SAFARI：一种社区参与的方法和撒哈拉以南非洲语境下的刻板印象资源数据集
SAFARI: A Community-Engaged Approach and Dataset of Stereotype Resources in the Sub-Saharan African Context
AI总结：
SAFARI通过社区参与方法构建了覆盖四个撒哈拉以南非洲国家的多语言刻板印象资源数据集，旨在填补NLP资源的空白。
摘要：
刻板印象库对于评估生成式AI模型的安全性至关重要，但目前缺乏足够的全球覆盖。必须优先考虑有针对性的扩展，战略性地解决现有缺陷，而不是仅仅增加数据量。本文介绍了一个涵盖四个严重缺乏NLP资源的撒哈拉以南非洲国家的多语言刻板印象资源：加纳、肯尼亚、尼日利亚和南非。通过利用具有社会文化背景的社区参与方法，包括用母语进行的电话调查，我们建立了一种可复制的方法，该方法对该地区复杂的语言多样性以及传统口头文化敏感。通过有意平衡样本在不同民族和人口背景中的多样性，我们确保了广泛的覆盖，最终得到一个包含3534个英语刻板印象和15种母语中3206个刻板印象的数据集。
英文摘要：
Stereotype repositories are critical to assess generative AI model safety, but currently lack adequate global coverage. It is imperative to prioritize targeted expansion, strategically addressing existing deficits, over merely increasing data volume. This work introduces a multilingual stereotype resource covering four sub-Saharan African countries that are severely underrepresented in NLP resources: Ghana, Kenya, Nigeria, and South Africa. By utilizing socioculturally-situated, community-engaged methods, including telephonic surveys moderated in native languages, we establish a reproducible methodology that is sensitive to the region's complex linguistic diversity and traditional orality. By deliberately balancing the sample across diverse ethnic and demographic backgrounds, we ensure broad coverage, resulting in a dataset of 3,534 stereotypes in English and 3,206 stereotypes across 15 native languages.
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。
