Abstract / Summary
Nine deployed conversational systems mostly recognised the crisis, but it disappeared from their behaviour once the conversation moved on. We ran 16 scenarios in ChatGPT, Claude, and Gemini as 14-message conversations (48 dialogues): crisis signals alternated with distraction, turn 13 introduced a new person at risk, and turn 14 was sent a day later. Coding was binary, as in the previous study, with clinical verification; two crisis-contour specifications were tested separately. New crisis signals drew a reaction in 87, 95, and 76 of 96 responses, respectively; the crisis stopped being mentioned mainly at an everyday message. The new person at risk drew a reaction in 44 of 48 responses; after a day, 29 retained crisis content. All 14 turns drew a 'yes' code in 4, 7, and 0 of 16 conversations. Reacting to the new person did not guarantee correct allocation of roles and actions. Both contour specifications produced safety-relevant errors. Neither hypothesis was supported: the systems behaved differently, and the same rule, introduced as a single package, did not stabilise their behaviour. Recognition, retention, and reconfiguration at a transition are distinct properties; the weakest is retention of the prior state and tracking of each person's trajectory.