OpenAI is testing called confessions, which is designed to make language models more honest by getting them to reveal when their answers are uncertain or flawed. Instead of relying only on traditional training signals, the approach teaches models to internally acknowledge mistakes, reasoning gaps, or unsupported claims so they can correct themselves before producing a final response. Early experiments show that models using this technique hallucinate less and provide clearer explanations of what they do or do not know. The idea is that encouraging models to reflect on their own outputs leads to safer behavior and more dependable reasoning. Overall, the piece highlights how internal self checking may become an important tool for improving future AI systems.
