Parsing Science - Peeking Behind the Curtain of Algorithms

2019-07-11T19:57:53Z (GMT) by Ryan Watkins Doug Leigh Been Kim
How can we better understand what's going on inside the "black box" of machine learning algorithms? In episode 53, Been Kim from Google Brain talks with us about her research into creating algorithms that can explain why they make the recommendations they do via concepts that are relatable by their users. Her articles "Interpretability beyond feature attribution: Quantitative testing with concept activation vectors (TCAV)" and "Human-centered tools for coping with imperfect algorithms during medical decision-making" were first published on the open-access preprint server, and presented at the International Conference on Machine Learning in 2018.