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Journal articles on the topic 'AI-Generated work'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Wang, Faye F. "Copyright Protection for AI-Generated Works." Amicus Curiae 5, no. 1 (2023): 88–103. http://dx.doi.org/10.14296/ac.v5i1.5663.

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Since the 2010s, artificial intelligence (AI) has quickly grown from another subset of machine learning (ie deep learning) in particular with recent advances in generative AI, such as ChatGPT. The use of generative AI has gone beyond leisure purposes. It has now been widely used to generate music, news articles and image-based art works. This prompts a regulatory interpretation as to how AI-generated works should be appropriately used to eliminate their potential harm to society, but at the same time how it should be protected to foster human creativity and promote a well-functioning market. T

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Nielsen, Aileen, Stavroula Skylaki, Milda Norkute, and Alexander Stremitzer. "Building a better lawyer: Experimental evidence that artificial intelligence can increase legal work efficiency." Journal of Empirical Legal Studies 21, no. 4 (2024): 979–1022. http://dx.doi.org/10.1111/jels.12396.

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AbstractRapidly improving artificial intelligence (AI) technologies have created opportunities for human–machine cooperation in legal practice. We provide evidence from an experiment with law students (N = 206) on the causal impact of machine assistance on the efficiency of legal task completion in a private law setting with natural language inputs and multidimensional AI outputs. We tested two forms of machine assistance: AI‐generated summaries of legal complaints and AI‐generated text highlighting within those complaints. AI‐generated highlighting reduced task completion time by 30% without

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闫, 瑜. "Copyrightability and Protection Path of the AI-Generated Work." Dispute Settlement 07, no. 03 (2021): 89–97. http://dx.doi.org/10.12677/ds.2021.73012.

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Mr., Kuncha Anudeep Durga Prasad. "The Intersection of Copyright and AI: Issues, Opportunities and Legal Solutions." Annual International Journal on Analysis of Contemporary Legal Affairs (AIJACLA) 5 (May 25, 2025): 157–68. https://doi.org/10.5281/zenodo.15514221.

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<em>This paper discusses about establishment of Copyright Law through the Berne Convention, 1886 worldwide to protect the creator’s work as well as the moral rights of such work. It examines whether AI (Artificial Intelligence) is considered as a legal person as current legal framework and implications this has for AI-generated works, in terms of authorship, originality, and liability in the context of AI-generated context. </em><em>This paper addresses key challenges AI poses to traditional Copyright Principles such as the concept of moral rights and the question of whether AI can be an

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Shen, Jialing. "The Nature and Copyright Ownership of Artificial Intelligence Creations." Journal of Economics and Law 1, no. 2 (2024): 168–74. http://dx.doi.org/10.62517/jel.202414224.

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With the vigorous development of artificial intelligence technology in our country, AI-generated works have brought tremendous convenience to our daily work. However, while developing and using AI-generated works, disputes have arisen in the academic and judicial fields regarding whether AI-generated works have copyright and how to legally protect them. Currently, the legal issues related to AI-generated works in our country mainly include the recognition of the work attributes of AI-generated works and the attribution of copyright ownership. In response, the author first analyzes the current

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Jeremie Busio Legaspi, Roan Joyce Ohoy Licuben, Emmanuel Alegado Legaspi, and Joven Aguinaldo Tolentino. "Comparing ai detectors: evaluating performance and efficiency." International Journal of Science and Research Archive 12, no. 2 (2024): 833–38. http://dx.doi.org/10.30574/ijsra.2024.12.2.1276.

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The widespread utilization of AI tools such as ChatGPT has become increasingly prevalent among learners, posing a threat to academic integrity. This study seeks to evaluate capability and efficiency of AI detection tools in distinguishing between human-authored and AI-generated works. Three-paragraph works on “AutoCAD and Architecture” were generated through ChatGPT, and three human-written works were subjected to evaluation. AI detection tools such as GPTZero, Copyleaks and Writer AI were used to evaluate these paragraphs. Parameters such as “Human/Human Text/Human Generated Text” and “AI/AI

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Hwang, Yohan, Dongkwang Shin, and Jang Ho Lee. "Who owns AI-generated artwork? Revisiting the work of generative AI based on human-AI co-creation." Telematics and Informatics 98 (April 2025): 102266. https://doi.org/10.1016/j.tele.2025.102266.

