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arXiv · 2509.13679

"GenAI Defaults to Bias!" Gamify AI Literacy Through Reflections on Prompts

Qianou Ma·Megan Chai·Yike Tan·Jihun Choi·Jini Kim·Erik Harpstead·Geoff Kauffman·Tongshuang Wu
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Abstract

As Generative AI (GenAI) becomes widespread, it is increasingly important for the public to understand the model's behaviors and biases. However, existing AI literacy efforts miss opportunities to engage the general public to reflect on enduring GenAI bias and behaviors (e.g., how GenAI defaults to its internal bias in response to ambiguous or challenging prompts). In this work, we introduce ImaginAItion, a multiplayer game to help adults better reflect on GenAI bias and understand GenAI behaviors. ImaginAItion is grounded in reflective play to surface GenAI limitations by encouraging players to manipulate prompt specificity (e.g., an underspecified prompt "CEO" defaults to a white man). From ten sessions (n=30), we find that the game significantly improved players' understanding of GenAI behaviors by 35% in accuracy. Qualitative analysis showed how game mechanisms supported player reflections, including on prompting strategies to mitigate GenAI bias. Our work demonstrates a viable pathway to scale GenAI literacy through playful, social interventions resilient to rapidly evolving technologies.

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Qianou Ma, Megan Chai, Yike Tan, Jihun Choi, Jini Kim, Erik Harpstead, Geoff Kauffman, Tongshuang Wu. 2025-09-17. "GenAI Defaults to Bias!" Gamify AI Literacy Through Reflections on Prompts. https://doi.org/10.1007/978-3-032-29763-1_7

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