How to Fail Interpretability Research

How to Fail Interpretability Research

Explore the pitfalls and misconceptions in interpretability research with Google Brain's Been Kim in this 45-minute talk from the Simons Institute's "Emerging Challenges in Deep Learning" series. Delve into common mistakes and misunderstandings in the field, including the pursuit of universal definitions, performance trade-offs, and evaluation methods. Examine the responsibilities of researchers in presenting explanations and the real-world implications of their work. Gain insights on how to approach interpretability research more effectively and ethically, avoiding common traps that can hinder progress in this crucial area of machine learning.