Role of Mechanistic Interpretability in AI Safety

Determine the exact role that mechanistic interpretability can play in addressing AI safety for transformer-based language models, clarifying how mechanistic interpretability results should be used to mitigate risks.

Background

Mechanistic interpretability is widely discussed as a potential approach to improve the safety and reliability of LLMs, including efforts such as enumerative safety and generation steering. Despite these efforts, the survey explicitly notes uncertainty regarding the precise contribution of mechanistic interpretability to AI safety.

Clarifying the role of mechanistic interpretability would help define concrete pathways for its deployment in risk mitigation, governance, and alignment work.