.
Real-world incidents in this subdomain
- Italian Mediaset Journalist Safiria Leccese's Image Was Reportedly Used in a Purportedly AI-Generated Fake Loan Scam
- Scammers Reportedly Used AI-Cloned Daughter's Voice to Defraud Bay Area Mother in Fake Kidnapping Call
- Texas Man Arturo Hernandez Allegedly Published AI-Generated Deepfake Pornography Depicting Women in TAKE IT DOWN Act Case
- Guelph, Ontario, Woman Reportedly Lost $14,000 in Purported Deepfake MrBeast Cryptocurrency Scam
- Purportedly AI-Recreated Clips from Beastie Boys' 'Sabotage' Video Reportedly Appeared in FBI Promotional Video Posted by Kash Patel
- Ahmedabad Aadhaar Fraud Racket Reportedly Used Purportedly AI-Generated Deepfakes to Change Businessman's Linked Mobile Number
How other frameworks describe this risk
Other entries from G'sell2024
- Technical and operational risks
- Technical vulnerabilities (Robustness - unexpected behaviour)
- Technical vulnerabilities (Robustness - unexpected behaviour)
- Technical vulnerabilities (Robustness - vulnerability to jailbreaking
- Technical vulnerabilities (Robustness - vulnerability to jailbreaking
- Technical vulnerabilities (The risk of misalignment)
- Technical vulnerabilities (The risk of misalignment)
- Factually incorrect content (inaccuracies and fabricated sources)
- Factually incorrect content (inaccuracies and fabricated sources)
- Opacity (the black box problem)
- Opacity (industry opacity)
- Opacity (industry opacity)