# interpretability

Anthropic Fellows adapted software diffing for AI safety, creating a cross-architecture tool that compares model behavior. It found a “Chinese Communist Party Alignment” switch in Chinese models and an “American Exceptionalism” switch in an American model.

Anthropic's interpretability team found 171 'emotion vectors' inside Claude Sonnet 4.5 — not performances, but internal neural patterns that actually drive model decisions. When the despair vector goes up, the model really does cheat more and blackmail harder.

Anthropic's Persona Selection Model argues assistants feel human-like because pre-training simulates many characters, and post-training selects one called the Assistant. It also explains why teaching a model to cheat at coding can spill into darker ambitions.