The Sharjah International Conference on AI & Linguistics
The 2024 Sharjah International Conference on AI & Linguistics (SICAL 2024) aims to bridge the gap between the study of linguistics and Artificial Intelligence. In doing so, the conference seeks to foster global dialogue on all aspects of language study through examining both the impact and the potential of artificial intelligence. More specifically, the conference serves as a platform for language scholars, researchers, language technologists, materials developers, and educators to discuss advancements, challenges, policies, and future directions in linguistic intelligence, especially as it applies to linguistic diversity as a cornerstone of cultural wealth.
التحديات في مجال الذكاء الاصطناعي (AI) وتأثيراتها على المجتمع المعاصر
تتناول هذه الورقة التقدمات والتحديات الكبيرة في مجال الذكاء الاصطناعي (AI) وتأثيراتها على المجتمع المعاصر. مع استمرار تطور تقنيات الذكاء الاصطناعي، تقدم هذه التقنيات فرصًا كبيرة للابتكار، ولكنها أيضًا تطرح عقبات تتطلب اعتبارات دقيقة. تؤكد هذه الدراسة على أهمية التعاون بين التخصصات المختلفة بين العلماء والممارسين في مجالات التكنولوجيا والأخلاق والدراسات الثقافية للتعامل مع التعقيدات التي يقدمها الذكاء الاصطناعي. نستكشف الإمكانيات التحويلية للذكاء الاصطناعي في قطاعات متعددة، بما في ذلك التعليم والرعاية الصحية والصناعة، مع تسليط الضوء أيضًا على المعضلات الأخلاقية والتأثيرات الاجتماعية التي ترافق هذه التقدمات. من خلال تعزيز الحوار بين مجالات أكاديمية متنوعة وتعزيز فهم شامل للذكاء الاصطناعي، نهدف إلى المساهمة في تطوير ممارسات مسؤولة ومستدامة في هذا المجال. تؤكد نتائجنا على ضرورة البحث المستمر والتعاون لاستغلال فوائد الذكاء الاصطناعي مع تقليل مخاطره، ساعين في النهاية إلى مستقبل تكون فيه التكنولوجيا في خدمة الإنسانية بشكل فعال وعادل. كما نؤكد على أهمية تكامل المعرفة بين مختلف التخصصات، حيث أن الذكاء الاصطناعي يتطلب تفاعلًا بين العلوم الإنسانية والتكنولوجيا. إن التحديات التي تواجهنا في هذا المجال تتطلب استجابة جماعية من المجتمع الأكاديمي والصناعي، مما يعزز من أهمية الفعاليات العلمية والثقافية التي تجمع بين الباحثين والممارسين. في ختام هذه الورقة، ندعو إلى مزيد من التعاون بين الجامعات والمؤسسات البحثية لتطوير استراتيجيات فعالة تعزز من استخدام الذكاء الاصطناعي بشكل مسؤول، مما يسهم في تحقيق التنمية المستدامة والرفاهية العامة.
