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arXiv Computer Vision By Amalia Foka

Playing Bias: Epistemic Games for Interpreting Text-to-Image Models

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The paper "Playing Bias: Epistemic Games for Interpreting Text-to-Image Models" proposes a three-stage, humanities-informed framework—Interpret, Interrogate, and Expose—to make the cultural work of text-to-image (T2I) systems visible and debatable. These epistemic games, tested with undergraduate fine‑arts students, shift discussions from impressionistic reactions to concise, evidence‑based hypotheses, using lightweight classroom tools for reproducibility and structured collaboration. The authors argue that such game‑based approaches foster critical literacy, enabling learners to recognize, discuss, and contest how T2I models encode bias.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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