On the Practical Applications of AI Interpretability
Introduction
This post was either an anonymous submission of an interesting paper or was written by a student; full credit remains with the author (linked).
Written in the wake of the excitement around sparse autoencoders, this post asks what comes next for interpretability once the initial hype fades. Rather than focusing only on AI safety framings, the author lays out hypotheses for how interpretability could become genuinely useful in industry — starting with model debugging as a practical, near-term application.