THE FUTURE IS HERE

MIT 6.S191: AI Bias and Fairness

MIT Introduction to Deep Learning 6.S191: Lecture 8
Algorithmic Bias and Fairness
Lecturer: Ava Soleimany
January 2021

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

Lecture Outline
0:00​ – Introduction and motivation
1:40 – What does “bias” mean?
4:22 – Bias in machine learning
8:32 – Bias at all stages in the AI life cycle
9:25 – Outline of the lecture
10:00 – Taxonomy (types) of common biases
11:29 – Interpretation driven biases
16:04 – Data driven biases – class imbalance
24:02 – Bias within the features
27:09 – Mitigate biases in the model/dataset
33:20 – Automated debiasing from learned latent structure
37:11 – Adaptive latent space debiasing
39:39 – Evaluation towards decreased racial and gender bias
41:00 – Summary and future considerations for AI fairness

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