Sara Hooker
Titles as the sources gave them. In 1 entry, with 0 checked quotations.
In the Base
Every entry they appear in.
Understanding AI from the Inside: The State of Mechanistic Interpretability for AI Safety
According to the abstract, Barez and 26 co-authors survey mechanistic interpretability and ask whether understanding how models work makes them safer. They propose a framework for evaluating interpretability claims, discuss limits, and release code notebooks.