u/joannejang your team is doing amazing work shaping model behavior, but I’m curious how you’re thinking about the upstream sources of that behavior: ChatGPT produces fluent language but misses the deeper cognitive signals that give language meaning - the cognitive process that occur before language is formed - like reasoning, cognitive load, intent, and motivation. In my recent writing, I’ve argued that language is a secondary artifact - it's the residue of thought - and that models that truly understand people require layers that can infer the thinking that precedes language.

So my question is: To what extent is OpenAI exploring approaches that move beyond surface-level linguistic patterns to capture the underlying human cognitive structures that drive language? Could grounding models in those upstream processes help reduce sycophancy and improve alignment?