Closing keynote at #LLMSS2026 Hong Kong: Scott Hale (Oxford Internet Institute) on what four weeks with a relationship-seeking AI does to people. They used steering vectors to dial the model’s warmth directly — the treatment is the model’s disposition, not the prompt. N=3,534, randomised, longitudinal. Liking fell. Wanting rose. arxiv.org/abs/2512.01991

Day 2 keynote at #LLMSS2026 Hong Kong: Issa Dahabreh (Harvard Chan) on augmenting randomized trials. The question is old and the answer is hard: what are you entitled to conclude about a population you did not study? Epidemiology has twenty years on this. Most of us building synthetic samples are trying to re-invent it.

“A snapshot tells us where a person is — not how they got there.” Zhongyu Wei (Fudan) opening #LLMSS2026 in Hong Kong — SocioVerse 2.0, and the problem of simulating a population that changes its mind. github.com/FudanDISC/SocioVe…

Tomorrow the first Large Language Models and the Social Sciences conference opens in Hong Kong. Three days on what these models can do as research instruments, what happens when you use them as subjects, and what they are doing to the things we study. On one of those threads — using them as subjects — I’ve written up where I think the field actually stands. talkingtomachines.substack.c… #LLMSS2026

Reminder: Next week Talking to Machines (Oxford) and City University of Hong Kong host the first Large Language Models and the Social Sciences conference. Three days on what happens when you put a language model where a research subject used to be — and whether the answer means anything. 14–16 October, Hong Kong eps-academic.org/ai-conferen…