OpenAI's new research reveals the 'counterintuitive' truth about AI safety: For the safety of humanity, AI needs to 'think slowly.' In the rapid development of AI, we often fall into a misconception: the larger the model parameters and the faster the response, the more advanced it is. However, OpenAI's latest paper, *Monitoring Monitorability*, throws cold water on this 'efficiency-only' mindset and raises a core question about the future of AGI safety. It's not just about whether AI gives the right answers, but whether we can understand how it thinks. This research introduces a critical concept: 'Monitorability.' In simple terms, it’s about whether humans can effectively detect lies or dangerous intentions in AI by observing its 'Chain-of-Thought.' The research team discovered a highly valuable 'golden rule': the longer the chain of thought, the harder it is for AI to hide its intentions. When we force models to fully 'spill' their thought processes—like asking students to write out detailed problem-solving steps—human supervisors can more accurately spot errors or signs of deception in its logic. But this comes with a thought-provoking cost: The 'Monitorability Tax.' To gain this level of transparency for safety, we must pay an additional computational cost. The paper’s data shows that a combination of a 'small model + deliberate reasoning (longer inference)' is often more monitorable than a 'large model + quick intuitive answers.' Although the former consumes more reasoning power and seems 'less efficient,' it makes the AI’s black box more transparent and observable. This suggests that the path to safe Artificial General Intelligence (AGI) may no longer be about simply stacking up larger parameters, but about learning to balance 'subtraction' and 'addition': we may need to accept that AI should think slower and longer, using computational resources to buy humanity control over AI. The impact of this research lies in how it transforms 'AI safety' from an abstract ethical slogan into a quantifiable, cost-calculable engineering metric. In the future, when we face superintelligent AIs far smarter than humans, this mechanism of 'trading time for safety' might be the last line of defense to prevent them from hiding their true intentions from humanity. Chinese translation of the paper: https://(randomarea.com)/monitoring-monitorability/