AIPolicyTracker
Menu

AI incident ·

Purportedly AI-Recreated Clips from Beastie Boys' 'Sabotage' Video Reportedly Appeared in FBI Promotional Video Posted by Kash Patel

1 news report Snapshot 7 Sep 2026

In brief

An AI system built by Synthetic Video Generation Technology Developers and Deepfake Technology Developers and deployed by Kash Patel and Federal Bureau Of Investigation allegedly harmed Spike Jonze, Musicians and 4 others.

Risk domain
Malicious Actors & Misuse Fraud, scams, and targeted manipulation
Occurred
Coverage
1 reportMay 2026

What happened

An FBI promotional video posted by Director Kash Patel reportedly used AI-generated clips that closely recreated shots from the Beastie Boys' 1994 "Sabotage" music video directed by Spike Jonze. NPR identified at least six matching clips and quoted experts who said AI likely recreated the footage, possibly from screenshots or short clips. The video promoted FBI anti-fraud work and received roughly half a million views by the next day.

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 (1)

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

  1. Did FBI Director Kash Patel use AI to rip off the Beastie Boys?
    npr.org · Geoff Brumfiel

Who was involved

Alleged harmed party
Spike Jonze, Musicians, Filmmakers, Epistemic Integrity, Copyright Holders, Beastie Boys

Classification (MIT AI Risk Repository taxonomy)

Causal entity
Human
Intent
Intentional
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.

  • 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)

Incidents in the same risk subdomain

All incidents in this subdomain

Source record: incident #1480 on the AI Incident Database · all 1 report