Theoretical Aspects of Trustworthy AI

Overview

Explore the theoretical aspects of trustworthy AI in this insightful presentation by Susmit Jha from SRI International, a leading organization in technological innovations. Discover the key concepts and challenges that define the trustworthy AI landscape in this enlightening session.

Available now on YouTube.

• Deep dive into trustworthy AI
• Pioneering insights by Susmit Jha
• Challenging concepts and innovative solutions

Syllabus

• Introduction to Trustworthy AI
Definition and importance of trustworthy AI
Overview of trust in AI systems
• Key Concepts in Trustworthy AI
Fairness and bias mitigation in AI
Explainability and interpretability
Robustness and reliability in AI models
• Theoretical Foundations
Formal methods in AI
Verification and validation techniques
The role of logic and reasoning in trustworthy AI
• Challenges in Trustworthy AI
Scalability of trustworthy systems
Handling uncertainty and probabilistic reasoning
Addressing ethical and societal implications
• Case Studies and Applications
Real-world examples of trustworthy AI systems
Analysis of failures and trust breaches in AI
• Future Directions in Trustworthy AI
Emerging technologies and their impact on trust
Advancements in AI safety and governance
• Conclusion
Recap of key concepts
Open questions and areas for further research

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Subjects

Computer Science