This study sets out to answer one major question: Can ChatGPT capture swearing nuances? It presents an empirical study on the ability of ChatGPT to translate Arabic oath expressions into English. 30 Arabic oath expressions were collected from the literature. These 30 oaths were first translated via ChatGPT and then analyzed and compared to the human translation in terms of types of gaps left unfulfilled by ChatGPT. Specifically, the gaps involved are: religious gap, cultural gap, both religious and cultural gaps, no gap, using non-oath particles, redundancy and noncapturing of Arabic script diacritics. It concludes that ChatGPT translation of oaths is still much unsatisfactory, unveiling the need of further developments of ChatGPT, and the inclusion of Arabic data on which ChatGPT should be trained including oath expressions, oath nuances, rituals, and practices.

Accessing and comprehending religious texts, particularly the Quran (the sacred scripture of Islam) and Ahadith (the corpus of the sayings or traditions of the Prophet Muhammad), in today's digital era necessitates efficient and accurate Question-Answering (QA) systems. Yet, the scarcity of QA systems tailored specifically to the detailed nature of inquiries about the Quranic Tafsir (explanation, interpretation, context of Quran for clarity) and Ahadith poses significant challenges. To address this gap, we introduce a comprehensive dataset meticulously crafted for QA purposes within the domain of Quranic Tafsir and Ahadith. This dataset comprises a robust collection of over 73,000 question-answer pairs, standing as the largest reported dataset in this specialized domain. Importantly, both questions and answers within the dataset are meticulously enriched with contextual information, serving as invaluable resources for training and evaluating tailored QA systems. However, while this paper highlights the dataset's contributions and establishes a benchmark for evaluating QA performance in the Quran and Ahadith domains, our subsequent human evaluation uncovered critical insights regarding the limitations of existing automatic evaluation techniques. The discrepancy between automatic evaluation metrics, such as ROUGE scores, and human assessments became apparent. The human evaluation indicated significant disparities: the model's verdict consistency with expert scholars ranged between 11% to 20%, while its contextual understanding spanned a broader spectrum of 50% to 90%. These findings underscore the necessity for evaluation techniques that capture the nuances and complexities inherent in understanding religious texts, surpassing the limitations of traditional automatic metrics.

This position paper concerns the use of religious texts in Natural Language Processing (NLP), which is of special interest to the Ethics of NLP. Religious texts are expressions of culturally important values, and machine learned models have a propensity to reproduce cultural values encoded in their training data. Furthermore, translations of religious texts are frequently used by NLP researchers when language data is scarce. This repurposes the translations from their original uses and motivations, which often involve attracting new followers. This paper argues that NLP's use of such texts raises considerations that go beyond model biases, including data provenance, cultural contexts, and their use in proselytism. We argue for more consideration of researcher positionality, and of the perspectives of marginalized linguistic and religious communities.

From ChatGPT to a virtual girlfriend, a range of weird and wonderful chatbots have emerged in recent months amid the proliferation of artifical intelligence (AI). But the latest AI-powered app is arguably the most bizarre yet. The app, called Text With Jesus, is designed for'devoted Christians seeking a deeper connection with the Bible's most iconic figures', according to its developers. As the name suggests, users can'text' with Jesus, as well as a number of other figures including Mary, Joseph, Peter and Matthew. And while the basic app is free, users can opt to pay $2.99/month (£2.35/month) to speak to Satan. Text With Jesus is designed for'devoted Christians seeking a deeper connection with the Bible's most iconic figures', according to its developers Text With Jesus was trained on all publicly available versions of the Bible, including the King James Version, the New International Version and the New American Standard Bible, according to its developers.

Meta has created an AI language model that (in a refreshing change of pace) isn't a ChatGPT clone. The company's Massively Multilingual Speech (MMS) project can recognize over 4,000 spoken languages and produce speech (text-to-speech) in over 1,100. Like most of its other publicly announced AI projects, Meta is open-sourcing MMS today to help preserve language diversity and encourage researchers to build on its foundation. "Today, we are publicly sharing our models and code so that others in the research community can build upon our work," the company wrote. "Through this work, we hope to make a small contribution to preserve the incredible language diversity of the world."

The Qur'an is a fourteen centuries old divine book in Arabic language that is read and followed by almost two billion Muslims globally as their sacred religious text. With the rise of Islam, the Arabic language gained popularity and became the lingua franca for large swaths of the old world. Devout Muslims read the Qur'an daily seeking guidance and comfort. Though the Qur'an, as a text, is short, there is a huge volume of supporting work filling tens of thousands of volumes, e.g., commentaries, exegesis, etc. Recently, there has been a renewed interest in such religious texts by non-specialists.

Travis DeShazo is, to paraphrase Cake's 2001 song "Comfort Eagle," building a religion. He is building it bigger. He is increasing the parameters. The results are fairly convincing, too, at least as far as synthetic scripture (his words) goes. "Not a god of the void or of chaos, but a god of wisdom," reads one message, posted on the @gods_txt Twitter feed for GPT-2 Religion A.I. "This is the knowledge of divinity that I, the Supreme Being, impart to you. When a man learns this, he attains what the rest of mankind has not, and becomes a true god. Another message, this time important enough to be pinned to the top of the timeline, proclaims: "My sayings are a remedy for all your biological ills.

TLDR: No! Your Machine Translation Model is not "prophesying", but let's look at the six major issues with neural machine translation (NMT). So I saw a Twitter thread today with the editor-in-chief of Motherboard tweeting, "Google Translate is popping out bizarre religious texts and no one is sure why". I am going to spend a little time on the "why" part (folks who work in MT know why), but mostly focus on actual problems with neural machine translation. The choice of headlines, the promotion tweet, and the tone of the article reminds me of all the irresponsible writing that went around the famous "Facebook Frankenstein" experiment. I would not be surprised if other media outlets picked up this Motherboard piece and ran ridiculous stories about machine translation conspiracy theories.