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Snihur, Volodymyr, and Ivan Bratus. "AUTHORSHIP OF AI-GENERATED WORKS IN ARTISTIC DOMAIN." Grail of Science, no. 33 (November 20, 2023): 426–32. http://dx.doi.org/10.36074/grail-of-science.10.11.2023.69.

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The article analyzes the question of authorship of AI-generated works in the artistic domain. As usage of AI is projected to increase in many different industries, sometimes regardless of presence of any tangible benefits to the user, we have to evaluate potential impact of an AI on the artistic domain, mostly from the perspective of it being used as a tool by various artists. Discussion is held from the perspective of the evaluation of actual work done and the quality of the result, accounting for the time spent to achieve that result, along with human-made edits where necessary. Discussions

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B, Balamurali. "DECIPHERING THE LEGAL PUZZLE: COPYRIGHT PROTECTION FOR AI GENERATED WORK." LawFoyer International Journal of Doctrinal Legal Research 2, no. 3 (2024): 559–73. https://doi.org/10.70183/lijdlr.2024.v02.33.

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Massadeh, Firas, Fayez Alnusair, Ali Abdel Mahdi Massadeh, and Mahmoud Ismail. "The legal protection of artificial intelligence-generated work: The argument for sui generis over copyright." Corporate Law and Governance Review 6, no. 1 (2024): 49–56. http://dx.doi.org/10.22495/clgrv6i1p5.

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Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. As with other elements of society, the modern economy has become more reliant on AI, indicating the potentially great influence it has on innovation. Many previous studies on the status of AI-generated work have focused on its connection to intellectual property (IP) law, mainly under copyright and regulations, and whether this type of work could be protected within the legal framework of copyright. Therefore, an all-inclusive assessment of the fitness of the existing copyri

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Wojnowski, Konrad. "The Work of Art in the Age of Automated Creativity: On the autonomy of AI art." Praktyka Teoretyczna, no. 3(53) (December 23, 2024): 179–212. https://doi.org/10.19195/prt.2024.3.7.

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This paper explores the evolving notion of aesthetic autonomy in the context of AI-generated art, proposing three central arguments. First, it revisits Nicholas Brown’s theory of artistic autonomy, suggesting that AI art can achieve a form of autonomy through the interaction of structured prompts and neural network processes, without necessitating direct human intention. Second, it introduces a framework viewing AI-generated artworks as “epistemic consumption objects,” whose unpredictability introduces new aesthetic dimensions that operate independently of conventional commodity relations. Thi

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Gao, Yaxuan. "Embrace AI to Complete Film Odyssey: A Comparative Analysis of Conventional and AI-generated Production Design-Crisis and Prospect." Lecture Notes in Education Psychology and Public Media 101, no. 1 (2025): 6–12. https://doi.org/10.54254/2753-7048/2024.24359.

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Artificial Intelligence (AI) technology has been applied to humongous industries and tested out its beneficial potential in finance, engineering, transportation, and so on. Therefore, filmmakers have started to learn and practice the feasibility and efficiency of ai-generated work. This paper explores the crisis and prospects that production designers and art directors could face when using AI technology to produce films. To better understand the pros and cons of AI-generated work in filmmaking, this paper draws a comparative analysis of the conventional and ai-generated production design in t

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Dr., Sudhir Vaijanathrao Panchagalle, and Ravindra Dadarao Gaikwad Dr. "Intellectual Property Law's In India." International Journal of Advance and Applied Research S6, no. 12B (2025): 64–68. https://doi.org/10.5281/zenodo.14909748.

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<em>Artificial Intelligence (AI) is a technology which is known for carrying out various tasks efficiently with little or no human intervention at  all.  Generative  AI  is  one  of  the  branches  of  AI  which  is  known  for  generating  content  at  par  with  human  intelligence.  Generative  AI  tools  like  ChatGPT,  Google’s  Bard  and  DeepAI  are  being  used  in  today’s  world  by  s

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Li, Xiaoyao. "Legal Attributes of AI-Generated Images in Copyright Law." Highlights in Business, Economics and Management 39 (August 8, 2024): 271–76. http://dx.doi.org/10.54097/pf2ar509.

