Evan discusses the differences between deception and corrigible behavior in AI models. He explains how deception can be simpler to achieve during training, while corrigible behavior requires building a robust pointer to the correct objective. The podcast explores the challenges of understanding simplicity in neural networks and its implications for training processes.
