The Malicious Technical Ecosystem: Exposing Limitations in Technical Governance of AI-Generated Non-Consensual Intimate Images of Adults
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912946620203008 |
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| author | Ding, Michelle L. Suresh, Harini |
| author_facet | Ding, Michelle L. Suresh, Harini |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2504_17663 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Malicious Technical Ecosystem: Exposing Limitations in Technical Governance of AI-Generated Non-Consensual Intimate Images of Adults Ding, Michelle L. Suresh, Harini Human-Computer Interaction Artificial Intelligence Computers and Society Machine Learning 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. |
| title | The Malicious Technical Ecosystem: Exposing Limitations in Technical Governance of AI-Generated Non-Consensual Intimate Images of Adults |
| topic | Human-Computer Interaction Artificial Intelligence Computers and Society Machine Learning |
| url | https://arxiv.org/abs/2504.17663 |