手语人工智能研究中的系统性偏见：由聋人主导的重新评估研究议程的呼吁
Systemic Biases in Sign Language AI Research: A Deaf-Led Call to Reevaluate Research Agendas
AI总结：
针对手语AI研究由听力研究者主导、存在系统性偏见的问题，研究通过综述101篇相关论文指出四类偏见，呼吁让聋人研究者主导该领域的研究议程。
摘要：
随着手语识别、生成与翻译人工智能领域研究的不断增长，学界也出现了对此类技术进行伦理化开发的呼吁。尽管这些工作对帮助个体研究者改进研究至关重要，但目前明显缺乏对塑造该领域研究问题与方法的系统性偏见的讨论，也缺乏对相关修辞的分析，尤其是该领域目前仍由听力正常且不会手语的研究者主导。为此，我们对手语人工智能领域的101篇近期论文开展了系统性综述。我们的分析发现，当前手语人工智能研究存在显著偏见，包括过度关注解决所谓的沟通障碍、缺乏具代表性的数据集的使用、采用缺乏语言学基础的标注，以及基于有缺陷的模型开发方法。我们认为，该领域缺乏聋人利益相关者的有意义参与，反而由听力研究者认为最方便或最重要的决策所驱动。最后我们提出行动呼吁：该领域必须为聋人研究者主导手语人工智能的讨论留出空间。
英文摘要：
Growing research in sign language recognition, generation, and translation AI has been accompanied by calls for ethical development of such technologies. While these works are crucial to helping individual researchers do better, there is a notable lack of discussion of systemic biases or analysis of rhetoric that shape the research questions and methods in the field, especially as it remains dominated by hearing non-signing researchers. Therefore, we conduct a systematic review of 101 recent papers in sign language AI. Our analysis identifies significant biases in the current state of sign language AI research, including an overfocus on addressing perceived communication barriers, a lack of use of representative datasets, use of annotations lacking linguistic foundations, and development of methods that build on flawed models. We take the position that the field lacks meaningful input from Deaf stakeholders, and is instead driven by what decisions are the most convenient or perceived as important to hearing researchers. We end with a call to action: the field must make space for Deaf researchers to lead the conversation in sign language AI.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