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The use of artificial intelligence (AI) to generate images has become a trending method of content creation, yet many controversies still surround the legal attributes of AI-generated images. An analysis of the definition of works in copyright law reveals that assessing “originality” is key to determining whether AI-generated images can be recognized as works. The academic community holds both affirmative and negative views on the legal attributes of AI-generated images. Based on this, an analysis of the current two theories from the perspective of originality suggests that the legal attribute

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Saravanan, Muniraj. "Enhancing AI-Generated Image Accessibility Challenges and Solutions." International Journal for Research Trends and Innovation 9, no. 8 (2024): 145–50. https://doi.org/10.5281/zenodo.13293092.

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This research examined accessibility issues with AI-created images and assessed current solutions for improving inclusivity. Key problems identified include insufficient alt text, with 45% of AI images lacking proper descriptions, challenges in differentiating AI images from real ones (38.7% misclassification by people), and ethical worries about representation and bias in image descriptions. The study analyzed solutions like AI-based description generators, which can boost accuracy by up to 60%, and better image detection methods. Results show that while progress has been made in making AI im

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Chen, Jiahui. "Can the AI-Generated Content be Protected as Work Under Copyright Law? ---Jurisprudential Developments in China." Advances in Economics, Management and Political Sciences 7, no. 1 (2023): 187–200. http://dx.doi.org/10.54254/2754-1169/7/20230233.

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Recent Chinese cases of the copyright disputes on AI-generated content (AGC) reveal challenges to copyright jurisprudence by Natural Language Processing (NPL)-based AI systems. Some scholars argued from the perspectives of intellectual characteristics of the AGC. This paper, however, combines historical and doctrinal methods to show that the production process of AGC should be the defining factor of work. This paper argues that modern copyright law does not protect the AI-generated content from the aspect of copyright law in intellectual writings/ paintings/ music/ art as work. Work in the his

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Young, Victoria. "An Unauthorized Renaissance? An Analysis of Artists’ Claims for Copyright Infringement Against AI Generated Art and Possible Defenses." FIU Law Review 18, no. 2 (2024): 521–43. http://dx.doi.org/10.25148/lawrev.18.2.14.

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AI currently presents a novel issue in terms of copyright infringement, specifically AI generated art. Recently, a group of artists filed a class action lawsuit against several AI generated art companies. This comment evaluates the potential avenues the court may take. The artists allege these AI generated art companies directly infringed on their copyrighted works by making unauthorized copies of copyrighted works which they used to train their machine learning programs. A determination on whether AI generated art constitutes copyright infringement has not been made by the courts before. To b

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Wu, Nan. "A Comparative Analysis of Human-Written vs. AI-Generated Prompts for Task Executions." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 12 (2024): 1–3. https://doi.org/10.55041/ijsrem39321.

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Abstract—This study examines the effectiveness of AI-generated prompts in task execution compared to human-written prompts. AI-generated prompts showed comparable performance to expert-crafted prompts and offered greater flexibility, making prompt engineering more accessible to users. Future work will explore more advanced prompt templates. Keywords—AI-generated prompts, prompt engineering, task execution, content quality, humanized writing

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Price, Gregory, and Marc D. Sakellarios. "The Effectiveness of Free Software for Detecting AI-Generated Writing." International Journal of Teaching, Learning and Education 2, no. 6 (2023): 31–38. http://dx.doi.org/10.22161/ijtle.2.6.4.

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As artificial intelligence (AI) technology advances, educators are faced with the challenge of detecting AI-generated writing in student assignments. This study explores the effectiveness of freely available AI detection software in identifying AI-generated content and its implications for teacher evaluation of student work. The research involved Japanese university students who used AI for English writing assignments. We compared our manual analysis with results from five different free AI writing detectors. The findings reveal the limitations of free AI detection tools and the need for cauti

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Mukoji, Christopher. "Copyright Protection for AI-generated Works in Tanzania: The Need for Legal Reforms." East African Journal of Law and Ethics 7, no. 1 (2024): 149–60. http://dx.doi.org/10.37284/eajle.7.1.2436.

