AI aids but does not replace human expertise in decoding endangered and extinct languages: systemic challenges and collaborative pathways
Original framing: “What happens when you put AI to work deciphering lost languages?” — Ars Technica
The loss of languages is rooted in centuries of colonization, forced assimilation, and missionary schooling, echoing the fate of the Rosetta Stone and the decipherment of Linear B. Historical precedents show that top‑down scholarly interventions often ignored community agency, leading to partial or biased reconstructions. Understanding these patterns cautions against repeating past mistakes and highlights the need for reparative scholarship.
The drive to decode lost languages with AI masks a complex web of colonial histories, power imbalances, and epistemic inequities that only a systemic lens can reveal.
By foregrounding Indigenous custodians, historical accountability, and cross‑cultural linguistic diversity, we can reshape AI from a solitary tool into a collaborative platform that respects cultural sovereignty. Integrating scientific rigor with artistic‑spiritual insight, future‑modelling, and marginalised voices creates resilient pathways for language revitalization. Trickster logic reminds us that the allure of technological miracles must be tempered by humility and shared authority, lest we repeat past extractive practices.