AIPolicyTracker

AI incident ·

Social Media Scammers Used Deepfakes of Taylor Swift and Several Other Celebrities in Fraudulent Le Creuset Cookware Giveaways

30 news reports Snapshot 7 Sep 2026

In brief

An AI system built by Deepfake Technology Developers and deployed by Scammers allegedly harmed Trisha Yearwood, Taylor Swift and 11 others.

Risk domain
Malicious Actors & Misuse Fraud, scams, and targeted manipulation
Occurred
Coverage
30 reportsDec 2023 - Jan 2024

What happened

Scammers reportedly made deepfakes of Taylor Swift, Selena Gomez, Joanna Gaines, Lainey Wilson, Ree Drummond, Oprah, Jennifer Lopez, Trisha Yearwood, Martha Stewart, and Blake Shelton promoting a Le Creuset giveaway. These AI-generated ads, appearing on Meta and TikTok, falsely claimed users could receive free cookware by paying a small shipping fee. Victims were unknowingly enrolled in a costly monthly subscription.

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 (30)

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

  1. Ree Drummond Warns of Scam
    bartlesvilleradio.com · Ty Loftis
  2. Taylor Swift fake AI ad dupes fans
    foxnews.com · Elizabeth Stanton
  3. Le Creuset Taylor Swift Giveaway Scam
    news.trendmicro.com · Trend Micro

Who was involved

Alleged deployer
Scammers
Alleged harmed party
Trisha Yearwood, Taylor Swift, Selena Gomez, Ree Drummond, Oprah, Martha Stewart, Le Creuset, Lainey Wilson, Joanna Gaines, Jennifer Lopez, General Public, Fans, Blake Shelton

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 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

Other incidents involving Scammers

Source record: incident #626 on the AI Incident Database · all 30 reports