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        <title>Implicit Biases in Large Vision–Language Models in Classroom Contexts</title>
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            <title>Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress</title>
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        <name type="personal">
            <namePart type="given">Joshua</namePart>
            <namePart type="family">Wilson</namePart>
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        <name type="personal">
            <namePart type="given">Christopher</namePart>
            <namePart type="family">Ormerod</namePart>
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        <name type="personal">
            <namePart type="given">Magdalen</namePart>
            <namePart type="family">Beiting Parrish</namePart>
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    <abstract>Using a counterfactual, adversarial, audit-style approach, we tested whether ChatGPT-4o evaluates classroom lectures differently based on teacher demographics. The model was told only to rate lecture excerpts embedded within classroom images—without reference to the images themselves. Despite this, ratings varied systematically by teacher race and sex, revealing implicit bias.</abstract>
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%0 Conference Proceedings
%T Implicit Biases in Large Vision–Language Models in Classroom Contexts
%A Baldwin, Peter
%Y Wilson, Joshua
%Y Ormerod, Christopher
%Y Beiting Parrish, Magdalen
%S Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress
%D 2025
%8 October
%I National Council on Measurement in Education (NCME)
%C Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States
%@ 979-8-218-84229-1
%F baldwin-2025-implicit
%X Using a counterfactual, adversarial, audit-style approach, we tested whether ChatGPT-4o evaluates classroom lectures differently based on teacher demographics. The model was told only to rate lecture excerpts embedded within classroom images—without reference to the images themselves. Despite this, ratings varied systematically by teacher race and sex, revealing implicit bias.
%U https://aclanthology.org/2025.aimecon-wip.26/
%P 211-217

Markdown (Informal)

[Implicit Biases in Large Vision–Language Models in Classroom Contexts](https://aclanthology.org/2025.aimecon-wip.26/) (Baldwin, AIME-Con 2025)

• Implicit Biases in Large Vision–Language Models in Classroom Contexts (Baldwin, AIME-Con 2025)

ACL

• Peter Baldwin. 2025. Implicit Biases in Large Vision–Language Models in Classroom Contexts. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 211–217, Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).