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The Malicious Technical Ecosystem: Exposing Limitations in Technical Governance of AI-Generated Non-Consensual Intimate Images of Adults

Published: April 24, 2025 | arXiv ID: 2504.17663v1

By: Michelle L. Ding, Harini Suresh

Potential Business Impact:

Stops fake nude pictures from being made.

Business Areas:
Intelligent Systems Artificial Intelligence, Data and Analytics, Science and Engineering

In this paper, we adopt a survivor-centered approach to locate and dissect the role of sociotechnical AI governance in preventing AI-Generated Non-Consensual Intimate Images (AIG-NCII) of adults, colloquially known as "deep fake pornography." We identify a "malicious technical ecosystem" or "MTE," comprising of open-source face-swapping models and nearly 200 "nudifying" software programs that allow non-technical users to create AIG-NCII within minutes. Then, using the National Institute of Standards and Technology (NIST) AI 100-4 report as a reflection of current synthetic content governance methods, we show how the current landscape of practices fails to effectively regulate the MTE for adult AIG-NCII, as well as flawed assumptions explaining these gaps.

Country of Origin
🇺🇸 United States

Page Count
4 pages

Category
Computer Science:
Human-Computer Interaction