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

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.

Risk classification

• Primary risk domain: 4 Malicious actors
• Primary risk subdomain: 4.3 Fraud, scams, and targeted manipulation

The incident involved the unauthorized use of celebrity likenesses and cloned voices in deepfake advertisements to deceive social media users for financial gain through scams.

Additional risk subdomains

• 6.3 Economic and cultural devaluation of human effort: The reports highlight how the unauthorized replication of actors' voices and likenesses fuels ongoing labor disputes and fears of human creatives being devalued or replaced by AI.

Causal factors

• Entity: Human
• Intent: Intentional
• Timing: Post-deployment

The incident was caused by human malicious actors who intentionally created and deployed AI deepfakes post-deployment to scam social media users.

EU AI Act risk tier

• Risk tier: 3 Limited Risk

Risk Level 3: The incident involves AI-generated content (deepfakes), which falls under Limited Risk due to transparency obligations requiring users to be informed that the content is synthetic.

AI system and alleged parties

• AI system: unspecified
• AI purpose: Deepfake Video Generation; Voice Generation
• Behaviour type: Tool
• Alleged developer: unknown
• Alleged deployer: unknown
• Alleged harmed parties: Wolf Blitzer, Tom Hanks, Sanjay Gupta, Sally Bundock, Robin Williams, public figures, MrBeast, Matthew Amroliwala, Jesse Waters, Ian Hanomansing, General public, Gayle King, celebrities

Harm severity

Severity ratings are based on this scale.

Highest direct severity in any category: Minor. Severity is scored from Negligible to Catastrophic in each harm category, for harm the reports describe as caused directly or indirectly by the AI system.

• Physical: direct Negligible, indirect Negligible
• Infrastructure: direct Negligible, indirect Negligible
• Property: direct Negligible, indirect Negligible
• Financial: direct Negligible, indirect Negligible
• Environmental: direct Negligible, indirect Negligible
• Malicious content: direct Minor, indirect Negligible
• Differential treatment: direct Negligible, indirect Negligible
• Civil rights: direct Negligible, indirect Negligible
• Democracy: direct Negligible, indirect Negligible
• Privacy: direct Minor, indirect Negligible
• Psychological: direct Negligible, indirect Negligible
• Epistemic: direct Minor, indirect Negligible
• Child sexual exploitation and abuse: direct Negligible, indirect Negligible

Malicious content

Reported: Yes, the reports describe the creation and spread of malicious deepfake videos and cloned audio designed to scam users.

Directly caused: Malicious actors directly created deepfake videos of Tom Hanks, Gayle King, and MrBeast to promote fraudulent schemes on Instagram and TikTok.

Inferred additional harm: Numerous other unquantified deepfake scam ads likely exist across social media platforms, exposing millions of users to deceptive and malicious content.

Privacy

Reported: Yes, the reports describe the unauthorized use and manipulation of the celebrities' voices and likenesses.

Directly caused: The voice and video data of Tom Hanks, Gayle King, and MrBeast were harvested and manipulated without their consent to train AI models and generate deepfakes.

Inferred additional harm: The personal data of other public figures and private individuals is likely being harvested similarly to create unauthorized synthetic media.

Epistemic

Reported: Yes, the reports describe how these deepfakes contribute to a crisis of trust and erode public confidence in digital media and trusted personalities.

Directly caused: The deepfakes fabricated endorsements from trusted figures, misleading viewers and undermining the reliability of video and audio evidence online.

Inferred additional harm: The proliferation of such deepfakes is likely to cause widespread skepticism, making it difficult for the public to distinguish real media from synthetic fabrications.

People affected

• Occurrences reported: 3
• People reportedly harmed: 3
• People reportedly exposed: 10000

Potential causes

Management

• Reduction in Ethical AI Research: Tech companies cut ethical AI teams as part of broader cost-cutting.
• Prioritizing Growth Over Safety: Platforms focus on engagement rather than robust safety enforcement.

Technology

• Advanced Voice Cloning: AI clones voices from short audio to make fake endorsements.
• Realistic Faceswap Tools: Sophisticated AI easily overlays faces onto existing video clips.
• Generative AI Accessibility: Powerful tools are widely available to make convincing deepfakes.

Data Inputs

• Abundant Public Video Footage: Ample public footage of celebrities is used to train AI models.
• Lack of Source Authentication: No tracking of original video origins before manipulation occurs.

Human Factors

• Erosion of Public Trust: Viewers struggle to distinguish real videos from fake, causing skepticism.
• User Susceptibility to Scams: Average social media users often fall for realistic fake advertisements.

Process and Methods

• Inadequate Platform Moderation: Social media platforms fail to proactively block deepfakes before they spread.
• Delayed Takedown Procedures: Platforms are slow to respond even after celebrities flag fake ads.

Regulatory Environment

• Absence of Clear AI Laws: Few concrete laws exist globally targeting unauthorized deepfakes.
• Unclear Intellectual Property Rights: Legal frameworks for protecting faces and voices as IP are still developing.

Information quality

• Classification confidence: High
• Reason for confidence: The reports provide consistent, detailed accounts of the celebrity deepfake incidents, including direct statements from the affected individuals and platforms. The nature of the scams and the technology used are clearly described across multiple reputable sources.
• Ambiguities identified: The specific AI tools or platforms used to generate the deepfakes are not identified, and the exact number of victims who lost money is not quantified.

Unauthorized use of prominent celebrity likenesses and cloned voices in AI-generated deepfake advertisements on social media platforms for commercial scams. Although showcasing the rapid progression and accessibility of synthetic media tools, the incident has minor direct implications for national security, primarily posing consumer fraud and localized epistemic trust challenges.

• Overall national security impact: Minor
• Scope: Single nation
• Primary target: United States
• Alleged perpetrator: Unknown

Threat characteristics

• Imminence: Long-term. Represents an ongoing strategic concern regarding synthetic media proliferation rather than an immediate national security crisis.
• Autonomy: Human-controlled. AI tools were used strictly as instruments by human scammers to generate and deploy specific deceptive media assets.
• Novelty: Evolved capability. Builds upon established deepfake and voice cloning techniques but reflects an evolution in accessibility, quality, and scaling for commercial scams.

Impact by dimension

• Physical security: Negligible. No physical threat, critical infrastructure impact, or kinetic targeting reported in connection with this commercial scam incident.
• Information security: Minor. Demonstrates sophisticated deepfake and voice cloning capabilities on social platforms, but lacks evidence of state-sponsored intelligence compromise or geopolitical information warfare.
• Sovereignty: Negligible. No impact on government operations, sovereign authority, border control, or national decision-making processes.
• Economic security: Minor. Represents commercial fraud and likeness theft targeting individual consumers, but does not threaten strategic industries, financial systems, or national technological advantages.
• Societal stability: Minor. Contributes to epistemic harm and erosion of public trust in digital media, but does not involve mass surveillance, systematic discrimination, or threat of civil unrest.