teleo-codex/entities/ai-alignment/spar-automating-circuit-interpretability.md

type	entity_type	name	status	founded	parent_org	domain	supports	reweave_edges
entity	research_program	SPAR Automating Circuit Interpretability with Agents	active	2025	SPAR (Scalable Alignment Research)	ai-alignment	Circuit tracing requires hours of human effort per prompt which creates a fundamental bottleneck preventing interpretability from scaling to production safety applications	Circuit tracing requires hours of human effort per prompt which creates a fundamental bottleneck preventing interpretability from scaling to production safety applications|supports|2026-04-08

SPAR Automating Circuit Interpretability with Agents

Research program targeting the human analysis bottleneck in mechanistic interpretability by using AI agents to automate circuit interpretation work.

Overview

SPAR's project directly addresses the documented bottleneck that 'it currently takes a few hours of human effort to understand the circuits even on prompts with only tens of words.' The program attempts to use AI agents to automate the human-intensive analysis work required to interpret traced circuits, potentially enabling interpretability to scale to production safety applications.

Approach

Applies the role specialization pattern from human-AI mathematical collaboration to interpretability work, where AI agents handle the exploration and analysis while humans provide strategic direction and verification.

Timeline

• 2025 — Program initiated to address circuit tracing scalability bottleneck
• 2026-01 — Identified by Mitra as the most direct attempted solution to the hours-per-prompt constraint