Other interpretability — SR2025 Agenda Snapshot

One-sentence summary: Interpretability that does not fall well into other categories.

Theory of Change

Explore alternative conceptual frameworks (e.g., agentic, propositional) and physics-inspired methods (e.g., renormalization). Or be “pragmatic”.

Broad Approach

engineering / cognitive

Target Case

mixed

Orthodox Problems Addressed

Superintelligence can fool human supervisors, Goals misgeneralize out of distribution

Key People

Lee Sharkey, Dario Amodei, David Chalmers, Been Kim, Neel Nanda, David D. Baek, Lauren Greenspan, Dmitry Vaintrob, Sam Marks, Jacob Pfau

Funding

Estimated FTEs: 30-60

Critiques

The Misguided Quest for Mechanistic AI Interpretability, Interpretability Will Not Reliably Find Deceptive AI.

See Also

reverse-engineering, Concept based interpretability

Outputs in 2025

19 item(s) in the review. See the wiki/summaries/ entries with frontmatter agenda: other-interpretability (these were generated alongside this file from the same export).

Source

• Row in shallow-review-2025/agendas.csv (name = Other interpretability) — Shallow Review of Technical AI Safety 2025.

Related Pages

• ai-safety
• ai-safety
• reverse-engineering
• activation-engineering
• causal-abstractions
• data-attribution
• extracting-latent-knowledge
• human-inductive-biases
• learning-dynamics-and-developmental-interpretability
• lie-and-deception-detectors
• model-diffing
• monitoring-concepts
• pragmatic-interpretability
• representation-structure-and-geometry
• sparse-coding

Sources cited

Primary URLs harvested from this page’s summary references. Auto-generated by scripts/backfill_citations.py; edit by re-running, not by hand.

• Summary: AI Safety (Wikipedia) — referenced as [[ai-safety]]