AIPolicyTracker

AI incident ·

Deepfaked Advertisements Using the Likenesses of Celebrities Such as Tom Hanks and Gayle King Without Their Consent

15 news reports Snapshot 7 Sep 2026

In brief

An AI system built and deployed by Unknown allegedly harmed Wolf Blitzer, Tom Hanks and 11 others.

Risk domain
Malicious Actors & Misuse Fraud, scams, and targeted manipulation
Occurred
Coverage
15 reportsOct 2023 - Nov 2023

What happened

Deepfake technology was used to generate video advertisements featuring celebrities. Notable examples include the likeness of Tom Hanks touting a dental plan and another one in which the likeness of Gayle King touts a weight loss product. In each case, the individuals whose likenesses and voices had been deepfaked had not consented to their images and voices being used for the commercials.

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 (15)

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

  1. Tom Hanks Warns of Dental Ad Using A.I. Version of Him
    nytimes.com · Derrick Bryson Taylor
  2. Celebrity deepfakes are having a moment
    morningbrew.com · Sam Klebanov
  3. AI Deepfake Ads: Tom Hanks, Gayle King Sound Warning
    cnet.com · Gael Fashingbauer Cooper
  4. Deepfake Scammers Target Top News Anchors on Facebook
    news18.com · Shankhyaneel Sarkar, AFP

Who was involved

Alleged deployer
Unknown
Alleged developer
Unknown
Alleged harmed party
Wolf Blitzer, Tom Hanks, Sanjay Gupta, Sally Bundock, Robin Williams, Public Figures, Mrbeast, Matthew Amroliwala, Jesse Waters, Ian Hanomansing, General Public, Gayle King, Celebrities

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 Unknown

Source record: incident #606 on the AI Incident Database · all 15 reports