Aledo High School Student Allegedly Generates and Distributes Deepfake Nudes of Seven Female Classmates

In October 2023, an unnamed male student at Aledo High School outside of Fort Worth, Texas allegedly generated and distributed deepfake nude pictures of classmate Elliston Berry and six other female students in her friend group via social media. Berry's mother, Anna McAdams, spoke with Senators Ted Cruz and Amy Klobuchar, who consequently drafted the Tools to Address Known Exploitation by Immobilizing Technological Deepfakes on Websites and Networks (or TAKE IT DOWN) Act.

Risk classification

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

The classmate used AI software to create humiliating and non-consensual sexual imagery targeting specific victims for personal harassment and social degradation.

Additional risk subdomains

• 1.2 Exposure to toxic content: The incident involved the creation and distribution of non-consensual sexually explicit content depicting minors, exposing classmates and social media users to toxic material.

Causal factors

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

The harm was caused by a human classmate who intentionally chose to use AI clothes-removal software to generate and distribute explicit images of his peers.

EU AI Act risk tier

• Risk tier: 3 Limited Risk

Limited Risk: The report describes the generation of deepfakes, which are classified as limited risk under the EU AI Act and are subject to specific transparency and disclosure obligations.

AI system and alleged parties

• AI system: unspecified AI clothes-removal software
• AI purpose: Deepfake Image Generation; Image Generation
• Behaviour type: Tool
• Alleged developer: Unknown deepfake technology developers, Unknown AI image generator developer
• Alleged deployer: Unnamed male student at Aledo High School, Unnamed male student
• Alleged harmed parties: Truth, Epistemic integrity, Elliston Berry, Aledo High School students

Harm severity

Severity ratings are based on this scale.

Highest direct severity in any category: Substantial. 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 Minor, indirect Negligible
• Civil rights: direct Minor, indirect Negligible
• Democracy: direct Negligible, indirect Negligible
• Privacy: direct Minor, indirect Negligible
• Psychological: direct Minor, indirect Minor
• Epistemic: direct Minor, indirect Negligible
• Child sexual exploitation and abuse: direct Substantial, indirect Negligible

Malicious content

Reported: The report explicitly describes toxic and malicious content created and spread directly by the incident.

Directly caused: Hyper-realistic, non-consensual AI-generated nude images of nine minor girls were created and distributed across Snapchat and other social media platforms.

Differential treatment

Reported: The report explicitly describes differential treatment of individuals based on gender.

Directly caused: The cyber exploitation and sexualized harassment exclusively targeted female students in the grade, disproportionately harming young girls.

Civil rights

Reported: The report explicitly describes violations of human and civil rights caused directly by the incident.

Directly caused: The victims' fundamental rights to privacy, personal dignity, and protection from sexual exploitation and harassment were violated by the creation of non-consensual explicit imagery.

Privacy

Reported: The report explicitly describes privacy violations caused directly by the incident.

Directly caused: The classmate violated the victims' privacy by taking photos from their private Instagram accounts and using their likenesses without consent to generate explicit content.

Psychological

Reported: The report explicitly describes severe psychological and mental-health harm to the victims and their families.

Directly caused: Elliston Berry and her eight friends experienced severe anxiety, shame, fear, paranoia, and social withdrawal, with Berry dreading school and feeling unable to focus.

Indirectly caused: The victims' parents experienced significant emotional distress, anger, and feelings of helplessness in protecting their children.

Epistemic

Reported: The report explicitly describes epistemic harm caused directly by the creation of highly realistic fake evidence.

Directly caused: The AI software generated hyper-realistic fake nude images that classmates believed were real, forcing the victims to defend their reputation against false depictions.

Child sexual exploitation and abuse

Reported: The report explicitly describes a CSEA incident as reported by the sources.

Directly caused: The classmate generated and distributed explicit nude images of nine 14-year-old girls, which the victims' families and legal experts explicitly characterized as child pornography.