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This paper examines the current legal framework in Tanzania regarding copyright protection for works autonomously generated by artificial intelligence (AI). It highlights the lag in Tanzanian law, specifically the Copyright and Neighbouring Rights Act of 1999, in addressing the issues caused by AI-generated works. Advancements in AI, especially generative AI, are enabling the creation of literary, artistic, and musical works without human input. This challenges traditional concepts of authorship and ownership of literary and artistic works. The paper identifies limitations in the Tanzanian cop

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Håkansson Lindqvist, Marcia, and Catarina Arvidsson. "Exploring Student and AI Generated Texts: Reflections on Reflection Texts." Electronic Journal of e-Learning 22, no. 6 (2024): 52–59. http://dx.doi.org/10.34190/ejel.22.6.3473.

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As pointed out by many scholars, Artificial Intelligence (AI) provides both opportunities and challenges in regard to assignments and examination in higher education. The accessibility and use of AI in regard to student assignments, examinations and assessments places demands on teachers’ work in course design and formats of assignments and examination. For teachers, this work is a constant and continuous process, in line with the Scholarship of Teaching and Learning (SoTL) according to Boyer (1991). In order to meet these new demands, teachers need to reflect upon design, as reflective practi

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Ratta, Ali Ashraf, Saba Muneer, and Hisham ul Hassan. "The Impact of AI Generated Advertising Content on Consumer Buying Intention and Consumer Engagement." Bulletin of Business and Economics (BBE) 13, no. 2 (2024): 1152–57. http://dx.doi.org/10.61506/01.00476.

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This Study explores the difference between human generated advertising content and the AI generated Advertising content and this research explore the impact on AI generated advertising content on consumer engagement and consumer buying behavior. Qualitative approach used to unveil the perception about AI Generated Advertising content in the perspective of Marketers and AI experts and answer that what is different in humanly created advertising content and Ai generated advertising content. This study elaborates the impact of AIGAC on brands sales volumes and competitive edges. Researcher conduc

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Lavrič, Franc, and Andrej Škraba. "Brainstorming Will Never Be the Same Again—A Human Group Supported by Artificial Intelligence." Machine Learning and Knowledge Extraction 5, no. 4 (2023): 1282–301. http://dx.doi.org/10.3390/make5040065.

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A modification of the brainstorming process by the application of artificial intelligence (AI) was proposed. Here, we describe the design of the software system “kresilnik”, which enables hybrid work between a human group and AI. The proposed system integrates the Open AI-GPT-3.5–turbo model with the server side providing the results to clients. The proposed architecture provides the possibility to not only generate ideas but also categorize them and set priorities. With the developed prototype, 760 ideas were generated on the topic of the design of the Gorenjska region’s development plan with

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Borg, Massimo, and Marina Bluvshtein. "Early Recollections and the Use of Artificial Intelligence." Journal of Individual Psychology 80, no. 2 (2024): 130–48. http://dx.doi.org/10.1353/jip.2024.a929767.

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ABSTRACT: This article explores the use of artificial intelligence–generated images in Adlerian work with clients’ early recollections. The history of AI, the current advances in the use of AI in health care, the risks and benefits of AI, and the directions for future studies and possible clinical use are addressed. A case example with the use of Midjourney-generated images is presented.

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Wang, Yongqing. "A Study on the Identification of Artificial Intelligence-generated Content Works and Copyright Attribution: Taking Sora, a Large Model of Text-generated Video, as an Example." Journal of Economics and Law 1, no. 4 (2024): 77–84. https://doi.org/10.62517/jel.202414411.

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The emergence of a large model of text-generated video, represented by Sora, sheds new light on the identification of works and the discussion of copyright attribution of AI-generated content. Under "anthropocentrism", works protected by copyright law have the requirement of originality, so whether the content generated by AI in text-generated videos meets the requirement of originality is of great significance for the determination of works. In addition, determining the copyright attribution of AI-generated content is conducive to the division of rights and obligations over AI-generated conte

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Putra, Edy Semara. "THE ROLE OF AI IN CONTEMPORARY ART: CAN AI WORK BE CONSIDERED "ORIGINAL" ART?" CITA KARA : JURNAL PENCIPTAAN DAN PENGKAJIAN SENI MURNI 5, no. 1 (2025): 117–25. https://doi.org/10.59997/ctkr.v5i1.5422.

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The development of artificial intelligence (AI) in contemporary visual arts has presented both challenges and opportunities. This study examines the role of AI in art creation and its legal and ethical implications, particularly regarding copyright and originality. Using a qualitative descriptive method through literature review, this research analyzes how AI influences the definition of art and the role of artists in the digital era. The findings indicate that AI can serve as a creative tool that expands artistic exploration but raises debates over the authenticity and copyright of AI-generat

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Wu, Nan. "A Comparative Analysis of Human-Written vs. AI-Generated Prompts for Task Executions." Journal of Artificial Intelligence & Cloud Computing 3, no. 6 (2024): 1–5. https://doi.org/10.47363/jaicc/2024(3)410.

