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AI incident: sexual content (Jul 2024)

3 news reports Synced from source · record last edited 5 Sep 2026

In brief

An AI system built by Synthetic media generation technology developers, Synthetic image generation technology developers and 1 other and deployed by Synthetic media creators and Deepfake creators allegedly harmed Women and girls, Women and 10 others.

Risk domain
Malicious Actors & Misuse Fraud, scams, and targeted manipulation
Occurred
Coverage
3 reportsJul 2024 - Jan 2026

What happened

Female politicians in the United Kingdom, including Angela Rayner, Gillian Keegan, Penny Mordaunt, Priti Patel, Stella Creasy, and Dehenna Davison, have reportedly been targeted by non-consensual, purportedly AI-generated deepfake pornography. The images, which some accounts suggest may have circulated online for an extended period, were reported to have caused distress and, in at least some instances, to have prompted reports to or involvement by law enforcement.

Laws that address this harm

Policy angle: Classified under Malicious Actors & Misuse (Fraud, scams, and targeted manipulation) in the MIT AI Risk Repository taxonomy; 5 recorded instruments address this use case.

Matched from the record's risk domain and country to the instruments recorded here. A reviewer can correct the match in the repository (data/external/incident_overrides.yaml).

News reports (3)

Titles link to the original publisher; report text is not reproduced here.

  1. British female politicians targeted by fake pornography
    theguardian.com · Jim Waterson
  2. We must fight the deepfake future
    newstatesman.com · Zoë Huxford
  3. Deepfakes are undermining faith in politics
    observer.co.uk · Rachel Sylvester

Who was involved

Alleged harmed party
Women and girls Women Stella Creasy Public figures Privacy Priti Patel Politicians in the United Kingdom Politicians Penny Mordaunt Gillian Keegan Dehenna Davison Angela Rayner

AI systems implicated

Synthetic media generation technologySynthetic image generation technologyDeepfake technology

Classification (MIT AI Risk Repository taxonomy)

Causal entity
AI
Intent
Intentional
Timing
Post-deployment
Harm level
—
Sectors
—
Countries
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Risk entries describing this failure mode

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

  • 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)

  • 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)

  • 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)

  • 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)

  • 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)

  • Misinformation and Manipulation

    "Recent studies have demonstrated that LLMs can be exploited to craft deceptive narratives with levels of persuasiveness similar to human-generated content (Pan et al., 2023b; Spitale et al., 2023), to fabri- cate fake n...

    Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

  • 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)

Linked by editors or by text similarity in the source dataset.

Incidents in the same risk subdomain

All incidents in this subdomain

Other incidents involving Synthetic media creators

Source record: incident #754 on the AI Incident Database · all 3 reports