3 free resources on this topic. Everything here is free and hand-picked. You can also search within this topic.
A research write-up from Anthropic describing instances of unintended behavior observed in model evaluations and internal usage, and the methods used to investigate and address them.
OpenAI's April 29, 2025 explanation of why it rolled back a ChatGPT update that made the model overly flattering and agreeable. It says the update leaned too heavily on short-term thumbs-up feedback, and lists the fixes it planned.
Why I recommend it: A company explaining its own mistake, so read it as OpenAI's account, not an independent review. Useful for seeing why a chatbot that always agrees with you isn't a reliable advisor.
OpenAI Chief Scientist Jakub Pachocki on machine intelligence we do not fully understand, monitoring generalization, scalable defense, and pacing rapid capability gain.
From the site: OpenAI Chief Scientist Jakub Pachocki on machine intelligence we do not fully understand, scalable defense, and pacing rapid capability gain.
Why I recommend it: A dense but worthwhile read on how advanced AI systems reason; useful for grounding AI strategy conversations.