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This study examines the effectiveness of AI-generated prompts in task execution compared to human-written prompts. AI-generated prompts showed comparable performance to expert-crafted prompts and offered greater flexibility, making prompt engineering more accessible to users. Future work will explore more advanced prompt templates.

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ABAH, Joshua Abah, Ubagu David Terungwa, and Taurayi Willard Chinaka. "Conceptualizing the Influence of Artificial Intelligence on Students’ Academic Integrity." Journal of Mathematics Instruction, Social Research and Opinion 4, no. 2 (2025): 257–90. https://doi.org/10.58421/misro.v4i2.383.

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Artificial Intelligence (AI) has evolved into an indispensable tool in education. AI usage in education permeates tutoring systems, automated essay scoring, plagiarism detection, virtual reality simulations, and chatbot-based learning support. This ubiquity has threatened the tenets of academic integrity upon which the entire education system hinges. This present conceptualization focuses on demystifying the concepts and conversations at the nexus of AI adoption and academic integrity. The conceptualization deeply explored the development of AI and the motivation for its deployment in educatio

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Yeadon, Will, Oto-Obong Inyang, Arin Mizouri, Alex Peach, and Craig P. Testrow. "The death of the short-form physics essay in the coming AI revolution." Physics Education 58, no. 3 (2023): 035027. http://dx.doi.org/10.1088/1361-6552/acc5cf.

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Abstract The latest AI language modules can produce original, high quality full short-form (300-word) Physics essays within seconds. These technologies such as ChatGPT and davinci-003 are freely available to anyone with an internet connection. In this work, we present evidence of AI generated short-form essays achieving First-Class grades on an essay writing assessment from an accredited, current university Physics module. The assessment requires students answer five open-ended questions with a short, 300-word essay each. Fifty AI answers were generated to create ten submissions that were inde

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尚, 秀秀. "Comparative Study on Copyrightability of the Ai-Generated Work between China and Japan." Advances in Social Sciences 11, no. 12 (2022): 5299–305. http://dx.doi.org/10.12677/ass.2022.1112721.

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Dazzeo, Robin. "AI-Enhanced Writing Self- Assessment." Journal of Technology-Integrated Lessons and Teaching 3, no. 2 (2024): 80–85. https://doi.org/10.13001/jtilt.v3i2.9119.

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This technology-rich, three-day lesson for 9th-12th grade English Language Arts students leverages artificial intelligence (AI)-enhanced rubrics and writing analysis tools (Ouyang & Jiao, 2021) to improve student writing and self-assessment skills. Students explore AI-enhanced digital rubrics, use AI tools to analyze their writing, and apply AI-generated feedback to revise their work. This approach enhances current writing assignments and develops critical thinking skills and digital literacy. Assessments include AI-generated feedback reports, peer evaluations, and final revised writing sa

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De Cicco, Roberta, Barbara Francioni, Ilaria Curina, and Marco Cioppi. "AI, human or a blend? How the educational content creator influences consumer engagement and brand-related outcomes." Journal of Services Marketing 39, no. 10 (2025): 52–70. https://doi.org/10.1108/jsm-10-2024-0539.

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Purpose This study aims to investigate the impact of educational digital content (EDC) creators on perceived content quality, consumer engagement, brand attitude and advocacy intention. Design/methodology/approach The research consists of two experimental studies. In Study 1 (N = 172), participants were exposed to either AI-generated or human-generated educational content, with measured perceived content quality and consumer engagement. In Study 2 (N = 158), the authors extended the investigation and compared the effects of AI-generated, human-generated and hybrid-generated EDC on consumer eng

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James, Thomas B. "Artificial Intelligence, Copyright Registration, and the Rule of Doubt." Texas A&M Law Review Arguendo 12, no. 1 (2024): 20–31. http://dx.doi.org/10.37419/lr.v12.arg.2.