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التقدم المعاصر في مجال الذكاء الاصطناعي وتأثيراته المتعددة على مختلف المجالات
في ظل التقدم المعاصر في مجال الذكاء الاصطناعي وتأثيراته المتعددة على مختلف المجالات، يتناول هذا البحث التقاطع الحاسم بين نشر المعرفة والابتكار التكنولوجي. نجتمع اليوم، أيها الحضور الكريم، من علماء ومفكرين، لاستكشاف التحديات والفرص العميقة التي يقدمها الذكاء الاصطناعي، خاصة في مجالات التعليم والتبادل الثقافي. إن أهمية هذا النقاش تتعزز من خلال ضرورة التعاون بين المؤسسات الأكاديمية والباحثين والتقنيين لتطوير إطار قوي لمشاركة المعرفة والابتكار. يهدف هذا الحدث إلى تسليط الضوء على الإمكانات التحويلية للذكاء الاصطناعي في تعزيز منهجيات التعليم وفهم الثقافات. نؤكد على أهمية التعاون بين التخصصات، داعين إلى دمج وجهات نظر أكاديمية متنوعة لمواجهة التحديات المتعددة التي تطرحها التقدمات التكنولوجية السريعة. علاوة على ذلك، نبرز ضرورة الاعتبارات الأخلاقية والحساسية الثقافية في نشر تقنيات الذكاء الاصطناعي. من خلال هذا الملتقى، نطمح إلى تعزيز حوار غني لا يسهم فقط في تقدم البحث الأكاديمي، بل يساهم أيضًا في النقاش المجتمعي الأوسع حول دور الذكاء الاصطناعي في تشكيل مستقبلنا المشترك. ندعو المشاركين للمشاركة بنشاط في المناقشات التي ستؤدي إلى حلول مبتكرة ومبادرات تعاونية، مما يعزز مجتمعًا عالميًا أكثر وعيًا وترابطًا. إننا نعيش في عصر يتطلب منا التفكير النقدي والتعاون الفعال لمواجهة التحديات المعقدة التي يطرحها الذكاء الاصطناعي. لذا، فإننا نؤكد على أهمية تعزيز العلاقات بين الثقافات المختلفة، وتبادل المعرفة، وتطوير استراتيجيات تعليمية مبتكرة تسهم في بناء مستقبل أفضل للجميع.
تعزيز البحث اللغوي من خلال الدعم والتعاون وتبادل الخبرة بين العقل البشري والذكاء الاصطناعي
تتناول هذه الورقة أهمية الذكاء الاصطناعي في تعزيز البحث اللغوي، حيث تركز على التطورات السريعة في هذا المجال وتأثيرها العميق على مختلف جوانب الحياة. تناقش كيف يمكن للذكاء الاصطناعي أن يسهم في تطوير أدوات وأساليب جديدة، مما يتيح للباحثين إمكانية الوصول إلى مصادر بيانات جديدة ومعقدة. كما تتطرق إلى التحديات التي قد تواجه الباحثين، مثل جودة البيانات والاعتماد المفرط على التكنولوجيا، مما قد يؤثر على القدرات الإبداعية والتفكيرية للأجيال القادمة. في النهاية، تشدد الورقة على ضرورة استخدام الذكاء الاصطناعي بطريقة أخلاقية ومسؤولة لضمان عدم المساس بالقيم والمبادئ الثقافية.
The Impact of Arabs on the Evolution of Sicilian Language and Culture
The Arab presence in Sicily, though shorter than in Spain, left an indelible mark on the island's language, culture, architecture, and scientific advancement. From the Arab conquest in 827 AD to their rule until 1091 AD, Sicily became a center for the transmission of knowledge between the Islamic world and Europe. This paper examines the enduring legacy of Arab influence on Sicilian language, architecture, agriculture, and science. Linguistically, over 300 words from the Siculo-Arabic dialect persist in modern Sicilian, demonstrating the profound integration of Arab culture into the island’s identity. Architecturally, the emergence of the Norman-Arab style, blending Arab, Byzantine, and Romanesque influences, produced a unique Sicilian aesthetic, with notable examples such as the Palatine Chapel and the Zisa Palace. The paper also highlights agricultural innovations, including the introduction of new crops like citrus fruits and innovative irrigation techniques. Furthermore, the role of Arab scholars in preserving and transmitting classical knowledge to Europe is explored, emphasizing the circular nature of cultural and intellectual exchanges. By delving into these shared histories, the research argues for the importance of cross-cultural understanding in combating modern-day populism, xenophobia, and racism. This historical examination serves as a reminder of the deep interconnection between Arab and European civilizations, fostering dialogue and mutual respect. The paper concludes by reflecting on the contemporary relevance of these influences, as exemplified by the opening of the first Arabic Cultural Institute in Italy and stresses the importance of nurturing human creativity and adaptability in an age of artificial intelligence.
