Yangman Zhang
Research Mentor(s): Joshua Ashkinaze
Mentor Department:
Authors: Joshua Ashkinaze, Amelia Zhang
Session: Session 3 (11:00am – 11:50am)
Presentation Type: Poster 51
Abstract
The background of our project expands from the idea that personal experiences shape attitudes, but individuals are limited to their own lived experiences. Our research explores whether artificial intelligence can bridge this experiential gap by generating personalized counterfactual scenarios. We developed a multi-agent AI system that integrates psychological theories of narrative transportation, mental simulation, and imagined contact to help users immerse themselves in alternative life experiences. We performed this research because we want to understand how greater exposure to diverse perspectives can foster empathy and reduce bias and we implemented AI-driven narratives to simulate life experiences beyond their own. Our work builds on Construal Level Theory (CLT), which suggests that psychologically distant events are processed abstractly, making narratives an effective tool for attitude change. Also research on narrative transportation (Green & Brock, 2000) shows that immersive storytelling reduces resistance to new perspectives. Our project is significant in a way that it contributes to AI-driven interventions by adopting interactive storytelling to promote empathy and attitude change. By simulating diverse perspectives, our research could influence real-world social interactions and policy attitudes.
