When language becomes AI data, timing shapes power. Decolonising tech means working with underserved language communities from the start.
Synopsis
Lindsey DeWitt Prat, PhD Debates about linguistic decolonisation often turn on two positions: restoring languages displaced by colonialism, or affirming community choice to adopt, adapt, or reject any linguistic tools, including ex-colonial ones.
Both approaches centre agency, and for good reason. But when language is turned into data for computational systems, timing matters too. Industry and academia are often cast as fast and slow, but the reality is messier. Decisions about data get made quickly; consequences unfold over much longer horizons. Language is dynamic and context-dependent; datafication fixes particular forms at a given moment and leaves others out. Speakers of underserved languages adapt fast - out of necessity, not preference - to systems built without them.
This talk explores temporal dynamics through two bodies of work: industry research with African languages and large language models, and an academic meta-review of AI data production and its impacts on underserved communities worldwide.
Across different tempos, both works foreground the need for anthropological and participatory methods alongside technical work - early, not late. That integration is itself a question of timing and an example of what decolonial method can look like in 2026.
About the speaker
Lindsey DeWitt Prat is a research leader translating languages, cultures, and complexity across technological contexts. Her recent publications and speaking engagements explore pathways for making AI more inclusive and culturally resonant through contextual understanding of people and societies.
She is currently a Director at Bold Insight, a board member of EPIC, and an Adjunct Senior Research Fellow at The University of Western Australia. Lindsey holds a PhD in Asian Languages & Cultures from UCLA and an MA in International Studies and Comparative Religion from the University of Washington.
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