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Artificial intelligence (“AI”) technology has detonated an explosive burst of seemingly creative expression. Stories, images, music, and even entire books are now being generated very quickly. This development is a major headache for copyright registrars because the copyrightability of works created in this way is uncertain. The almost limitless variability in the extent of human involvement in the creation of a work using an AI tool compounds the uncertainty. In some cases, copyrightability is easy to determine, such as where an author only claims rights in the selection and arrangement of AI

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Ma, Xinyu, Hengyu Meng, Ziwei Wu, Zeyu Wang, and Clea T. von Chamier-Waite. "Becoming Space: Exploring Agential Materiality through AI-Generated Metamorphosis in Artistic Practice." Proceedings of the ACM on Computer Graphics and Interactive Techniques 8, no. 3 (2025): 1–11. https://doi.org/10.1145/3736775.

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This paper examines the intersection of materiality, agency, and transformation in AI-assisted artistic practice through Becoming Space , an installation of 3D printed sculptures and video. Drawing from Ovid’s Metamorphoses , the work investigates states of transformation between human and animal forms using generative AI and additive manufacturing. Through a theoretical investigation, this paper tries to analyze how material-discursive practices emerge in the convergence of language and physical materials. The work demonstrates how agency distributes across human and nonhuman actors in creati

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Dong, Ruihan. "Study on the Copyrightability of Objects Created by Artificial Intelligence." Applied and Computational Engineering 135, no. 1 (2025): 204–9. https://doi.org/10.54254/2755-2721/2025.21219.

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With the continuous development of AI technology, the emergence of a large number of AI-generated products has brought about many urgent problems for copyright law. At the forefront of this issue is the question of whether AI-generated objects can be copyrighted. In this paper, we first summarize the consistent jurisprudential ideas through case studies: analyzing the controversial aspects of "originality" and "intellectual achievement" in the definition of works to determine whether AI-generated products are works. In terms of originality, applying the criteria of "unique" and "original", thi

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Mr., Anup D. Mohadkar, and Mrs. S. T. Aurangabadkar Dr. "Artificial Intelligence and Work-Life Balance: Transforming the Academic Landscape for Educators." International Journal of Advance and Applied Research S6, no. 22 (2025): 419–24. https://doi.org/10.5281/zenodo.15502012.

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<em>The rapid integration of Artificial Intelligence (AI) within academia has generated considerable interest in its potential to transform educators' work-life balance, teaching methodologies, and institutional practices. This study examines the role of AI in reshaping the academic landscape, specifically focusing on its effects on workload distribution, job expectations, and mental well-being. The research illuminates how AI can streamline administrative tasks, enhance student engagement, and personalize learning experiences by exploring the benefits and challenges associated with AI-driven

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Mr., Anup D. Mohadkar, and Mrs. S. T. Aurangabadkar Dr. "Artificial Intelligence and Work-Life Balance: Transforming the Academic Landscape for Educators." International Journal of Advance and Applied Research S6, no. 22 (2025): 832–37. https://doi.org/10.5281/zenodo.15533490.

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<em>The rapid integration of Artificial Intelligence (AI) within academia has generated considerable interest in its potential to transform educators' work-life balance, teaching methodologies, and institutional practices. This study examines the role of AI in reshaping the academic landscape, specifically focusing on its effects on workload distribution, job expectations, and mental well-being. The research illuminates how AI can streamline administrative tasks, enhance student engagement, and personalize learning experiences by exploring the benefits and challenges associated with AI-driven

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Jarrahi, Mohammad Hossein. "In the age of the smart artificial intelligence: AI’s dual capacities for automating and informating work." Business Information Review 36, no. 4 (2019): 178–87. http://dx.doi.org/10.1177/0266382119883999.

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Recent developments in artificial intelligence (AI) have generated tidal waves, which are shaking the foundation of organizations and businesses. Even though AI is considered an unprecedented disruptive force for work automation, much can be learned from current research on the computerization of work. Drawing on the seminal work of Shoshana Zuboff, this article provides a balanced perspective on the dual affordances of AI systems for automating and informating work. Whereas AI offers unique capacities for automating cognitive work that once required high-skill workers, it may be a source of u

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Mayana, Ranti Fauza, Tisni Santika, Yin Yin Win, Jamil Adrian Khalil Matalam, and Ahmad M. Ramli. "Legal Issues of Artificial Intelligence – Generated Works: Challenges on Indonesian Copyright Law." LAW REFORM 20, no. 1 (2024): 54–75. http://dx.doi.org/10.14710/lr.v20i1.61262.

