cs.CY提交于 2026-10-26已译

玩转偏见：用于解读文本到图像模型的认知游戏

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

Amalia Foka

中文摘要

文本到图像(T2I)系统不只是渲染提示词，还会流通“X 看起来是什么样”的默认设定，通过姿态、镜头、服装、道具和场景塑造认知。现有多样性审计虽能量化差距，却很少培养论证图像如何组装刻板印象并赋予其权威的素养。论文将一套三阶段、人文学科启发的框架转化为认知游戏：解读(Interpret)结合艺术史细读与 AI 输出，追问(Interrogate)通过反意图提示开展艺术探索，揭示(Expose)则用成对提示词、固定母题及 BiasSlot 规则进行创意误用，仅改变偏见线索。本科美术专业学生的试点显示，游戏使讨论从直觉反应转向基于视觉证据、简洁且有依据的假设；轻量课堂工具支持复现与结构化协作。此类游戏方法可在教育环境中培养批判素养，帮助学习者识别、讨论并质疑 T2I 模型如何编码偏见。

关键要点

01现有 T2I 偏见审计多量化差异，较少培养解释图像如何组装刻板印象并赋予权威的能力。
02三阶段认知游戏包括解读、追问和揭示，其中 BiasSlot 规则仅改变偏见线索。
03美术专业学生试点中，讨论由印象式反应转向基于视觉证据的简洁且有依据的假设。
04轻量课堂工具支持实验复现与结构化协作，使模型偏见更易观察和讨论。
05游戏化方法面向教育场景培养批判素养，帮助识别、讨论并质疑 T2I 模型的偏见编码。

解读

尚无解读。

原始英文摘要

arXiv:2610.32159v1 Announce Type: cross Abstract: Text-to-image (T2I) systems do not merely render prompts; they circulate defaults for "what X looks like," shaping recognition through pose, camera, costume, props, and setting. While technical audits quantify disparities, they rarely cultivate the literacy needed to argue how images assemble stereotypes and confer authority. This paper translates a three-stage, humanities-informed framework into a set of epistemic games that make this cultural work visible and debatable: Interpret (art-historical close looking with AI outputs), Interrogate (counter-intent prompting as artistic exploration), and Expose (creative misuse through paired prompts with a constant motif and a BiasSlot rule, in which only the bias cue varies). In a pilot with undergraduate fine-arts students, the games shifted discussion from impressionistic reactions to concise, warranted hypotheses grounded in visual evidence, supported by lightweight classroom instruments that enabled reproducibility and structured collaboration. We argue that such game-based approaches foster critical literacy across educational contexts, equipping learners to recognize, discuss, and contest how T2I models encode bias.