Fostering Linguistic Justice in Digital Spaces: Using Indigenous Methods in the Study of NLP

Data and data modeling practices in natural language processing (NLP) privilege languages with the greatest levels of representation online, leaving behind speakers of the overwhelming majority of the world's languages from enjoying the full benefits of digital inclusion. These dynamics have been explored in the context of historic colonial relationships, with linguists and language activists noting the colonizing discourses around the adoption of language-related technologies, and highlighting problematic research practices among linguists and computational linguists working in the area of digital corpus development for minoritized and Indigenous languages. Such power differentials raise questions about the source(s) and nature of language technology development bias in Global South contexts. To that end, this paper is divided into three parts. The first addresses the identification and roots of bias in NLP as it is currently understood, emphasizing the particular ways it is expressed in Global South contexts, and Latin America in particular. The second briefly discusses the theoretical frameworks of data colonialism and Indigenous data sovereignty as mechanisms to clarify how bias in NLP operates in these contexts. In the third section, Indigenous methods are proposed to investigate how these frameworks can help illuminate a research ethics around NLP for minoritized languages. Although there is an abundance of literature addressing ethics in NLP, no work to date has utilized an Indigenous methods framework to examine bias in the field, even as it relates specifically to Indigenous language data and technologies. This work argues that Indigenous methods can ultimately yield deeper insights into the concepts of bias and fairness in NLP, as well as the motivations and decisions employed in the development of language technologies, thereby serving as a more effective generator of equitable solutions while advancing theory development.