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Responsible AI checklst
Data Collection
Ensure data is collected ethically and legally
Use diverse and representative data sources
Regularly review and update data collection processes
Model Development
Test models for bias and fairness
Include diverse stakeholders in model development
Document model development process thoroughly
Model Deployment
Monitor model performance in real-world applications
Implement feedback mechanisms for users to report issues
Provide transparency about model decisions and limitations
Model Evaluation
Regularly audit and evaluate model performance
Conduct impact assessments on marginalized communities
Continuously update and improve models based on evaluation results
Accountability
Assign responsibility for model decisions and outcomes
Establish processes for handling complaints and addressing errors
Regularly review and update Responsible AI policies and practices
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