AI incident #771 · 6 February 2020

Noelle Martin Deepfaked Without Consent in AI-Generated Pornography

Open on the AI Incident Database 1 news report Snapshot 7 Sep 2026

What happened

In 2017, Noelle Martin discovered explicit deepfake videos online that used AI technology to superimpose her face onto pornographic scenes. This incident was a continuation of the abuse she had experienced since at least 2012, when she first found doctored still images of herself in similar contexts. Despite the initial lack of legal protections, her advocacy efforts were instrumental in making image-based abuse a criminal offense in Australia.

Only the incident metadata is stored here. The underlying news reports are on the AI Incident Database (CC BY-SA 4.0); use the links above to read them.

News reports (1)

Coverage catalogued by the AI Incident Database. Titles link to the original publisher; the text is not reproduced here.

6 Feb 2020
Deepfake Porn Nearly Ruined My Life
elle.com · Daniella Scott · AIID #4019

Who was involved

Alleged deployer: Deepfake Creators
Alleged developer: Stanford University, Max Planck Institute, University Of Erlangen Nuremberg, Face2Face, Faceapp, Zao
Alleged harmed party: Noelle Martin

Classification (MIT AI Risk Repository taxonomy)

Risk domain: Malicious Actors & Misuse
Risk subdomain: 4.3 Fraud, scams, and targeted manipulation
Causal entity: AI
Intent: Unintentional
Timing: Post-deployment
Harm level: —
Sectors: —
Countries: —

Risk entries describing this failure mode

Entries from the MIT AI Risk Repository coded to subdomain 4.3.

Impersonation/identity theft
"Impersonation/identity theft - Theft of an individual, group or organisation’s identity by a third-party in order to defraud, mock or otherwise harm them."
A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)
IP/copyright loss
"IP/copyright loss - Misuse or abuse of an individual or organisation’s intellectual property, including copyright, trademarks, and patents."
A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)
Dehumanisation/objectification
"Dehumanisation/objectification - Use or misuse of a technology system to depict and/or treat people as not human, less than human, or as objects."
A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)
Defamation/libel/slander
"Defamation/libel/slander - Use of a technology system to create, facilitate or amplify false perception(s) about an individual, group, or organisation."
A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)
Financial and business
"Financial and Business - Use or misuse of a technology system in a manner that damages the financial interests of an individual or group, or which causes strategic, operational, legal or financial harm to a business or...
A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)
Cheating/plagiarism
"Cheating/plagiarism - Use of another person’s or group’s words or ideas without consent and/or acknowledgement."
A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)
Cybersecurity
"LLMs may exacerbate cybersecurity risks in various ways (Newman, 2024). Firstly, LLMs may significantly amplify the effectiveness of deceptive operations aimed at tricking people into disclosing sensitive information or...
Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)
Domain-Specific Misuses
"Improvements in LLMs may exert greater pressure to apply LLMs to various domains, such as health and education (Eloundou et al., 2023). Crude efforts to use LLMs in such domains, however, may incur harm and should be di...
Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

Incidents in the same risk subdomain

All incidents in this subdomain