MIT 6.S191: Introduction to Deep Learning - 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 Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!!