Current State-of-the-Art of Bias Detection and Mitigation in Machine Translation for African and European Languages: a Review

2024/10/28 by Catherine Ikae, Ikae, Catherine, Mascha Kurpicz-Briki +1 · 1 citation
Computer Science · Engineering · #Artificial intelligence #Biology #Computation and Language (cs.CL) #Computer science #Current (fluid) #Data science #Electrical engineering #Engineering #FOS: Computer and information sciences #Linguistics #Machine translation #Natural Language Processing Techniques #Natural language processing #Philosophy #Political science #Programming language #State (computer science) #State of art #Translation (biology)

paper · pdf · doi:10.48550/arxiv.2410.21126

openalex publication_date 2024/10/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Studying bias detection and mitigation methods in natural language processing and the particular case of machine translation is highly relevant, as societal stereotypes might be reflected or reinforced by these systems. In this paper, we analyze the state-of-the-art with a particular focus on European and African languages. We show how the majority of the work in this field concentrates on few languages, and that there is potential for future research to cover also the less investigated languages to contribute to more diversity in the research field.

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• Charting the Landscape of African NLP: Mapping Progress and Shaping the Road Ahead

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