"It's how you do things that matters": Attending to Process to Better
Serve Indigenous Communities with Language Technologies
- URL: http://arxiv.org/abs/2402.02639v2
- Date: Tue, 6 Feb 2024 02:50:48 GMT
- Title: "It's how you do things that matters": Attending to Process to Better
Serve Indigenous Communities with Language Technologies
- Authors: Ned Cooper, Courtney Heldreth, Ben Hutchinson
- Abstract summary: This position paper explores ethical considerations in building NLP technologies for Indigenous languages.
We report on interviews with 17 researchers working in or with Aboriginal and/or Torres Strait Islander communities.
We recommend practices for NLP researchers to increase attention to the process of engagements with Indigenous communities.
- Score: 2.821682550792172
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Indigenous languages are historically under-served by Natural Language
Processing (NLP) technologies, but this is changing for some languages with the
recent scaling of large multilingual models and an increased focus by the NLP
community on endangered languages. This position paper explores ethical
considerations in building NLP technologies for Indigenous languages, based on
the premise that such projects should primarily serve Indigenous communities.
We report on interviews with 17 researchers working in or with Aboriginal
and/or Torres Strait Islander communities on language technology projects in
Australia. Drawing on insights from the interviews, we recommend practices for
NLP researchers to increase attention to the process of engagements with
Indigenous communities, rather than focusing only on decontextualised
artefacts.
Related papers
- A Capabilities Approach to Studying Bias and Harm in Language Technologies [4.135516576952934]
We consider fairness, bias, and inclusion in Language Technologies through the lens of the Capabilities Approach.
The Capabilities Approach centers on what people are capable of achieving, given their intersectional social, political, and economic contexts.
We detail the Capabilities Approach, its relationship to multilingual and multicultural evaluation, and how the framework affords meaningful collaboration with community members in defining and measuring the harms of Language Technologies.
arXiv Detail & Related papers (2024-11-06T22:46:13Z) - Harnessing the Power of Artificial Intelligence to Vitalize Endangered Indigenous Languages: Technologies and Experiences [31.62071644137294]
We discuss the decreasing diversity of languages in the world and how working with Indigenous languages poses unique ethical challenges for AI and NLP.
We report encouraging results in the development of high-quality machine learning translators for Indigenous languages.
We present prototypes we have built in projects done in 2023 and 2024 with Indigenous communities in Brazil, aimed at facilitating writing.
arXiv Detail & Related papers (2024-07-17T14:46:37Z) - The Call for Socially Aware Language Technologies [94.6762219597438]
We argue that many of these issues share a common core: a lack of awareness of the factors, context, and implications of the social environment in which NLP operates.
We argue that substantial challenges remain for NLP to develop social awareness and that we are just at the beginning of a new era for the field.
arXiv Detail & Related papers (2024-05-03T18:12:39Z) - NLP Progress in Indigenous Latin American Languages [44.8359369488204]
The paper focuses on the marginalization of indigenous language communities in the face of rapid technological advancements.
We highlight the cultural richness of these languages and the risk they face of being overlooked in the realm of Natural Language Processing.
arXiv Detail & Related papers (2024-04-08T10:04:55Z) - What Do Dialect Speakers Want? A Survey of Attitudes Towards Language Technology for German Dialects [60.8361859783634]
We survey speakers of dialects and regional languages related to German.
We find that respondents are especially in favour of potential NLP tools that work with dialectal input.
arXiv Detail & Related papers (2024-02-19T09:15:28Z) - Neural Machine Translation for the Indigenous Languages of the Americas:
An Introduction [102.13536517783837]
Most languages from the Americas are among them, having a limited amount of parallel and monolingual data, if any.
We discuss the recent advances and findings and open questions, product of an increased interest of the NLP community in these languages.
arXiv Detail & Related papers (2023-06-11T23:27:47Z) - Ethical Considerations for Machine Translation of Indigenous Languages:
Giving a Voice to the Speakers [40.84344504873471]
Machine translation has become very successful for high-resource language pairs.
This has sparked new interest in research on the automatic translation of low-resource languages, including Indigenous languages.
arXiv Detail & Related papers (2023-05-31T01:04:20Z) - How can NLP Help Revitalize Endangered Languages? A Case Study and
Roadmap for the Cherokee Language [91.79339725967073]
More than 43% of the languages spoken in the world are endangered.
In this work, we focus on discussing how NLP can help revitalize endangered languages.
We take Cherokee, a severely-endangered Native American language, as a case study.
arXiv Detail & Related papers (2022-04-25T18:25:57Z) - Not always about you: Prioritizing community needs when developing
endangered language technology [5.670857685983896]
We discuss the unique technological, cultural, practical, and ethical challenges that researchers and indigenous speech community members face.
We report the perspectives of language teachers, Master Speakers and elders from indigenous communities, as well as the point of view of academics.
arXiv Detail & Related papers (2022-04-12T05:59:39Z) - Including Signed Languages in Natural Language Processing [48.62744923724317]
Signed languages are the primary means of communication for many deaf and hard of hearing individuals.
This position paper calls on the NLP community to include signed languages as a research area with high social and scientific impact.
arXiv Detail & Related papers (2021-05-11T17:37:55Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.