Seeking Indigenous Data Sovereignty in the Age of Data Scraping: The Digital Archive of Indigenous Language Persistence (DAILP)

The problem of data extraction to feed LLMs impacts all digital archives and open-sourced initiatives. Though the practice of data-scraping bots used to create the LLMs that feed algorithms is recent, extractivist models of language documentation are nothing new. To redress the challenges presented by extractivist methods, Indigenous language scholars and linguists as well as digital archivists and librarians have innovated methodologies to provide for a mutually sustaining relationship between language documentation efforts and indigenous language practices with the goal of enhancing language persistence practices and recuperating dormant practices. The Digital Archive of Indigenous Language Persistence (DAILP) at Northeastern University provides one effort to redress extractivist methods using Indigenous Data Sovereignty methodological frameworks. In this essay, I describe the CARE heuristic in relation to DAILP’s goals and methods to support the decision making required to meet the challenges of language extractivism. Though data scraping for LLMs presents ongoing challenges, Indigenous data-sovereignty methodologies allow language persistence with Indigenous communities and digital archives.