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The Loss in AI Translation

Examining the Pitfalls and Ethical Implications of AI Translation

##article.authors##

Arham Doshi Carroll Sid

DOI:

Keywords:

AI Translation, Neural Machine Translation, Transformer Model, LSTM, Jainism, Jain Scriptures, Meaning Loss, Machine Learning, Computational Linguistics, NLP, Natural Language Processing, Deep Learning, Cross - Linguistic Data, Hindu, English, Hugging Face

Abstract

This research paper investigates the potential pitfalls and limitations of Artificial Intelligence (AI) translation for Jain scriptures, as well as how different AI models perform on Hindi to English translation tasks, and how to improve our understanding of Jainism, an ancient Indian religion, possessing a rich body of scriptures in various languages. Preserving and disseminating these texts for the global Jain community is crucial. However, translating these scriptures adequately, especially concepts specific to Jain philosophy, presents a significant challenge. While AI translation offers a promising avenue for overcoming language barriers, its effectiveness for Jain scriptures still needs to be explored. This paper also addresses this gap by evaluating the performance of AI models on Hindi-to-English translation tasks involving Jain scriptures. We analyze the strengths and weaknesses of current AI models, highlighting issues like semantic distortion, loss of context, cultural misinterpretation, and linguistic errors. Simultaneously, we explore how these issues can impact the comprehension and interpretation of the translated texts. Finally, the paper discusses the ethical implications of AI translation errors and the importance of preserving cultural and spiritual heritage. We conclude by exploring potential future advancements in AI technology that can address the limitations of current models and ensure accurate and culturally sensitive translation of Jain scriptures.

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