AIPolicyTracker

AI incident ·

Purported AI Deepfake Reportedly Impersonated Thai PBS World Anchor and Miss Universe CEO in Fraudulent Investment Video

1 news report Snapshot 7 Sep 2026

In brief

An AI system built by Deepfake Technology Developers and Synthetic Audio Generation Technology Developers and deployed by Unknown Scammers Impersonating Doliyana Bunnak, Unknown Scammers Impersonating Anne Jakkraphong Jakrajutatip and 1 other allegedly harmed Thairath Tv, Thai Social Media Users and 7 others.

Risk domain
Malicious Actors & Misuse Fraud, scams, and targeted manipulation
Occurred
Coverage
1 reportJul 2025

What happened

A purported deepfake video allegedly used AI-generated visuals and synthetic speech to impersonate Thai PBS World anchor Doliyana Bunnak and Miss Universe Organization CEO Anne Jakkraphong Jakrajutatip, falsely promoting an online investment promising rapid, high returns. The clip was reportedly derived from a June 24 2025 Thai PBS World Tonight broadcast and circulated on Facebook, misusing news logos and likenesses, causing reputational harm and exposing viewers to financial fraud.

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.

Who was involved

Alleged harmed party
Thairath Tv, Thai Social Media Users, Thai Pbs World, Thai Facebook Users, Investors In Thailand, General Public Of Thailand, Epsitemic Integrity, Doliyana Bunnak, Anne Jakkraphong Jakrajutatip

Classification (MIT AI Risk Repository taxonomy)

Causal entity
Human
Intent
Intentional
Timing
Post-deployment
Harm level
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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

Source record: incident #1254 on the AI Incident Database · all 1 report