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Digital transformation fosters the massive utilization of Artificial Intelligence (AI) in creating literary, artistic, and musical works worldwide, including in Indonesia. The autonomous functioning of AI challenges the essential presumption that technology is merely a device in the hands of humans in the creation process of Works. This paper examines several legal issues and problems concerning the copyright-ability, authorship, and ownership of AI-generated works using a juridical normative approach. The result of the analysis shows that although the framework of Indonesia's copyright law is

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Kurnia, Rudi, and Arifpermana Ratum. "STUDI PERBANDINGAN KARYA STORYBOARD MAHASISWA DENGAN IMAGE GENERATED AI." EDUTECH 23, no. 3 (2024): 393–406. https://doi.org/10.17509/e.v23i3.73841.

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This research discusses the comparison between storyboards created manually by students and those generated using an AI Image Generator. With the rapid development of artificial intelligence (AI), its usage in education, particularly in visual design, has been increasing. This study investigates whether the outputs generated by AI are comparable to manual work in terms of design principles such as emphasis, rhythm, balance, unity, as well as scale and proportion. Data were collected from the storyboard assignments of BINUS Bandung students in the "Production and Storytelling" course, resulting

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O’Grady, Stefan. "An AI Generated Test of Pragmatic Competence and Connected Speech." Language Teaching Research Quarterly 37 (November 2023): 188–203. http://dx.doi.org/10.32038/ltrq.2023.37.10.

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Language testing is witnessing increasing interest in the potential for AI to support test development and validation. To date, published research involving AI in language testing has typically been conducted in the context of high-stakes proficiency tests and the potential for this technology to support local language testing is under-researched. The current study seeks to address this gap by reporting on the piloting of an AI generated language test in the context of a university in the UK. The focus of the paper was selected to explore two key areas in the work of J.D. Brown, namely pragmat

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Tang, Yan Fei, and Wai Yie Leong. "Integrating AI-generated art styles into traditional illustration design teaching course." Eurasia Journal of Mathematics, Science and Technology Education 21, no. 7 (2025): em2668. https://doi.org/10.29333/ejmste/16602.

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This study explores the integration of AI image-generation technology into traditional illustration education, focusing on projects centered on Chinese cultural elements (e.g., Dream of the Red Chamber, Dunhuang art). Through mixed-method analysis of 32 design students’ work and survey data, we evaluated AI’s impact on creative efficiency, cultural reinterpretation, and pedagogical challenges. Results indicate AI significantly accelerates design iteration and inspires conceptual exploration yet struggles with cultural accuracy–requiring human intervention to correct symbolic misrepresentations

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Zhang, Yalin. "The Impact of AI-Generated Content on China’s New Media Visual Creative Practitioners." SHS Web of Conferences 207 (2024): 03002. https://doi.org/10.1051/shsconf/202420703002.

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This article mainly focuses on the impact of the current AIGC applied to the film and television or media industry on the work content or form of work. Based on the work characteristics of AIGC, the commonalities and differences between visual creative workers are analysed from a realistic perspective, and the main impact of the two on workload and work efficiency is discussed. The research method is mainly based on in-depth interviews with industry insiders, focusing on the current employment environment and work content, and the media industry is mainly divided into two parts: business and d

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Su, Zhaoyuan, Lu He, Sunit P. Jariwala, Kai Zheng, and Yunan Chen. ""What is Your Envisioned Future?": Toward Human-AI Enrichment in Data Work of Asthma Care." Proceedings of the ACM on Human-Computer Interaction 6, CSCW2 (2022): 1–28. http://dx.doi.org/10.1145/3555157.

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Patient-generated health data (PGHD) is crucial for healthcare providers' decision making, as it complements clinical data by providing a more holistic view of patients' daily conditions. We interviewed 20 healthcare providers in asthma care to envision future technologies to support their PGHD use. We found that healthcare providers want future artificial intelligence (AI) systems to enhance their ability to treat patients by analyzing PGHD for profiling risk and predicting deterioration. Despite the potential benefits of AI, providers perceived various challenges of AI use with PGHD, includi

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Wu, Yuheng, Yi Mou, Zhipeng Li, and Kun Xu. "Investigating American and Chinese Subjects’ explicit and implicit perceptions of AI-Generated artistic work." Computers in Human Behavior 104 (March 2020): 106186. http://dx.doi.org/10.1016/j.chb.2019.106186.

