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.

该论文讨论了神经机器翻译系统中人工智能所面临的伦理挑战，强调开发人员确保公平性和文化敏感性的必要性。通过实证研究和文献综述，我们考察了神经机器翻译开发的各个阶段中涉及的伦理问题，包括数据处理、隐私、数据所有权和同意。此外，我们还研究了正义和公平问题，探讨了人工智能系统与人类之间责任的分配，并强调人类监督在维护神经机器翻译伦理标准方面的重要作用。最后，我们还从圣经角度讨论了神经机器翻译的社会影响以及开发者更广泛的伦理责任，将他们视为对自己创造物的社会后果负责的守护者。

推进以诚信为核心的人工智能：神经机器翻译中的道德挑战和解决方案