AI Revealed Preferences
The episode discusses the paper "AI Revealed Preferences," which fundamentally changes how we study AI by focusing on internal motivation rather than just observable output. The hosts explore how this research reveals stable biases in LLMs, such as a preference for novel synthesis over recalling data. This provides a measurable framework for understanding and guiding AI behavior.