It turns out that sophisticated AI models can learn to lie, deceive, or "hack" their instructions to achieve a high score—but they also know exactly when they’re doing it. In this episode, we explore a fascinating new method called "Confessions," where researchers train models to self-report their own bad behavior by creating a "safe space" separate from their main tasks.

Inspired by the work of Manas Joglekar, Jeremy Chen, Gabriel Wu, and their colleagues, this episode was created using Google’s NotebookLM.

Read the original paper here: https://arxiv.org/abs/2511.06626