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Grok AI Reportedly Generates Offensive and Violent Images Without Proper Safeguards

3 news reports Snapshot 7 Sep 2026

In brief

An AI system built by X (Twitter) and Xai and deployed by Xai allegedly harmed Taylor Swift, Nintendo and 5 others.

Risk domain
Discrimination and Toxicity Exposure to toxic content
Occurred
Coverage
3 reportsAug 2024

What happened

Elon Musk’s Grok AI, launched on X, generated offensive and violent images without adequate safety controls. The AI produced deepfakes of public figures like Taylor Swift, Kamala Harris, and Alexandria Ocasio-Cortez, as well as copyrighted characters such as Mickey Mouse in inappropriate scenarios. Despite claiming adherence to certain content guidelines, Grok's outputs included politically charged and explicit imagery

Laws that address this harm

Policy angle: Classified under Discrimination and Toxicity (Exposure to toxic content) 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 (3)

Titles link to the original publisher; report text is not reproduced here.

  1. Lack of Grok-2 Image Generation Filters Prompts X Users to Generate Damaging Images
    theguardian.com · Nick Robins-Early
  2. People Are Using X’s AI Chatbot ‘Grok’ to Create Offensive Images of Trademarked Characters — And Troll Elon Musk
    mediaite.com · Sarah Rumpf
  3. Grok-2 Generates Controversy; Expert Reactions
    aibusiness.com · Berenice Baker

Who was involved

Alleged deployer
Xai
Alleged developer
X (Twitter), Xai
Alleged harmed party
Taylor Swift, Nintendo, Kamala Harris, Joe Biden, Donald Trump, Disney, Alexandria Ocasio Cortez

Classification (MIT AI Risk Repository taxonomy)

Causal entity
AI
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 1.2.

  • Harmful Content

    "The LLM-generated content sometimes contains biased, toxic, and private information"

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Toxicity

    "Toxicity means the generated content contains rude, disrespectful, and even illegal information"

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Toxic Training Data

    "Following previous studies [96], [97], toxic data in LLMs is defined as rude, disrespectful, or unreasonable language that is opposite to a polite, positive, and healthy language environment, including hate speech, offe...

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Not-Suitable-for-Work (NSFW) Prompts

    "Inputting a prompt contain an unsafe topic (e.g., notsuitable-for-work (NSFW) content) by a benign user. "

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Controversial Opinions

    The controversial views expressed by large models are also a widely discussed concern. Bang et al. (2021) evaluated several large models and found that they occasionally express inappropriate or extremist views when disc...

    Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements (Deng2023)

  • Toxicity and Abusive Content

    This typically refers to rude, harmful, or inappropriate expressions.

    Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements (Deng2023)

  • Harmful responses

    "Current Frontier AI mdoels amplify existing biases within their training data and can be manipulated into providing potentially harmful responses, for example abusive language or discriminatory responses91,92. This is n...

    Future Risks of Frontier AI (GOS2023)

  • Violation of social norms

    "Second, because LLMs are trained on internet text data, there is also a risk that model weights encode functions which, if deployed in particular contexts, would violate social norms of that context. Following the princ...

    The Ethics of Advanced AI Assistants (Gabriel2024)

Incidents in the same risk subdomain

All incidents in this subdomain

Other incidents involving Xai

Source record: incident #762 on the AI Incident Database · all 3 reports