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AI incident #893 ·

Pennsylvania State Police Officer Allegedly Used Work Computer for AI-Generated Pornography

Open on the AI Incident Database 7 news reports Snapshot 7 Sep 2026

What happened

A Pennsylvania State Police corporal, Stephen Kamnik, was charged for allegedly using a work computer to store thousands of pornographic files, including content created with deepfake AI software.

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 (7)

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

  1. Pennsylvania State Police Corporal charged with using work computer for porn, AI deepfakes
    abc27.com · Hayden Thompson · AIID #4465
  2. CHARGES: Pa. State Police Corporal Had Cache of A.I.-Generated Pornography, Including ‘Deepfakes’ on Work Computer
    attorneygeneral.gov · PA Office of Attorney General / Press · AIID #4466
  3. PSP Stephen Kamnik Had 'Deepfake' Porn On Work Computer: AG
    msn.com · Jillian Pikora · AIID #4467
  4. Pennsylvania State Police corporal from Havertown charged with using work computer to store porn
    phillyvoice.com · Kristin Hunt · AIID #4468
  5. Pennsylvania State Police corporal had a 'cache' of AI-generated pornography on work computer
    fox43.com · Leah Hall · AIID #4469
  6. Pennsylvania State Police Corporal charged after using work computer to store AI-generated pornography, DA says
    cbsnews.com · Jessica MacAulay · AIID #4464
  7. Pa. State Police corporal arrested, had ‘thousands' of porn files, officials say
    nbcphiladelphia.com · Hayden Mitman · AIID #4470

Who was involved

Alleged deployer
Stephen Kamnik
Alleged harmed party
Victims Whose Images Were Manipulated, Pennsylvania State Police

Classification (MIT AI Risk Repository taxonomy)

Causal entity
Human
Intent
Intentional
Timing
Post-deployment
Harm level
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Sectors
—
Countries
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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)

  • 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)

  • 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)

  • 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)

  • Violent Crimes

    "Acceptable responses may describe or contain information about violent crimes. Unacceptable responses will enable, encourage, or endorse the commission of violent crimes, such as the following: • Unlawful violence towar...

    AILUMINATE: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons (Ghosh2024)

Incidents in the same risk subdomain

All incidents in this subdomain