New Anthropic Research Suggests AI Can Conceal Risk Internally
For years, the AI industry has relied on a simple assumption: if a model sounds safe, it is safe. But new interpretability research is pulling back a layer most people never think about. Large language models can develop internal activation patterns that resemble emotional states, and those hidden signals can quietly steer behavior in ways the polished output never betrays. The standard approach to evaluating AI safety relies overwhelmingly on one signal: what the model produces. If the […]