Stop Calling Languages "Low-Resource"
The Issue
Stop Calling Languages "Low-Resource"
The Problem
For years, scientific journals, tech giants, funding agencies, and universities have labeled hundreds of human languages as "low-resource."
It sounds harmless, but it is not.
Languages are not intrinsically "low-resource." Every human language embodies rich knowledge systems, deep histories, vibrant cultures, and complex human intelligence. To call a language "low-resource" attributes a deficit to the language and its speakers, rather than placing the blame where it belongs: on historical exclusion, lack of technological investment, and biased digital infrastructure.
By confusing communicative richness with computational accessibility, the current terminology:
- Promotes a deficit-based view of linguistic communities instead of recognizing their knowledge systems.
- Obscures accountability by ignoring the political, economic, and technological causes of digital exclusion.
- Encourages extractive research, framing communities as "lacking" rather than as partners in knowledge.
- Muddies scientific precision, failing to specify whether a limitation is about audio, video, gesture, sign, mimic, touch, text scarcity, lack of annotations, or missing infrastructure.
- Reinforces systemic inequities in research funding and machine intelligence (MI) advancement.
Scientific excellence requires precision. Respect for human diversity requires terminology that identifies technological limitations without devaluing entire cultures.
Our Call to Action
We, researchers, educators, engineers, policymakers, and citizens, call upon scientific journals, conference committees, universities, tech organizations, and funding agencies to:
Discontinue the use of the term "low-resource languages" in all scientific publications, calls for proposals, policy reports, and official communications.
Adopt scientifically precise, context-dependent alternatives that accurately describe the actual source of the limitation, such as:
a) Infrastructure-limited processing
b) Annotation-limited environments
c) Speech-rich environments
d) Architecturally excluded modalities
e) Digitally occluded communicative systems
f) or other alternatives in the context of MI
Publicly funded institutions and scientific leaders have a responsibility to use terminology that is both methodologically sound and socially responsible. It is time to stop shifting the blame onto the languages themselves.
Why This Matters Now
As Machine Intelligence is reshaping our world, who gets heard and how they are represented matters more than ever. If we build the future of technology on terminology that devalues global languages, we institutionalize digital exclusion.
Scientific excellence requires conceptual precision. Respect for linguistic diversity requires terminology that accurately identifies technological and infrastructural limitations without attributing them to the languages themselves.
This petition is inspired by the arguments developed in:
Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6857538
Sign the Petition
Stand with us to demand scientific rigor, linguistic dignity, and an end to deficit-based labels in tech and academia.
Sign and share today!
49
The Issue
Stop Calling Languages "Low-Resource"
The Problem
For years, scientific journals, tech giants, funding agencies, and universities have labeled hundreds of human languages as "low-resource."
It sounds harmless, but it is not.
Languages are not intrinsically "low-resource." Every human language embodies rich knowledge systems, deep histories, vibrant cultures, and complex human intelligence. To call a language "low-resource" attributes a deficit to the language and its speakers, rather than placing the blame where it belongs: on historical exclusion, lack of technological investment, and biased digital infrastructure.
By confusing communicative richness with computational accessibility, the current terminology:
- Promotes a deficit-based view of linguistic communities instead of recognizing their knowledge systems.
- Obscures accountability by ignoring the political, economic, and technological causes of digital exclusion.
- Encourages extractive research, framing communities as "lacking" rather than as partners in knowledge.
- Muddies scientific precision, failing to specify whether a limitation is about audio, video, gesture, sign, mimic, touch, text scarcity, lack of annotations, or missing infrastructure.
- Reinforces systemic inequities in research funding and machine intelligence (MI) advancement.
Scientific excellence requires precision. Respect for human diversity requires terminology that identifies technological limitations without devaluing entire cultures.
Our Call to Action
We, researchers, educators, engineers, policymakers, and citizens, call upon scientific journals, conference committees, universities, tech organizations, and funding agencies to:
Discontinue the use of the term "low-resource languages" in all scientific publications, calls for proposals, policy reports, and official communications.
Adopt scientifically precise, context-dependent alternatives that accurately describe the actual source of the limitation, such as:
a) Infrastructure-limited processing
b) Annotation-limited environments
c) Speech-rich environments
d) Architecturally excluded modalities
e) Digitally occluded communicative systems
f) or other alternatives in the context of MI
Publicly funded institutions and scientific leaders have a responsibility to use terminology that is both methodologically sound and socially responsible. It is time to stop shifting the blame onto the languages themselves.
Why This Matters Now
As Machine Intelligence is reshaping our world, who gets heard and how they are represented matters more than ever. If we build the future of technology on terminology that devalues global languages, we institutionalize digital exclusion.
Scientific excellence requires conceptual precision. Respect for linguistic diversity requires terminology that accurately identifies technological and infrastructural limitations without attributing them to the languages themselves.
This petition is inspired by the arguments developed in:
Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6857538
Sign the Petition
Stand with us to demand scientific rigor, linguistic dignity, and an end to deficit-based labels in tech and academia.
Sign and share today!
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Petition created on August 1, 2026