Safety and Bias Mitigation in Fine-Tuned Models Training Course

Foundations of Safe and Fair Artificial Intelligence for Government

• Key concepts: safety, bias, fairness, transparency
• Types of bias: dataset, representation, algorithmic
• Overview of regulatory frameworks (EU AI Act, GDPR, etc.) for government operations

Bias in Fine-Tuned Models for Government

• How fine-tuning can introduce or amplify bias in public sector applications
• Case studies and real-world failures relevant to government agencies
• Identifying bias in datasets and model predictions within governmental contexts

Techniques for Bias Mitigation in Government AI Systems

• Data-level strategies (rebalancing, augmentation) for government data sets
• In-training strategies (regularization, adversarial debiasing) for public sector models
• Post-processing strategies (output filtering, calibration) to ensure fair outcomes

Model Safety and Robustness for Government Applications

• Detecting unsafe or harmful outputs in government systems
• Adversarial input handling to protect public sector models
• Red teaming and stress testing fine-tuned models for government use cases

Auditing and Monitoring AI Systems for Government Compliance

• Bias and fairness evaluation metrics (e.g., demographic parity) for government agencies
• Explainability tools and transparency frameworks to enhance public trust
• Ongoing monitoring and governance practices to ensure accountability

Toolkits and Hands-On Practice for Government AI Teams

• Using open-source libraries (e.g., Fairlearn, Transformers, CheckList) in government projects
• Hands-on: Detecting and mitigating bias in a fine-tuned model for government use
• Generating safe outputs through prompt design and constraints in public sector applications

Enterprise Use Cases and Compliance Readiness for Government Agencies

• Best practices for integrating safety in large language model (LLM) workflows for government operations
• Documentation and model cards for compliance with regulatory requirements
• Preparing for audits and external reviews to ensure adherence to standards

Summary and Next Steps for Government AI Initiatives