AI incident #963 · 5 March 2025

Google Reports Alleged Gemini-Generated Terrorism and Child Exploitation to Australian eSafety Commission

Open on the AI Incident Database 1 news report Snapshot 7 Sep 2026

What happened

Google reported to Australia's eSafety Commission that it received 258 complaints globally about AI-generated deepfake terrorism content and 86 about child abuse material made with its Gemini AI. The regulator called this a "world-first insight" into AI misuse. While Google uses hash-matching to detect child abuse content, it lacks a similar system for extremist material.

Only the incident metadata is stored here. The underlying news reports are on the AI Incident Database (CC BY-SA 4.0); use the links above to read them.

News reports (1)

Coverage catalogued by the AI Incident Database. Titles link to the original publisher; the text is not reproduced here.

5 Mar 2025
Google reports scale of complaints about AI deepfake terrorism content to Australian regulator
reuters.com · Byron Kaye · AIID #4842

Who was involved

Alleged deployer: Google
Alleged developer: Google
Alleged harmed party: General Public, General Public Of Australia, Google Gemini Users, Victims Of Deepfake Terrorism Content, Victims Of Deepfake Child Abuse, Victims Of Online Radicalization

Classification (MIT AI Risk Repository taxonomy)

Risk domain: Malicious Actors & Misuse
Risk subdomain: 4.3 Fraud, scams, and targeted manipulation
Causal entity: Human
Intent: Intentional
Timing: Post-deployment
Harm level: —
Sectors: —
Countries: —

Risk entries describing this failure mode

Entries from the MIT AI Risk Repository coded to subdomain 4.3.

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)
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)
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)
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)
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)
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)
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)

Incidents in the same risk subdomain

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