A.B. Paterson College Teacher in Queensland Allegedly Used AI to Create Explicit Images of Students and Staff

Queensland police allege that former A.B. Paterson College teacher Robert John Thomas used a work-issued laptop and AI software to create explicit images depicting staff members and students. The school discovered and quarantined the material in October 2025, dismissed Thomas, and reported the matter to police. Authorities said there was no evidence he shared the images; he was charged with child-exploitation and computer-misuse offences in July 2026.

Risk classification

• Primary risk domain: 1 Discrimination & Toxicity
• Primary risk subdomain: 1.2 Exposure to toxic content

The AI system was used to generate child sexual abuse material (CSAM) and explicit images, which falls under exposure to toxic and illegal content.

Additional risk subdomains

• 4.3 Fraud, scams, and targeted manipulation: The user generated explicit sexual imagery depicting real members of the school community without their consent.

Causal factors

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

The incident was directly caused by a human user intentionally utilizing deployed AI software to generate explicit and illegal images.

EU AI Act risk tier

• Risk tier: 3 Limited Risk

Limited Risk: The system used was an AI image generator capable of creating synthetic content and deepfakes, which falls under the category of AI-generated content requiring transparency.

AI system and alleged parties

• AI system: artificial intelligence software
• AI purpose: Deepfake Image Generation; Image Generation
• Behaviour type: Tool
• Alleged developer: Synthetic media generation technology developers, Synthetic image generation technology developers, Deepfake technology developers
• Alleged deployer: Teachers, Synthetic media creators, Robert John Thomas, Educators, Deepfake creators
• Alleged harmed parties: Victims of non-consensual deepfakes, Victims of deepfake child abuse, Victims of deepfake abuse, Teachers, Students, School employees, Privacy, Minors, Epistemic integrity, Educators, Educational communities, A.B. Paterson College students and staff depicted in alleged AI-generated explicit images, A.B. Paterson College

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 Negligible, indirect Negligible
• Civil rights: direct Minor, indirect Negligible
• Democracy: direct Negligible, indirect Negligible
• Privacy: direct Negligible, indirect Negligible
• Psychological: direct Negligible, indirect Minor
• Epistemic: direct Negligible, indirect Negligible
• Child sexual exploitation and abuse: direct Substantial, indirect Negligible

Malicious content

Reported: The report explicitly describes the generation of explicit images depicting adults and children using AI.

Directly caused: The AI software was used to generate explicit and toxic images of children and adults.

Civil rights

Reported: The report explicitly describes the creation of child exploitation material, which is a severe violation of children's rights.

Directly caused: The generation of child sexual abuse material directly violates the fundamental rights and protection of children.

Inferred additional harm: The unauthorized generation of explicit synthetic likenesses violates the personal rights and bodily autonomy of the depicted individuals.

Psychological

Reported: The report explicitly describes that the school's priority is supporting students and staff members, indicating psychological distress within the community.

Indirectly caused: The discovery of explicit AI-generated images depicting members of the school community caused distress and required the school to provide support to students and staff.

Inferred additional harm: It is highly likely that the individuals depicted and the broader school community experienced significant anxiety, distress, and trauma upon learning of the explicit images.

Child sexual exploitation and abuse

Reported: The report explicitly describes a CSEA incident involving the generation and possession of child exploitation material using AI.

Directly caused: The former teacher used AI software to generate explicit images of children, resulting in criminal charges for child exploitation material.

People affected

• Occurrences reported: 1
• People reportedly harmed: 10
• People reportedly exposed: 10

Potential causes

Management

• Lack of Proactive IT Audits: The school relied on reactive discovery rather than proactive content scanning.

Technology

• AI Image Generation Software: Software allowed the generation of explicit images of children and adults.
• Misuse of Work Laptop: The school-issued laptop was used to run or access AI generation tools.

Data Inputs

• Community Member Images: Images of school community members were used to generate false depictions.

Human Factors

• Deliberate Misuse by Employee: A former teacher intentionally generated child exploitation material.

Process and Methods

• Inadequate Device Monitoring: School IT systems did not proactively prevent the installation or use of AI.

Regulatory Environment

• Lagging AI Regulations: Regulatory frameworks struggle to prevent the generation of harmful AI content.

Information quality

• Classification confidence: High
• Reason for confidence: The reports provide clear and consistent details regarding the arrest, the charges, the school's response, and the nature of the AI-generated material. There is no conflicting information.
• Ambiguities identified: The specific AI model or software used is not named, and the exact number of community members depicted is not specified.

A localized criminal incident where a school teacher used AI to generate child exploitation material and explicit images of community members. While representing a severe violation of individual rights and dignity, the national security impact is minor and successfully managed by domestic law enforcement.

• Overall national security impact: Minor
• Scope: Single nation
• Primary target: Australia
• Alleged perpetrator: Individual

Threat characteristics

• Imminence: Long-term. The immediate threat is resolved with the perpetrator's arrest, but the broader capability of AI-generated CSAM remains an ongoing strategic concern.
• Autonomy: Human-controlled. The AI acted strictly as a tool, generating images based on direct prompts and inputs from the user.
• Novelty: Evolved capability. Represents an evolved threat where AI image generation is leveraged to create highly targeted, explicit synthetic likenesses of real community members.

Impact by dimension

• Physical security: Negligible. No threat to physical systems, critical infrastructure, or kinetic targeting was identified in this incident.
• Information security: Negligible. The incident does not involve state-sponsored disinformation, classified data theft, or compromise of intelligence capabilities.
• Sovereignty: Negligible. Core government operations, electoral systems, and state sovereignty were not impacted by this localized criminal act.
• Economic security: Negligible. There was no threat to financial systems, strategic technologies, or national economic competitive advantage.
• Societal stability: Minor. The generation of child exploitation material and unauthorized explicit images of community members represents a severe violation of rights, but remains localized and managed by standard law enforcement.