Recent research has revealed undesirable biases in NLP data and models. However, these efforts largely focus on social disparities in the West, and are not directly portable to other geo-cultural contexts. In this position paper, we outline a holistic research agenda to re-contextualize NLP fairness research for the Indian context, accounting for Indian societal context, bridging technological gaps in capability and resources, and adapting to Indian cultural values. We also summarize findings from an empirical study on various social biases along different axes of disparities relevant to India, demonstrating their prevalence in corpora and models.
翻译:最近的研究揭示了NLP数据和模型中的不良偏差,然而,这些努力主要侧重于西方的社会差异,不能直接从其他地理文化背景中吸收。在本立场文件中,我们概述了一项整体研究议程,以重新将NLP公平研究与印度背景重新联系起来,考虑到印度的社会背景,缩小能力和资源方面的技术差距,并适应印度文化价值观。我们还总结了一项经验研究的结果,该研究涉及与印度相关的不同差异轴心上的各种社会偏见,表明这些偏见在公司和模型中的流行程度。