Workshop: Combatting AI Bias in Public Policy Tools by Tonex
This workshop focuses on understanding, identifying, and mitigating algorithmic bias in AI systems applied in public policy. Participants will gain practical strategies to ensure fairness, transparency, and accountability in AI-driven decision-making processes within government frameworks.
Learning Objectives:
- Define algorithmic bias and its implications in public policy.
- Identify sources of bias in AI systems.
- Analyze case studies of AI failures in public policy.
- Explore frameworks for ethical AI in governance.
- Develop tools to assess and mitigate bias in algorithms.
- Implement strategies for equitable AI practices.
Audience:
- Public policy professionals.
- AI developers and engineers in the public sector.
- Government regulators and administrators.
- Legal experts focused on AI and ethics.
- Social scientists and data analysts.
- Educators and researchers in AI governance.
Course Modules:
Module 1: Introduction to AI Bias
- What is AI Bias?
- Types of Bias in AI Systems
- The Impact of Bias on Public Policy
- Real-World Examples of AI Bias
- Ethical Considerations in Public Policy Tools
- Bias Detection: Overview of Methods
Module 2: Understanding the Sources of Bias
- Bias in Data Collection
- Historical and Systemic Bias in Datasets
- Model Design and Algorithmic Bias
- Human Influence on AI Outcomes
- Bias Amplification in AI Systems
- Feedback Loops in AI Decision-Making
Module 3: Legal and Ethical Frameworks
- Regulations Governing AI Use in Governance
- Principles of Ethical AI Development
- Privacy and Data Protection in Public Policy Tools
- Equity and Inclusion in AI Systems
- Transparency and Explainability Standards
- Building Trust with Stakeholders
Module 4: Tools and Techniques for Bias Mitigation
- Data Preprocessing to Reduce Bias
- Fairness Metrics and Algorithms
- Auditing and Monitoring AI Systems
- Bias Mitigation During Model Training
- Post-Deployment Bias Detection Tools
- Leveraging Open-Source Solutions
Module 5: Implementing AI in Public Policy
- Policy Design with AI Systems
- Risk Assessment and Management
- Cross-Sector Collaboration for AI Governance
- Evaluating Long-Term AI Outcomes
- Public Engagement and Communication
- Continuous Learning and Feedback Systems
Module 6: Case Studies and Practical Applications
- Case Study: Predictive Policing and Its Challenges
- AI in Healthcare Policy and Ethical Issues
- Algorithmic Bias in Welfare Decision Systems
- Lessons from Global AI Governance Practices
- Hands-On: Identifying Bias in Real-World AI Tools
- Strategies for Scaling Ethical AI Practices
Take the first step toward creating fair and ethical AI systems in public policy. Join the Workshop: Combatting AI Bias in Public Policy Tools by Tonex and equip yourself with the knowledge and tools to drive responsible AI innovation. Sign up today!