MIT Introduction to Deep Learning 6.S191: Lecture 5
Robust and Trustworthy Deep Learning
Lecturer: Sadhana Lolla (Themis AI, https://themisai.io)
2023 Edition

For all lectures, slides, and lab materials: http://introtodeeplearning.com​

Lecture Outline
0:00 - Introduction and Themis AI
3:46 - Background
7:29 - Challenges for Robust Deep Learning
8:24 - What is Algorithmic Bias?
14:13 - Class imbalance
16:25 - Latent feature imbalance
20:30 - Debiasing variational autoencoder (DB-VAE)
23:24 - DB-VAE mathematics
27:40 - Uncertainty in deep learning
29:50 - Types of uncertainty in AI
32:48 - Aleatoric vs epistemic uncertainty
33:29 - Estimating aleatoric uncertainty
37:42 - Estimating epistemic uncertainty
44:11 - Evidential deep learning
46:44 - Recap of challenges
47:14 - How Themis AI is transforming risk-awareness of AI
49:30 - Capsa: Open-source risk-aware AI wrapper
51:51 - Unlocking the future of trustworthy AI


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