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Challenges in Fostering (Dis)Trust in AI
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Classroom Contents
Local Explanations for Deep Learning Models - Fall 2023
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- 1 Course overview and logistics
- 2 Data Preparation & Transformer
- 3 Pretrain-Finetune; Uncertainty Estimation (Part 1)
- 4 Uncertainty (Part 2); Prompting; Chain-of-Thoughts
- 5 Prompting (Part 2); Evaluation of Free-Text Explanations
- 6 Gradient-based Input Attribution
- 7 Evaluation of Input Attribution
- 8 Select-then-Predict
- 9 Pairwise Feature Importance (Effective Attention)
- 10 Data Influence
- 11 Contrastive Explanations
- 12 Application-Grounded Evaluations of Explanations
- 13 Human Trust in AI
- 14 Challenges in Fostering (Dis)Trust in AI
- 15 Explainability as a Dialog
- 16 An Overview of Local Explainability Methods & Their Evaluation
