Machine translation and fair access to information

Mary Nurminen · Maarit Koponen

29 citations0/0 files storedTranslation Spaces

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Translation Studies and Practices Natural Language Processing Techniques Ethics and Social Impacts of AI

Abstract

Abstract This article contributes to the discussion on fairness and ethics in MT by highlighting efforts that have been made to use MT for the humanitarian purpose of increasing access to information for groups that are underserved. The article provides an overview of example projects in which MT has been implemented for this purpose in three contexts: civic participation, public health and safety, and media and culture. In addition, the article examines some of the ethical issues surrounding efforts to use MT for accessibility, including issues of quality, acceptability, and the need to involve stakeholders in development.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 29 citations exist upstream.

References

1966The Universal Declaration of Human Rights 2019Universal Declaration of Human Rights 2019The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems 2010A Productivity Test of Statistical Machine Translation Post-Editing in a Typical Localisation Context 2013Is ELF more effective and fair than translation? An evaluation of the EU's multilingual regime 1995The Possibility of Language 2017Embracing the threat: machine translation as a solution for subtitling 2019Translation in Cascading Crises

Cited by

2021Towards Sustainable Use of Machine Translation: Usability and Perceived Quality from the End-User Perspective 2022Babel Fish Democracy? Prospects for Addressing Democratic Language Barriers through Machine Translation and Interpretation 2022Machine translation in the multilingual classroom

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.