This recommended practice addresses embedding ethical Artificial Intelligence (AI) into climate modelling processes. This includes: 1) Fairness & Bias Mitigation: The document helps to ensure AI systems do not reinforce inequities or amplify biases in climate data and projections. 2) Transparency & Explainability: The document promotes interpretable AI models so that scientists, policymakers, and communities can trust and act upon climate predictions. 3) Data Governance & Privacy: The document establishes protocols for responsible data handling, security, and consent. 4) Accountability & Standards: The document supports aligning AI-driven climate applications with international norms, regulations, and scientific standards. 5) Sustainable Practices: The document helps to ensure AI usage supports long-term environmental and social sustainability. The recommended practice aligns with UNESCO's AI Ethics Framework, while focusing on Disaster Risk Reduction (DRR) and long-term climate predictions. While the document covers ethical and procedural best practices, it does not address technical AI performance standards (e.g., algorithmic efficiency, model accuracy) or specific operational protocols for disaster response (e.g., emergency coordination, infrastructure deployment).
- Standard Committee
- SSIT/SC - Social Implications of Technology Standards Committee
- Status
- Active PAR
- PAR Approval
- 2025-12-10
Working Group Details
- Society
- IEEE Society on Social Implications of Technology
- Standard Committee
- SSIT/SC - Social Implications of Technology Standards Committee
- Working Group
-
CPWG - Addressing Ethical Concerns in AI based Climate Projections
- IEEE Program Manager
- Malia Zaman
Contact Malia Zaman - Working Group Chair
- Mahendra Samarawickrama
Other Activities From This Working Group
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