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Beginnt 6 June 2026 14:03
Endet 6 June 2026
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28 minutes
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Übersicht
Lehrplan
- Introduction to Social Bias in AI
- Introduction to Counterfactuals
- Probing Social Bias with Counterfactuals
- Mitigating Intersectional Bias Using Counterfactuals
- Tools and Frameworks for Counterfactual Analysis
- Evaluation of Counterfactual Methodologies
- Emerging Trends and Future Directions
- Conclusion and Course Recap
- Capstone Project
Understanding Social Bias and Its Impact
Intersectionality in AI Systems
Overview of Mitigating Techniques
Definition and Theory of Counterfactuals
Historical Context and Applications in AI
Techniques for Generating Counterfactuals
Identifying Bias Through Counterfactual Analysis
Case Studies: Real-World Applications
Designing Bias-Resistant AI Models
Counterfactual Fairness: Theory and Practice
Strategies for Implementing Counterfactual Mitigations
Overview of Popular Tools and Libraries
Hands-on Session: Using Counterfactual Tools
Metrics for Success in Bias Mitigation
Challenges and Limitations in Current Approaches
Ethical Considerations in Counterfactual Usage
Recent Innovations in Counterfactual Research
The Future of Equitable AI Systems
Ongoing Research and Community Efforts
Key Takeaways on Counterfactuals and Bias
Discussion: Pathways to More Equitable Technology
Application of Course Concepts to a Real-World Problem
Presentation and Peer Review of Solutions
Fachgebiete
Computer Science