YouTube Auto-Moderation Reportedly Banned Women of Sex Tech Conference

Laws that address this harm

Policy angle: Classified under AI system safety, failures, and limitations (Lack of capability or robustness) in the MIT AI Risk Repository taxonomy; 5 recorded instruments address this use case.

• India DPDP Act India · Partially applicable · binding
• Law on Artificial Intelligence (2025) Kazakhstan · Adopted · binding
• Law No. 132/2025 on artificial intelligence Italy · In force · binding
• EU AI Act European Union · Partially applicable · binding
• Texas Responsible AI Governance Act (TRAIGA) Texas (United States) · In force · binding

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 (2)

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

1. 8 May 2020
   YouTube says ban of women's sex tech live show was algorithm's fault

   dailymail.co.uk · James Pero
2. 8 May 2020
   YouTube Automatically Banned a Sex Tech Conference

   insidehook.com · Kayla Kibbe

Who was involved

Alleged deployer

YouTube

Alleged developer

YouTube

Alleged harmed party

YouTube users Women of Sex Tech conference organizers Women of Sex Tech conference attendants Women of Sex Tech Social media users

AI systems implicated

YouTubeSocial media platformsContent moderation systems

Classification (MIT AI Risk Repository taxonomy)

Risk domain

AI system safety, failures, and limitations

Risk subdomain

7.3 Lack of capability or robustness

Causal entity

AI

Intent

Unintentional

Timing

Post-deployment

Harm level

—

Sectors

—

Countries

—

Risk entries describing this failure mode

Entries from the MIT AI Risk Repository coded to subdomain 7.3.

• Reliability issues

  "Relying on general-purpose AI products that fail to fulfil their intended function can lead to harm. For example, general- purpose AI systems can make up facts (‘hallucination’), generate erroneous computer code, or pro...

  International AI Safety Report 2025 (Bengio2025)

• Type 2: Bigger than expected

  Harm can result from AI that was not expected to have a large impact at all, such as a lab leak, a surprisingly addictive open-source product, or an unexpected repurposing of a research prototype.

  TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI (Critch2023)

• Type 3: Worse than expected

  AI intended to have a large societal impact can turn out harmful by mistake, such as a popular product that creates problems and partially solves them only for its users.

  TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI (Critch2023)

• Ethics and Morality Issues

  LMs need to pay more attention to universally accepted societal values at the level of ethics and morality, including the judgement of right and wrong, and its relationship with social norms and laws.

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

• Safe learning

  "AGIs should avoid making fatal mistakes during the learning phase. Subproblems include safe exploration and distributional shift (DeepMind, OpenAI), and continual learning (Berkeley)."

  AGI Safety Literature Review (Everitt2018 )

• Malign belief distributions

  "Christiano (2016) argues that the universal distribution M (Hutter, 2005; Solomonoff, 1964a,b, 1978) is malign. The argument is somewhat intricate, and is based on the idea that a hypothesis about the world often includ...

  AGI Safety Literature Review (Everitt2018 )

• Meta-cognition

  "Agents that reason about their own computational resources and logically uncertain events can encounter strange paradoxes due to Godelian limitations (Fallenstein and Soares, 2015; Soares and Fallenstein, 2014, 2017) an...

  AGI Safety Literature Review (Everitt2018 )

• Technical and operational risks

  "To date, technical limitations and vulnerabilities are present in most generative AI models in various contexts. Consequently, malicious users find it easier to breach an AI system’s safety and ethical guardrails to e...

  Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024)

Related incidents

Linked by editors or by text similarity in the source dataset.

• 1 Oct 2021Facebook Internally Reported Failure of Ranking Algorithm, Exposing Harmful Content to Viewers over Months
• 19 May 2015Google’s YouTube Kids App Presents Inappropriate Content
• 28 Jun 2020YouTube's AI Mistakenly Banned Chess Channel over Chess Language Misinterpretation

Incidents in the same risk subdomain

• 15 May 2026Purported AI Name-Reading System Reportedly Skipped and Misannounced Graduates at Arizona's Glendale Community College Commencement
• 24 Apr 2026PocketOS Production Database Was Reportedly Deleted by Cursor AI Agent Running Claude Opus 4.6
• 31 Mar 2026Baidu Apollo Go Robotaxis Stopped in Traffic During Reported System Failure in Wuhan, Stranding Some Passengers
• 28 Feb 2026Purportedly AI-Enabled Targeting System Was Reportedly Implicated in Deadly U.S. Strike on Iranian Primary School
• 26 Feb 2026Claude Code Agent Reportedly Deleted DataTalks.Club Production Infrastructure, Database, and Snapshots via Terraform
• 17 Feb 2026Purportedly AI-Generated Sepsis Alert Reportedly Prompted Potentially Inappropriate IV Fluid Administration for a Dialysis Patient, Averted by Clinician Intervention

Other incidents involving YouTube

• 10 Dec 2024YouTube Algorithms Allegedly Amplify Eating Disorder Content to Adolescent Girls