SocialCounterfactuals: Probing and Mitigating Intersectional Social Bias with Counterfactuals

Overview

Syllabus

• Introduction to Social Bias in AI
Understanding Social Bias and Its Impact
Intersectionality in AI Systems
Overview of Mitigating Techniques
• Introduction to Counterfactuals
Definition and Theory of Counterfactuals
Historical Context and Applications in AI
• Probing Social Bias with Counterfactuals
Techniques for Generating Counterfactuals
Identifying Bias Through Counterfactual Analysis
Case Studies: Real-World Applications
• Mitigating Intersectional Bias Using Counterfactuals
Designing Bias-Resistant AI Models
Counterfactual Fairness: Theory and Practice
Strategies for Implementing Counterfactual Mitigations
• Tools and Frameworks for Counterfactual Analysis
Overview of Popular Tools and Libraries
Hands-on Session: Using Counterfactual Tools
• Evaluation of Counterfactual Methodologies
Metrics for Success in Bias Mitigation
Challenges and Limitations in Current Approaches
Ethical Considerations in Counterfactual Usage
• Emerging Trends and Future Directions
Recent Innovations in Counterfactual Research
The Future of Equitable AI Systems
Ongoing Research and Community Efforts
• Conclusion and Course Recap
Key Takeaways on Counterfactuals and Bias
Discussion: Pathways to More Equitable Technology
• Capstone Project
Application of Course Concepts to a Real-World Problem
Presentation and Peer Review of Solutions

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Subjects

Computer Science