Gamifying Compassion: Mitigating Dialect Prejudice Through An AI-Driven Serious Game

TL;DR

This paper introduces CompassioMate, an AI-driven serious game designed to reduce dialect prejudice by fostering perspective-taking through interactive audio-based activities and narratives, supported by a three-week field study.

Contribution

It presents a novel dialect-aware serious game that combines AI-mediated play and narrative exploration to mitigate dialect bias and promote perspective change.

Findings

Participants felt comfortable with region-specific dialogues

Several participants experienced perspective change

The game design supports safe exploration of dialect bias

Abstract

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.