Advancing AI with Integrity: Ethical Challenges and Solutions in Neural Machine Translation

TL;DR

This work surveys the ethical landscape of Neural Machine Translation (NMT), emphasizing fairness, privacy, data ownership, and cultural representation. It combines an empirical Luganda-English NMT study using Transformer architectures with a Longformer/BERT-based labeling approach and a broad literature review to surface actionable ethical guidelines. The authors propose concrete practices across data collection, labeling, model training, and publication, underscoring the need for human oversight and transparent, reproducible processes. They argue that developers bear primary responsibility for ethical outcomes, framing stewardship and societal impact as central to responsible NMT deployment, including considerations from a biblical perspective.

Abstract

This paper addresses the ethical challenges of Artificial Intelligence in Neural Machine Translation (NMT) systems, emphasizing the imperative for developers to ensure fairness and cultural sensitivity. We investigate the ethical competence of AI models in NMT, examining the Ethical considerations at each stage of NMT development, including data handling, privacy, data ownership, and consent. We identify and address ethical issues through empirical studies. These include employing Transformer models for Luganda-English translations and enhancing efficiency with sentence mini-batching. And complementary studies that refine data labeling techniques and fine-tune BERT and Longformer models for analyzing Luganda and English social media content. Our second approach is a literature review from databases such as Google Scholar and platforms like GitHub. Additionally, the paper probes the distribution of responsibility between AI systems and humans, underscoring the essential role of human oversight in upholding NMT ethical standards. Incorporating a biblical perspective, we discuss the societal impact of NMT and the broader ethical responsibilities of developers, positing them as stewards accountable for the societal repercussions of their creations.