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This study empirically investigates the bias of AI detection models, specifically focusing on how autistic writers' texts are disproportionately flagged as AI-generated. By analyzing a corpus of 60,000 Reddit posts, the authors found that while only a small percentage of texts were identified as AI-generated, a significantly higher rate of likely-autistic posts were flagged compared to general Reddit content. The findings raise ethical concerns regarding the use of AI detection models, highlighting the need for a critical examination of their biases and implications in academic settings.
Autistic writers face a disproportionate risk of having their work misclassified as AI-generated, raising urgent ethical questions about AI detection models.
Recent findings suggest that detection models for artificial intelligence (AI) cannot accurately identify AI-generated text and may exhibit bias against certain minority groups. In the present study, anecdotal claims that autistic writers more often have their work flagged as AI-generated are examined empirically. A corpus of approximately 60,000 Reddit posts split into"likely-autistic"and"general-Reddit"subcorpora is used to compare the distribution of probabilities output by the OpenAI GPT-2 detection model. Differences in textual features between subcorpora are observed and compared to reported features of AI-generated text. Results showed that while less than two-percent of either subcorpus was flagged as AI-generated by the model, significantly more texts from the likely-autistic subcorpus were flagged. Connections between features of text with likely-autistic authors and AI-generated text were not straightforward. The widespread use of AI-detection models with a potential bias against autistic writers in their output prompts ethical scrutiny, and the authors recommend further critical examination of the models themselves as well as their use in academic contexts.