Artificial Intelligence Policy Tracker

AI incident ·

Purportedly AI-Generated 'King Trump' Fighter Jet Video Allegedly Posted by President Depicts Defecation Attack on 'No Kings' Protesters

2 news reports Snapshot 7 Sep 2026
On this page 8 sections

In brief

An AI system built by Deepfake Technology Developers and deployed by Donald Trump and Pro Trump Social Media Accounts allegedly harmed Harry Sisson, Kenny Loggins and 7 others.

Risk domain
Discrimination and Toxicity Exposure to toxic content
Occurred
Coverage
2 reportsOct 2025

What happened

President Donald Trump reportedly posted an AI-generated video on Truth Social showing himself crowned and piloting a fighter jet labeled King Trump, dropping feces on protesters, including influencer Harry Sisson, during No Kings demonstrations. The clip, allegedly created by another account, drew criticism from Sisson and musician Kenny Loggins, whose song "Danger Zone" was reportedly used without consent.

Laws on record for this risk area

Policy angle: Classified under Discrimination and Toxicity (Exposure to toxic content) in the MIT AI Risk Repository taxonomy; 4 instruments on record cover this risk area.

Matched from the record's risk category and country to the instruments in effect recorded here: a law listed covers the area, which is not a finding that it applies to this incident. A reviewer can correct the match in the repository (data/external/incident_overrides.yaml).

News reports (2)

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

  1. Donald Trump’s War on Reality
    theatlantic.com · Franklin Foer

Who was involved

Alleged harmed party
Harry Sisson, Kenny Loggins, General Public, General Public Of The United States, No Kings Protesters, Epistemic Integrity, Cultural Integrity, Public Discourse Integrity, Democratic Integrity

Classification (MIT AI Risk Repository taxonomy)

Causal entity
Human
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 1.2.

  • Harmful Content

    "The LLM-generated content sometimes contains biased, toxic, and private information"

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Toxicity

    "Toxicity means the generated content contains rude, disrespectful, and even illegal information"

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Toxic Training Data

    "Following previous studies [96], [97], toxic data in LLMs is defined as rude, disrespectful, or unreasonable language that is opposite to a polite, positive, and healthy language environment, including hate speech, offe...

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Not-Suitable-for-Work (NSFW) Prompts

    "Inputting a prompt contain an unsafe topic (e.g., notsuitable-for-work (NSFW) content) by a benign user. "

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Toxicity and Abusive Content

    This typically refers to rude, harmful, or inappropriate expressions.

    Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements (Deng2023)

  • Controversial Opinions

    The controversial views expressed by large models are also a widely discussed concern. Bang et al. (2021) evaluated several large models and found that they occasionally express inappropriate or extremist views when disc...

    Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements (Deng2023)

  • Harmful responses

    "Current Frontier AI mdoels amplify existing biases within their training data and can be manipulated into providing potentially harmful responses, for example abusive language or discriminatory responses91,92. This is n...

    Future Risks of Frontier AI (GOS2023)

  • Violation of social norms

    "Second, because LLMs are trained on internet text data, there is also a risk that model weights encode functions which, if deployed in particular contexts, would violate social norms of that context. Following the princ...

    The Ethics of Advanced AI Assistants (Gabriel2024)

Incidents in the same risk subdomain

All incidents in this subdomain

Source record: incident #1244 on the AI Incident Database · all 2 reports