تأثير خوارزميات الذكاء الاصطناعي العربية على تحسين فهم النحو والنطق العربي من خلال منصة المعجم GPT
تعتبر دراسة تأثير خوارزميات الذكاء الاصطناعي العربية على تحسين فهم النحو والنطق العربي من خلال نموذج موضوعًا مهمًا يستحق البحث والتحليل. إذ يهدف هذا المشروع إلى فهم كيفية استخدام الذكاء الاصطناعي في تطوير فهم اللغة العربية من الناحيتين التحليلية والشفوية، ويعتبر ذلك جزءًا من البحث العلمي الحديث الذي يركز على استخدام التكنولوجيا في تعلم وتعليم اللغة. وبالتالي، فإن هذا الموضوع يعتبر محوريًا في فهم كيفية تقدم اللغة العربية وتحسين استخدامها لدى الناطقين بها. في ضوء النمو السريع لتكنولوجيا الذكاء الاصطناعي وتطبيقاتها في مجال اللغة العربية، يظهر الاهتمام المتزايد بفهم كيف يمكن لهذه الخوارزميات والنماذج أن تساهم في تحسين فهم النحو والنطق العربي. ومن هنا تنشأ الخلفية والمشكلة الأساسية لهذا البحث، حيث يسعى الباحثون إلى فهم التحديات والفرص المتاحة لتطبيقات الذكاء الاصطناعي في هذا المجال، وكيف يمكن تحديد النقاط القوية والضعف في هذه الأساليب بغية تحسين فهم النحو والنطق العربي. (أسامة2023)
برنامج لغة القرآن الكريم تعريف به ودور الذكاء الاصطناعي في تصميمه
تقدم هذه الورقة "برنامج لغة القرآن الكريم" الذي صممه الدكتور إبراهيم محمد علي عبد اللطيف، والذي يهدف إلى تعزيز مهارات اللغة العربية من خلال دمج القرآن الكريم والأنشطة اللغوية التفاعلية. يستهدف البرنامج الطلاب العرب في المدارس الدولية التي تتبع مناهج غير عربية، ويعالج التحديات اللغوية التي تواجه هذه الفئة. تسلط الدراسة الضوء على أهمية اللغة العربية كوسيلة للتعليم والتواصل، مع التأكيد على الحاجة إلى استراتيجيات فعالة لاكتساب اللغة. بالإضافة إلى ذلك، تستكشف الورقة دور الذكاء الاصطناعي في تصميم البرنامج، موضحة كيف يسهم في توفير نصوص دقيقة لغويًا ومعلوماتيًا، ودعم إنشاء المسابقات اللغوية، وتوليد جمل ونصوص عربية. من خلال استخدام أنشطة تدريبية مبتكرة، يسعى البرنامج إلى تعزيز تقدير أعمق للغة العربية لدى الطلاب، مما يسهم في تحسين كفاءتهم اللغوية وفهمهم الثقافي.
Cultural and Dialectal Implications for NLP: A Case Study on Arabic
This paper delves into the cultural and dialectal implications for Natural Language Processing (NLP) through a comprehensive case study focused on the Arabic language, which is characterized by a rich tapestry of spoken dialects. These dialects, including Gulf, Maghrebi, Levantine, Egyptian, and Iraqi, each possess unique linguistic features, cultural contexts, and social nuances that reflect the diverse identities of Arabic-speaking communities. The study emphasizes the significance of Modern Standard Arabic (MSA) as a unifying linguistic framework that facilitates communication across these varied populations, while also acknowledging the limitations of MSA in capturing the full spectrum of dialectal richness. By providing illustrative examples of how a single sentence can vary across different dialects, the paper highlights the complexities and nuances inherent in Arabic linguistics, showcasing the challenges that arise when attempting to develop NLP applications that are both effective and culturally relevant. The research addresses critical issues such as data scarcity, the need for dialectal representation, and the importance of understanding cultural context in language processing tasks. Furthermore, the paper discusses the ongoing challenges faced in the development of NLP applications tailored to native dialectal Arabic speakers, including the necessity for user-centered design principles, meticulous data collection, curation, and governance. It explores the potential of large language models (LLMs) specifically designed for Arabic dialects, aiming to enhance applications such as question answering, information retrieval, and writing assistance. The findings underscore the importance of collaboration between linguists, cultural experts, and AI practitioners to create more inclusive and effective NLP solutions. By fostering a deeper understanding of the interplay between language, culture, and technology, this research seeks to contribute to the advancement of AI technologies in the Arabic-speaking world, ultimately promoting better communication, accessibility, and understanding across diverse dialectal landscapes. The paper concludes with recommendations for future research directions and the potential for innovative applications that respect and celebrate the linguistic diversity of Arabic.