People affected

• Occurrences reported: 1
• People reportedly harmed: 9
• People reportedly exposed: 9

Potential causes

Management

• Outdated student codes of conduct: School board failed to update policies to address AI-driven misconduct.
• Platform negligence of user safety: Snapchat failed to prioritize and resource victim reporting mechanisms.
• Inadequate school support systems: School failed to provide mental health support or protect target students.

Technology

• Accessible clothes-removal software: Easy online tools allowed quick generation of realistic nude deepfakes.
• Hyper-realistic image generation: Advanced AI made the doctored images indistinguishable from real photos.
• Proliferation of generative AI: Rapid technological advances made powerful tools widely available to minors.

Data Inputs

• Insecure social media photos: Classmate downloaded innocent public or shared photos from Instagram.
• Lack of image protection tech: No mechanisms to prevent scraping or downloading of personal images.
• Access to private accounts: The perpetrator gained access by following a private Instagram account.

Human Factors

• Malicious intent of classmate: A male classmate chose to exploit and harass peers using AI.
• Lack of consent awareness: Minors lack understanding of digital consent and consequences of deepfakes.
• Misplaced social trust: Victims trusted acquaintances with access to private social media accounts.

Process and Methods

• Slow social media takedowns: Snapchat ignored family requests for nine months until a senator intervened.
• Inadequate platform moderation: Social media lacked automated processes to flag and block deepfake NCII.
• Weak school incident response: The high school lacked protocols to handle AI-enabled sexual exploitation.

Regulatory Environment

• Absence of federal deepfake laws: No federal legislation mandated rapid removal or criminalized AI deepfakes.
• Inconsistent state regulations: State laws were patchy, with some covering deepfake videos but not photos.
• Law enforcement confusion: Police lacked clear legal frameworks and training to prosecute AI deepfakes.

Information quality

• Classification confidence: High
• Reason for confidence: The incident is documented across multiple highly detailed and consistent news reports, including direct testimonies from the primary victim, her mother, and involved lawmakers. The facts regarding the AI's role, the distribution platform, and the resulting harms are clear and uncontradicted.
• Ambiguities identified: The specific name of the AI clothes-removal application used by the classmate is not explicitly mentioned in the reports.
• Alternative interpretations: None. The reports consistently describe the event as a targeted cyberbullying and sexual exploitation incident facilitated by generative AI.

A high school student used consumer AI clothes-removal software to generate and distribute non-consensual explicit deepfakes of classmates. While causing severe psychological harm to the victims and highlighting regulatory gaps in protecting minors from AI-enabled exploitation, the incident is a localized criminal and civil issue with minor national security implications.

• Overall national security impact: Minor
• Scope: Single nation
• Primary target: United States
• Alleged perpetrator: Individual (15-year-old male student)

Threat characteristics

• Imminence: Long-term. The active crisis is resolved; the incident represents an ongoing strategic concern regarding the proliferation and regulation of consumer deepfake tools.
• Autonomy: Human-controlled. The AI clothes-removal software was directly operated by a human user who uploaded the images and initiated the process.
• Novelty: Evolved capability. Represents an evolved capability where sophisticated generative AI tools are now easily accessible to minors with no technical expertise, amplifying harassment potential.

Impact by dimension

• Physical security: Negligible. No physical systems, critical infrastructure, or human safety/kinetic systems were impacted by this high school cyberbullying incident.
• Information security: Negligible. This was a localized peer-to-peer harassment incident, not a coordinated information warfare campaign or compromise of national intelligence.
• Sovereignty: Negligible. No state authority, electoral systems, or core government operations were compromised or threatened.
• Economic security: Negligible. No strategic technology, critical supply chains, or financial systems were targeted or compromised.
• Societal stability: Minor. Severe violation of privacy and human rights of minor victims through non-consensual deepfakes, but localized to a high school and manageable via standard domestic legal and educational procedures.