Dialect bias is pervasive yet often unconscious, normalized, or obscured by masking. Existing HCI interventions primarily audit disparities and propose reactive fixes. We present CompassioMate, a dialect-aware serious game that nurtures perspective-taking through AI-mediated play. Players listen to audio samples to identify regional dialects, engage in simulated social interactions involving dialect discrimination, and explore branching narratives that reveal how changes in wording or stance can influence the outcomes. In a three-week field study with 20 university students, participants reported feeling comfortable when observing region-tailored dialogues; several described experiencing perspective change. We contribute: 1) a formative study identifying goals for safe action consequence modelling, 2) the design and evaluation of a serious game integrating dialect audio, region-mapping play, bias; and 3) design implications highlighting listener-side training, transparent evaluation, and narratives maintaining psychological well-being.
@article{arxiv.2603.14260,
title = {Gamifying Compassion: Mitigating Dialect Prejudice Through An AI-Driven Serious Game},
author = {Sicheng Lu and Erick Purwanto and Hong Liu and Aini Li and Adel Chaouch-Orozco},
journal= {arXiv preprint arXiv:2603.14260},
year = {2026}
}