Effects of Communicative Interaction on Second Language Pronunciation Development
This session will provide an overview of research findings that focus on the impact of communicative interaction on second language development, in particular pronunciation. The session will briefly explore the main tenets of the interactionist approach, namely, input, output, corrective feedback, negotiation for meaning, as well as cognitive aspects such as attention and noticing. After that, the session will discuss findings from recent research on the relationship between interaction and second language pronunciation development. The session will end with a note on the potential ways that AI could be adopted to implement the main tenets of the interactionist approach for promoting second language learning.
Can AI-generated materials help in Arabic teaching? A study of potential and pitfall
The integration of Artificial Intelligence (AI) into language education has introduced innovative methods for developing personalized and adaptive learning materials. This study investigates the effectiveness of AI tools in generating Arabic reading comprehension materials, focusing on five prominent AI systems: ChatGPT, Gemini, Co-Pilot, JAIS, and Diffit. These tools were evaluated based on their ability to create linguistically accurate and pedagogically appropriate content for intermediate-level Arabic learners. The analysis revealed significant linguistic challenges across all tools, including overuse of nominal sentences, frequent verb misuse, pronoun errors, and unsystematic vocabulary repetition. Additionally, the study identified a notable influence of English on AI-generated Arabic texts, resulting in unnatural expressions and syntactic inconsistencies. Despite these issues, the tools demonstrated potential in generating diverse question types and engaging content. This paper underscores the necessity for rigorous quality control and human oversight in deploying AI for Arabic language education to preserve linguistic integrity and enhance learning outcomes. The findings provide valuable insights for educators, curriculum developers, and AI designers to improve the efficacy of AI tools in language teaching.
This contribution interpretatively assesses the quality of English translation from Arabic into English by the two currently leading free-to-use artificial intelligence (AI) tools, ChatGPT and Google Gemini, against translations listed in Al-Mawrid (the globally leading Arabic-English dictionary) and a comprehensive compilation of Arabic phrases by Abu Ssaydeh (2013). Data comprised the d-30 (d=difficult) Arabic phrases (a mixture of collocations and cultural references) that have persistently posed problems for lexicographers of Arabic-English bilingual dictionaries, who mostly simply exclude them. Deploying Pedersen’s 2011 taxonomy of translation strategies, the analysis indicates some interesting results. Al-Mawrid lists only 5 (c. 17%) of the d-30 phrases, but Abu Ssaydeh does better by including 20 (c. 67%). In complete contrast to the two human translators, both AI tools render all the d-30 (100%). While both AI tools displayed some seriously interesting human-like renderings (adding contextual clues), they nonetheless generated some howlers, usually associated with machine translation. Despite their recent launch (November 2022 for ChatGPT and December 2023 for Google Gemini), their English translations of the d-30 Arabic phrase examined here point to excellence seriously being established. The tedious, time-consuming and often thankless task of dictionary-making may well benefit from a clever combination of both humans and AI tools (H-AI, perhaps)
Verbal-linguistic Intelligence Strategies Used by Gifted Students
Student intelligence has many types, research has found nine intelligences called multiple intelligences. Linguistic Intelligence is one of these multiple types of intelligence. The selection of Linguistic intelligence is because this type of intelligence plays a role in developing. the language skills of low-grade students. Linguistic intelligence is the ability to use words effectively. This intelligence includes the ability to manipulate the structure of language, phonology or language sounds, semantic, or meaning of language, and the practical use of language. So the current paper discussed the Verbal-linguistic Intelligence Strategies Used by Gifted Students, Verbal-Linguistic Intelligence are important for students to have at an early ages, the paper used analytical approach regarding to reviewing literature studies, the literature reviews refers to the gifted students used a number of Strategies such as reading books and journals, discussions, podcasting, Storytelling, Crossword puzzles, so the teacher should develop these Strategies for the normal and disabilities students helping them to raise their academic achievement. The paper recommends that teachers learn students to use verbal-linguistic intelligence strategies like reading books and journals, live discussions with themselves, podcasting, Storytelling, Crossword puzzles.
