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: 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 t