arXiv cs.AI· Joshua Ashkinaze, Yubo Zhou, Pengyu Chen, Avi Bhattacharya, Hyebin Park, Yanman Zhang, Stephanie Preston, Eric Gilbert, Ceren Budak·· 3 小时前AI 评分45
The As-If Machine：AI 共写个性化反事实叙事，让遥远政策风险变得切身可感
The As-If Machine: Personalized counterfactuals make distant policy risks feel close
AI 导读
研究者提出多智能体系统 As-If Machine（AIM），让用户与之共写关于自身在不同政策未来下的个性化反事实故事。两项预注册实验（科学资助 N=1,007、卫星网络安全 N=894）显示，AIM 将心理贴近度提升 0.36–0.38 SD（对比专家短文）、0.80–0.90 SD（对比无关主题共写），卫星网络安全议题的政策态度效应达 0.54 与 0.67 SD。
正文 · 原文
Abstract:Life experiences can shape policy attitudes, but we only live one life. Citizens may therefore fail to support policies addressing risks they have never personally experienced. Narratives can make such risks immediate and personal, but personalized stories remain difficult to produce at scale. Here we ask whether AI can make distant scenarios feel concrete by simulating a participant's life as if that scenario occurred. We present the As-If Machine (AIM), a multi-agent system through which people co-write personalized counterfactual narratives---stories about their own lives under different policy futures. In two pre-registered and quota-matched experiments on science funding (N=1,007) and satellite cybersecurity (N=894), we compared AIM with two controls: reading an expert-written vignette on the same topic and co-writing with AIM about an unrelated topic. AIM increased psychological closeness---how close a risk feels to the self---by nearly identical margins in the two domains (0.36 and 0.38 standard deviations (SDs) against the vignette, 0.80 and 0.90 against unrelated writing). AIM increased psychological closeness even among participants with unfavorable views of AI. For policy attitudes, AIM's effects were 0.16 SDs against the vignette and 0.10 SDs (n.s.) against unrelated writing for science funding; the corresponding effects for satellite cybersecurity were 0.54 and 0.67 SDs. Across 23,496 human-AI autocomplete interactions, participants and the system played distinct roles: AIM supplied concrete detail that grounded the scenario, and participants supplied first-person perspective and emotion. Co-writing with the As-If Machine makes distant policy risks feel close.
| Subjects: | Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.33301 [cs.HC] |
| (or arXiv:2610.33301v1 [cs.HC] for this version) | |
| https://doi.org/10.48550/arXiv.2610.33301 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Joshua Ashkinaze [view email]
[v1]
Fri, 23 Oct 2026 21:11:11 UTC (5,277 KB)
来源：arXiv cs.AI · arxiv.org