The Impact of Computer Mediated Communication on Language Behavior Between Monolinguals and Bilinguals
The study aims to review Computer Mediated Communication (CMC) and explore its impact on evolution of language, specifically English. CMC can be divided into Synchronous and asynchronous communication, this study will focus on the latter division, investigating user behavior including use of punctuation, abbreviation and spelling. The idea is to collect data from a number of native English speakers and bilinguals by composing a set of questions to look for patterns and differences. Much scholarship has been done on CMC and both of its categories, but an area that explores the difference between monolinguals and bilinguals is yet to be explored, especially when the global language, English, is evolving due to its common use in different regions and cultures. American English, for example, has evolved differently than British English, and they both differ from Indian English. This study aims to explore the different paths a language can evolve by examining language behavior influenced by CMC between native English speakers and foreign English speakers by drawing out the different patterns of language use (punctuation, abbreviation, and spelling).
AI vs. Human: A Preliminary Investigation into Arabic-English Code-Switching
This talk delves into the comparative abilities of large language models (LLMs), particularly ChatGPT, and human native speakers when making judgments about code-switching—the phenomenon of alternating between languages within a conversation. The study focuses on distinguishing between acceptable and unacceptable patterns of code-switching in Emirati Arabic and English, as predicted by the Matrix Language Frame (MLF) model, which provides a framework for understanding how languages interact within bilingual discourse. Through our research, we aim to explore the degree to which LLMs, like ChatGPT, can accurately assess and replicate the complexities involved in human code-switching, which often hinges on linguistic, social, and cultural factors. Preliminary findings reveal interesting contrasts between the strengths and limitations of LLMs and those of human native speakers in their ability to process and evaluate multilingual language use. This comparison provides deeper insights into the nuances of multilingual language processing and underscores both the potential and the current limitations of AI in replicating human-like judgments of code-switching. These insights hold significance for the development of more refined language models and contribute to the broader understanding of the intersection between artificial intelligence and natural language processing in multilingual contexts.
18 Months of Researching GenAI on Campus: What We Have Learned
This session highlights the findings from 18 months of investigating the use of GenAI in higher education contexts. Our research looked closely into teachers' practice, students' engagement with GenAI, and classroom observations. Findings highlighted several needs to allow for a smooth and effective integration of GenAI tools into the classroom. To respond to these needs, we developed the LAIK framework, a practical framework that guides teachers in integrating GenAI into higher education classrooms. This session will discuss the framework and its different stages in ways that are practical and relevant to educators in higher education.
