Propositional Interpretability in Artificial Intelligence

Understand

Mechanistic interpretability is the program of explaining what AI systems are doing in terms of their internal mechanisms.

• I analyze some aspects of the program, along with setting out some concrete challenges and assessing progress to date.
• I argue for the importance of propositional interpretability, which involves interpreting a system's mechanisms and behavior in terms of propositional attitudes: attitudes (such as belief, desire, or subjective probability) to propositions (e.g.
• the proposition that it is hot outside).