Content revision 4e771eaf0390cc87b6c7c6fd8469f3508f6ceeec7119472e6c1ccf17e2e1e5d2

## Humans Disengage, Reasoning Models Persist: Separating Difficulty Registration from Deliberation Allocation

Research
Source ID research:humansDisengage
Original https://www.henryw.me/#/research#humansDisengage

I studied how people and large reasoning models allocate effort once a problem becomes difficult. Across visual abstraction, intuitive physics and relational reasoning, I analysed human response times alongside the length and content of reasoning traces, the text models generate before answering. Comparing attempts on the same problems let me separate sensitivity to difficulty from the allocation of further effort. On visual grid puzzles, successful human attempts lasted longer than failed ones, while the model analysis showed longer traces on failed attempts. Grid actions and reasoning traces helped characterise what happened during that extra work. I developed a resource-rational account in which continued reasoning depends on its expected progress, the value of that progress and the cost of pursuing it.

This makes the decision to continue a question about the return on further computation, and gives a basis for understanding how people and models can recognise the same difficulty yet pursue different courses of action.