GAI Developments in Auto-Peer: Enhancing the Automated Peer-Review Experience
This presentation examines the role of Generative Artificial Intelligence (GAI) in enhancing Auto-Peer, an Automated Writing Evaluation (AWE) tool designed to simulate peer-review experiences in student writing. Auto-Peer currently offers context-sensitive feedback on 25 aspects of writing, such as sentence structure, paragraph coherence, and argument development. Its design shifts away from merely identifying errors, instead focusing on what is ‘unusual’ or unexpected in the text, prompting students to either modify their writing based on the feedback or justify why their current approach is appropriate. While the Auto-Peer tool has been highly successful in improving student writing, recent GAI developments have enabled the tool to provide even more dynamic and formative feedback. These advancements allow Auto-Peer to move beyond traditional corrective feedback, offering more sophisticated insights into idea generation, organization, and critical reasoning, thus providing a comprehensive support system for student writers. The focus of this talk will be on how Auto-Peer’s GAI-powered features enhance the student writing experience throughout the entire writing process. The presentation will explore how the tool promotes learner autonomy by offering real-time, formative feedback that encourages students to self-edit and iteratively improve their work. Additionally, the talk highlights how Auto-Peer reduces instructor workload by automating peer review without compromising feedback quality. Finally, the talk discusses the future potential of Auto-Peer and how it can evolve as GAI technologies advance, reshaping peer review and writing instruction for diverse learners and educational contexts.
Future of Artificial Intelligence – A Visionary Business Approach
This paper presents a comprehensive analysis of the transformative potential of Artificial Intelligence (AI) and Large Language Models (LLMs) in reshaping various sectors of society, economy, and individual performance. The discussion begins with an overview of the current landscape of AI, highlighting the significant hype surrounding its capabilities and the dichotomy of perspectives that have emerged: the "Bloomers," who advocate for AI as a catalyst for unprecedented advancements in human capability, and the "Doomers," who express concerns about job displacement and existential threats posed by autonomous technologies. The paper delves into the challenges associated with AI adoption, including ethical dilemmas, privacy concerns, and the risk of an AI bubble that may inflate expectations beyond reality. It critically examines the implications of these challenges on the workforce and societal structures, emphasizing the need for proactive measures to mitigate potential negative outcomes. Furthermore, the analysis highlights the real value that AI can deliver across various industries, such as healthcare, finance, and education, by improving efficiency, enhancing decision-making, and fostering innovation. The paper outlines 14 distinct case studies that illustrate how AI can be better utilized to reshape operations and drive growth in these sectors, while also acknowledging the ongoing challenges related to technology dissemination and privacy. In conclusion, this work aims to provide a nuanced understanding of AI's capabilities and limitations, offering strategic insights for stakeholders to harness AI's potential responsibly and effectively. By examining the past, present, and future trajectories of AI, the paper seeks to contribute to the discourse on how to leverage AI for a more prosperous, equitable, and sustainable future.
الذكاء الُّلغوي وبناء المعجم العقلي في الطفولة المبِّكرة (مقاربة تطبيقية)
تعرض هذه الورقة لكيفية استثمار خصائص الذكاء اللغوي في بناء المعجم العقلي للطفل، حيث تمثّل مرحلة الطفولة مرحلة الخصوبة في الاكتساب، والتعلم اللغوي؛ فاللغة تُزوّد الأطفال بالأدوات اللازمة للتمثيل العقلي، والذي أطلق عليه فيجوتسكي "التوسط اللفظي" Verbal" mediation، ذلك أن تعلم اللغة هو في جوهره - تعلُّم كيفية بناء المعنى؛ ولهذا فهي عملية محفزة، ويأتي الذكاء اللغوي متضمنا خصائص ومكونات ، لو استثمرت من خلال نماذج تعليمية؛ لأسهم ذلك في بناء المعجم العقلي للطفل، الذي يؤدي بدوره - إلى اكتساب الطفل للمهارات اللغوية، وتطورها.
Impact of ChatGPT on Vocabulary Development: AComparison Study
This pilot study examines the efficacy of ChatGPT when compared to traditional online language learning platforms such as Google Translate on vocabulary learning among undergraduate students learning elementary Korean at the American University of Sharjah (AUS). While numerous studies have investigated ChatGPT’s effectiveness in improving students’ vocabulary development, few studies have focused on the impact of ChatGPT in enhancing learners' linguistic abilities in a language other than English. In this regard, the current study employs empirical methods to analyze the efficacy of ChatGPT on vocabulary development when compared to Google Translate. The target words included in the pre-test and post-test were some basic but frequently used concrete Korean nouns. The intervention involved participants reading two short Korean passages with embedded target words while using either ChatGPT or Google Translate to interpret any unknown words. Results showed that the ChatGPT group had a greater mean test score than the Google Translate group. The relative difference in the performance could be attributed to greater levels of involvement while using a chatbot as compared to a translation tool. By also taking into consideration the students’ perspectives on the effectiveness of online tools for language learning, the study recommends how instructors can use AI for language teaching.
