Recent advancements in image generation technology have enabled widespread access to AI-generated imagery, prominently used in advertising, entertainment, and progressively in every form of visual content. However, these technologies often perpetuate societal biases. This study investigates the representation biases in popular image generation models towards people with disabilities (PWD). Through a comprehensive experiment involving several popular text-to-image models, we analyzed the depiction of disability. The results indicate a significant bias, with most generated images portraying disabled individuals as old, sad, and predominantly using manual wheelchairs. These findings highlight the urgent need for more inclusive AI development, ensuring diverse and accurate representation of PWD in generated images. This research underscores the importance of addressing and mitigating biases in AI models to foster equitable and realistic representations.

翻译：近期图像生成技术的进步使得人工智能生成图像得以广泛应用，在广告、娱乐及各类视觉内容中日益普及。然而，这些技术往往延续了社会偏见。本研究探讨了主流图像生成模型对残障人士的表征偏见。通过涵盖多个流行文生图模型的综合实验，我们分析了残疾的描绘方式。结果表明存在显著偏见：大多数生成图像将残障个体描绘为年长、悲伤且主要使用手动轮椅的形象。这些发现凸显了开发更具包容性人工智能的迫切需求，以确保生成图像中残障人士的多样化和准确表征。本研究强调了在人工智能模型中解决和缓解偏见的重要性，以促进公平且真实的表征呈现。