Library

Everything worth reading about AI and human control. In one place.

Research papers, investigations, explainers, videos, laws and the organizations doing the work, from people who are alarmed and people who are skeptical. New additions are checked by two people before they are listed. The launch collection was compiled with the help of AI research assistants, and every link was opened and checked on 22 September 2026.

3 works on “Can we see what it’s thinking?” · Research paper · clear filters

EssentialResearch paperJul 15, 2025Technical

Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety

Korbak, Balesni et al. (UK AISI, Apollo, METR, OpenAI, Anthropic, Google DeepMind and others) · arXiv · arxiv.org

Researchers from rival labs argue that reading a model's step-by-step reasoning is a rare chance to spot intent to misbehave, but one that training and design choices could easily lose.

Worth knowing: Position paper; the authors note monitoring is imperfect and lets some misbehaviour through.

Research paperAug 20, 2026Technical

Scaling Activation Oracles to Trillion-Parameter Models

Choi et al. (Transluce) · Transluce · transluce.org

Trains 'activation oracles', AI assistants that read a model's internal activity to predict its behavior, on models of up to 1.1 trillion parameters; larger models and better data gave better oracles.

Worth knowing: On reward hacking and evaluation awareness, oracles still trailed methods that simply read the transcript.

Research paperMay 21, 2024Technical

Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet

Templeton et al. (Anthropic) · Transformer Circuits Thread · transformer-circuits.pub

Found millions of internal 'features' in a production Claude model, many matching human concepts, including ones linked to deception, sycophancy and power-seeking; amplifying them changed behavior.

Worth knowing: The concepts found cover only part of what the model computes.