لغة الوثائق وأهميتها في كتابة البحوث التاريخية الأرشيف والمكتبة الوطنية نموذجاً
تعرض هذه الورقة أهمية الأرشيف والوثائق في توثيق التاريخ والحفاظ على التراث الثقافي والمعرفي للأمم. تستعرض المراحل المختلفة لتطور الأرشفة، بدءًا من الأرشيف التقليدي إلى الأرشفة الإلكترونية في العصر الحديث. كما تبرز الوثيقة دور الأرشيف في دعم البحث العلمي وتوفير المعلومات اللازمة للباحثين والمهتمين. بالإضافة إلى ذلك، يتم تناول بعض النماذج من المخطوطات والأرشيفات المختلفة، مثل الأرشيف العثماني والأرشيف الألماني، مما يعكس تنوع الوثائق وأهميتها في فهم التاريخ. تسلط هذه الورقة الضوء أيضًا على المبادرات الحديثة مثل مشروع منصة أرشيف الخليج العربي الرقمي، الذي يهدف إلى تعزيز الوصول إلى المعلومات وحفظ التراث.
Ajami History, Culture, and Assimilation
This study investigates Ajami, which is the language of the Ajami ethnicity in the UAE. Currently, usage of Ajami is declining, and the multiplicity of Emirati citizens’ cultural identities has converged over time to form one monolithic national identity; consequently, academic research on local cultures that are not broadly officially recognized, like Ajami, is scarce. Given that language is one of the most important representations of culture, examining Ajami language and its use can provide valuable insights into the status of Ajami culture in the UAE. The body of existing academic work dedicated to studying the Ajami language and history, in addition to being scarce, is conflicting, reflecting the socially controversial nature of the Ajami identity and history. To address these gaps in knowledge, in-depth interviews were conducted with members of the Ajami community regarding their ethnicity, the social environment surrounding the Ajami language, and their language use. Findings of these interviews are cross-examined by previous research on Ajami and other minority languages, which further suggest the need for the revival of the Ajami language and culture through larger community efforts. It is expected that an introduction of new technologies such as AI language learning tools will play a crucial role in keeping records of the Ajami language, so that it may be inherited to future generations.
Leveraging Artificial Intelligence for Enhanced Linguistic Analysis: A Deep Learning Approach to Language Understanding
The integration of Artificial Intelligence (AI) into the field of linguistics has catalysed unprecedented advancements, particularly through the application of deep learning algorithms in Natural Language Processing (NLP). This paper investigates contemporary AI-driven methodologies for linguistic analysis, emphasizing the transformative impact of deep learning models on tasks such as language modeling, semantic analysis, and syntactic parsing. By leveraging state-of-the-art transformer architectures, we assess their efficacy in capturing the multifaceted nature of human language, including phenomena such as polysemy, syntactic variability, and discourse structures. Our research employs a comparative analysis of various AI models, evaluating their performance across diverse linguistic datasets to elucidate their strengths and limitations in language understanding tasks. Furthermore, we explore the implications of these advancements for computational linguistics, highlighting how AI can enhance both theoretical frameworks and practical applications, including machine translation, sentiment analysis, and the development of conversational agents. Despite the transformative potential of AI in linguistics, our findings underscore critical challenges, particularly concerning model interpretability and the nuanced replication of human context. This study contributes to the ongoing discourse on the development of more effective AI methodologies, advocating for the integration of AI tools in the pursuit of understanding and preserving linguistic diversity. By addressing these challenges, we aim to foster a more profound engagement with the complexities of human language through AI-enhanced linguistic research.
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