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Wang, Haochen, Xuhui Liu, Ziqian Lu, et al. "RADAR: Reasoning AI-Generated Image Detection for Semantic Fakes." Technologies 13, no. 7 (2025): 280. https://doi.org/10.3390/technologies13070280.

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As modern generative models advance rapidly, AI-generated images exhibit higher resolution and lifelike details. However, the generated images may not adhere to world knowledge and common sense, as there is no such awareness and supervision in the generative models. For instance, the generated images could feature a penguin walking in the desert or a man with three arms, scenarios that are highly unlikely to occur in real life. Current AI-generated image detection methods mainly focus on low-level features, such as detailed texture patterns and frequency domain inconsistency, which are specifi

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Lin, Xi. "Protecting AI-Generated Images as Works of Fine Art in China: Magnifying the Legacy of Art to Copyright." Law, Technology and Humans 7, no. 1 (2025): 107–26. https://doi.org/10.5204/lthj.3825.

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Generative artificial intelligence (AI) challenges copyright by raising questions about whether AI-generated content (AIGC) qualifies as protectable works and who should own the associated rights. The Chinese judiciary addressed these issues in Li Yunkai v Liu Yuanchun (Li v Liu), a landmark case where the Beijing Internet Court ruled that an AI-generated image qualified as a work of fine art, with authorship vested in the user who entered the original prompts. This article evaluates the validity of the first holding within the judicial narrative about generative AIs. It argues that the Chines

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Phalaguna, Ida bagus, Khwanjai Kaewsaeng, and Thaworn Worabuttara. "Exploring Teachers' Perceptions of AI-Generated English Lesson Plans for Students with Intellectual Disabilities." International Journal of Instructions and Language Studies 2, no. 2 (2024): 19–28. https://doi.org/10.25078/ijils.v2i2.4251.

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This research explores teachers' perceptions of AI-generated English lesson plans specifically designed for students with intellectual disabilities. The objective is to assess the effectiveness and usability of AI tools, namely ChatGPT, in enhancing lesson planning for this unique student population. A mixed-methods approach was employed, combining qualitative interviews and quantitative surveys with 14 teachers who work with students with intellectual disabilities. The findings reveal a general satisfaction among teachers regarding the innovative ideas and time-saving benefits of AI-generated

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Aamir Mushtaq, Shahzada, Khurram Baig, Syed Wajdan Rafay Bukhari, and Waqas Ahmad. "Does Pakistan's Copyright and Antitrust Law Protect Creators of AI-Generated Content? A Comparative Study with European Union Jurisdictions." Pakistan Journal of Criminal Justice 4, no. 1 (2024): 55–76. http://dx.doi.org/10.62585/pjcj.v4i1.51.

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With the rise of artificial intelligence (AI), how should copyright and antitrust law handle AI-created creative work? The Copyright Ordinance 1962 and Competition Act 2010 are examined in this context to examine Pakistan's legal system. This study compares Pakistan's legal system to the EU's. The study focuses on the DMA and the EU Copyright Directive (2019/790). These two laws measure Pakistan's legal strength. Compare and contrast the legal systems of Pakistan with those of the European Union to find weaknesses and opportunities for progress in Pakistan's legal structure. This study may ass

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Howard, Frederick Matthew, Anran Li, Mark Riffon, Elizabeth Garrett-Mayer, and Alexander T. Pearson. "Artificial intelligence (AI) content detection in ASCO scientific abstracts from 2021 to 2023." Journal of Clinical Oncology 42, no. 16_suppl (2024): 1565. http://dx.doi.org/10.1200/jco.2024.42.16_suppl.1565.

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1565 Background: Generative AI models such as OpenAI’s ChatGPT have been broadly utilized throughout the medical literature. Previous studies have found that AI can generate scientific abstracts which can be difficult to distinguish from the work of human authors. There is a pressing need to characterize utilization of AI in scientific writing to guide policy. Methods: In collaboration with ASCO's Center for Research and Analytics, we extracted text from all scientific abstracts submitted to ASCO 2021 – 2023 Annual Meetings. Likelihood of AI content was evaluated by four AI detectors: GPTZero,

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