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.

翻译：在日益增长的手语识别、生成与翻译人工智能研究中，伴随着对这些技术伦理发展的呼吁。尽管这些工作对帮助个体研究人员改进至关重要，但明显缺乏对系统性偏见或塑造该领域研究问题与方法的修辞学分析讨论，尤其是在该领域仍由听力正常且非手语使用的研究者主导的现状下。因此，我们对101篇近期手语人工智能论文进行了系统综述。我们的分析揭示了当前手语人工智能研究中的显著偏见，包括过度关注解决所谓的沟通障碍、缺乏代表性数据集的使用、采用缺乏语言学基础的标注，以及基于有缺陷模型开发方法。我们认为，该领域缺乏来自聋人利益相关者的有意义的输入，反而由哪些决策对听力研究者最便利或被认为最重要所驱动。我们最终提出行动呼吁：该领域必须为聋人研究者创造空间，使其主导手语人工智能领域的对话。