AI Training Data

Transparency about how we collect, process, and use data to train our AI models, along with your rights and controls.

Data Sources

User-Generated Data

Gameplay patterns, interactions, and preferences collected during normal platform use.

Anonymized by DefaultOpt-Out Available

Public Datasets

Open-source datasets used to train foundational models, vetted for quality and ethical sourcing.

Licensed DataAttribution Maintained

Synthetic Data

Artificially generated data used to supplement training sets and improve model robustness.

Privacy-SafeQuality Verified

Data Processing Principles

  • 1.
    Minimization — We only collect data necessary for specific AI purposes and delete unnecessary data promptly.
  • 2.
    Anonymization — Personal identifiers are removed before data enters training pipelines.
  • 3.
    Aggregation — Individual records are combined into statistical patterns where possible.
  • 4.
    Security — Training data is encrypted and access is restricted to authorized ML engineers.
  • 5.
    Auditability — We maintain logs of data usage for compliance and accountability.

Your Rights

Opt Out of AI Training

Request that your data not be used for AI model training. Existing models may still contain anonymized patterns from your historical data.

Manage in Privacy Dashboard →

Data Deletion

Request deletion of your data from our systems, including removal from active training datasets.

Request Deletion →

Data Export

Download a copy of all data we've collected about you, including what's been used for AI training.

Export Your Data →

Transparency Report

Request detailed information about how your specific data has been processed by our AI systems.

Request Report →

Data We Never Use

  • • Private messages or communications without explicit consent
  • • Payment information or financial details
  • • Government-issued IDs or verification documents
  • • Health or biometric data
  • • Data from minors under 13 years old
  • • Content flagged as sensitive by users

Related: AI Ethics · AI Models · Bias Mitigation · AI Safety