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Data & AI Usage Policy

Governance principles for environmental data, models, AI outputs, and human oversight.

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We May Use Data For:

  • Model training - Improving AI algorithms and environmental models
  • Analytics improvement - Enhancing data analysis capabilities
  • Anomaly detection - Identifying unusual patterns in environmental data
  • Environmental modeling - Creating predictive models for ecological systems

We Do Not:

  • Intentionally identify individuals from environmental datasets
  • Sell raw project datasets without proper authorization
  • Share sensitive information without consent or legal requirement
  • Use data beyond stated purposes without user agreement

Human Oversight

Critical Requirement: AI outputs may contain errors and should undergo human validation before critical decisions are made.

Human Review Required For:

  • Environmental impact assessments
  • Carbon credit calculations
  • Agricultural recommendations
  • Land use planning decisions
  • Financial projections and estimates

AI System Capabilities

Our AI systems provide:

  • Environmental Analytics - Pattern recognition in environmental data
  • Predictive Modeling - Forecasting environmental trends and outcomes
  • Data Processing - Automated analysis of large environmental datasets
  • Decision Support - Recommendations based on data analysis

AI System Limitations

  • Advisory Nature - All outputs are recommendations, not definitive answers
  • Data Dependency - Quality depends on input data accuracy and completeness
  • Context Sensitivity - May not account for all local environmental factors
  • Continuous Learning - Systems are regularly updated and improved

Data Processing Principles

  • Data Minimization - Only collect and process necessary data
  • Purpose Limitation - Use data only for stated purposes
  • Accuracy - Maintain data quality and correct inaccuracies
  • Security - Protect data through appropriate safeguards
  • Transparency - Provide clear information about data use

User Rights and Controls

Users have the right to:

  • Understand how their data is processed
  • Access their personal and project data
  • Request corrections to inaccurate data
  • Withdraw consent for certain data uses
  • Request deletion of personal data (subject to legal requirements)

Quality Assurance

We implement:

  • Regular AI model validation and testing
  • Continuous monitoring of system performance
  • User feedback integration for improvements
  • Professional review of critical outputs
  • Regular updates to address identified issues
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