AIPolicyTracker
Menu

AI incident #58 ·

Russian Chatbot Supports Stalin and Violence

Open on the AI Incident Database 5 news reports Snapshot 7 Sep 2026

What happened

Yandex, a Russian technology company, released an artificially intelligent chat bot named Alice which began to reply to questions with racist, pro-stalin, and pro-violence responses

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 (5)

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

  1. The Yandex Chatbot: What You Need To Know
    chatbotsmagazine.com · Charlie Moloney · AIID #1084
  2. Russian AI chatbot found supporting Stalin and violence two weeks after launch
    telegraph.co.uk · James Titcomb, Roland Oliphant · AIID #1079
  3. Russian AI Chatbot Found Supporting Stalin, Violence After Launch
    infowars.com · Jamie White · AIID #1080
  4. 2-Weeks Old Chatbot Declares 'It's Necessary to Shoot Enemies of the People'
    eteknix.com · Mike Sanders · AIID #1083
  5. Russian Voice Assistant Alice Goes Rogue, Found to be Supportive of Stalin and Violence
    voicebot.ai · Ava Mutchler · AIID #1082

Who was involved

Alleged deployer
Yandex
Alleged developer
Yandex
Alleged harmed party
Yandex Users

Classification (MIT AI Risk Repository taxonomy)

Causal entity
AI
Intent
Unintentional
Timing
Post-deployment
Harm level
none
Sectors
information and communication
Countries
RU

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