Decolonising Speech and Language Technology

By Steven Bird. 2020

236 citations recorded by the source corpus.

After generations of exploitation, Indigenous people often respond negatively to the idea that their languages are data ready for the taking. By treating Indigenous knowledge as a commodity, speech and language technologists risk disenfranchising local knowledge authorities, reenacting the causes of language endangerment. Scholars in related fields have responded to calls for decolonisation, and we in the speech and language technology community need to follow suit, and explore what this means for our practices that involve Indigenous languages and the communities who own them. This paper reviews colonising discourses in speech and language technology, and suggests new ways of working with Indigenous communities, and seeks to open a discussion of a postcolonial approach to computational methods for supporting language vitality.

Subfields: Artificial Intelligence, Cultural Studies, Language and Linguistics, Natural Language Processing, Safety, Robustness & Interpretability

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Citations in the corpus

Societal Biases in Language Generation: Progress and Challenges (2021, methodology): “However, we acknowledge that this remains a difﬁcult task and that it is also necessary to be aware of “community goals” and other factors in order to co-design language technologies without inﬂicting additional harm on marginalized populations (Bird, 2020).”
Five sources of bias in natural language processing (2021, background): “Recent work by Bird (2020) suggests new ways of collaborating with Indigenous communities in the form of open discussions and proposes a postcolonial approach to computational methods for supporting language vitality.”
Challenges and Strategies in Cross-Cultural NLP (2022, background): “Decolonisation (Bird, 2020; Mohamed et al., 2020; Birhane and Guest, 2021) aims to dismantle harmful power asymmetries and concepts of knowledge, turning us instead towards a “pluriversal epistemology of the future” (Mignolo, 2012) that unlike universalisms, acknowledges and supports a wider radius ”
Building Machine Translation Systems for the Next Thousand Languages (2022, background): “See Bird (2020) for some more reflections on this term.”