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Littérature scientifique sur le sujet « AI-Generated work »

Auteur : Grafiati

Publié le 2 juin 2025

Mis à jour le 31 juillet 2025

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Articles de revues sur le sujet "AI-Generated work"

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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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. 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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Thèses sur le sujet "AI-Generated work"

Makarowski, Felix. "AI and creative machines : copyright protection for AI generated works under EU and Swedish law." Thesis, Uppsala universitet, Juridiska institutionen, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-376798.

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The purpose of this thesis is to examine questions related to copyright protection of worksgenerated by artificial intelligence (AI) under EU and Swedish law. The first question that is examined in this thesis is whether works created by AI are at all eligiblefor copyright protection in Sweden and who is the creator of such works: the human behind theAI, the AI itself, both, or perhaps nobody. To determine who the creator of an AI generated workis, the term creator is first defined. The definition is then be applied to two cases. In the firstcase, a human and an AI collaborate to create a work

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Hsu, Li-Ju, and 許力儒. "A Discussion on the Copyright of AI-Generated Works: Based on the Laws of the U.S. and Taiwan." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/dkj639.

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碩士 國立交通大學 科技法律研究所 107 Artificial Intelligence （AI） is rising rapidly in recent years. It could generate a great quantity of works with high quality in a short time. However, the developing speed of regulations is far slower than the technology. The related laws and issues of AI-generated works haven’t come to a conclusion yet. It may bring some impacts to the creative industries in the future. The purposes of this article are to combine both legal and technical perspectives, explore the subject matter and ownership issues of copyright related to AI-generated works, try to solve the

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Grisales, Rendón Laura. "Attribution of Copyright to Artificial Intelligence Generated Works." Master's thesis, 2019. http://hdl.handle.net/21.11130/00-1735-0000-0003-C1A6-7.

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Livres sur le sujet "AI-Generated work"

Lilholt, Addison, OpenAI ChatGPT, and OpenAI DALL-E. Zippy the Moon Worm: An AI-Generated Children's Story. Lulu Press, Inc., 2023.

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Chapitres de livres sur le sujet "AI-Generated work"

Liu, Yuxin, and Keng L. Siau. "Generative Artificial Intelligence and Metaverse: Future of Work, Future of Society, and Future of Humanity." In AI-generated Content. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-7587-7_10.

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Agarwal, Pratik, and Joshua Aston. "The Protection of AI-Generated Work." In Recreating Creativity, Reinventing Inventiveness. Routledge, 2024. http://dx.doi.org/10.4324/9781003260127-13.

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Tuomi, Aarni. "AI-Generated Content, Creative Freelance Work and Hospitality and Tourism Marketing." In Information and Communication Technologies in Tourism 2023. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-25752-0_35.

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AbstractPowerful new AI models such as OpenAI’s DALL-E 2 or GPT-3 afford creative freelancers as well as hospitality and tourism SMEs new ways of generating and using creative content for marketing purposes. However, given AI’s rapid development, little is known about the current and potential future applications and implications of AI-generated content on the key stakeholders involved in hospitality and tourism marketing management. This conceptual research note presents preliminary ideas from an ongoing research project. Examples of AI models used for marketing content generation are reviewe

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Lee, Kai-Fu. "A Human Blueprint for AI Coexistence." In Robotics, AI, and Humanity. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-54173-6_22.

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AbstractThe positive coexistence of humans and AI is possible and needs to be designed as a system that provides for all members of society, but one that also uses the wealth generated by AI to build a society that is more compassionate, loving, and ultimately human. It is incumbent on us to use the economic abundance of the AI age to foster the values of volunteers who devote their time and energy toward making their communities more caring. As a practical measure, to protect against AI/robotics’ labor saving and job displacement effects, a “social investment stipend” should be explored. The

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Bhattacharya, Pronaya, Pushan Kumar Dutta, Bhisham Sharma, Subrata Chowdhury, and Imed Ben Dhaou. "Amber Alert: Unveiling an AI Solution for Enhanced Missing Persons Searches." In Proceedings in Technology Transfer. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-8588-9_5.

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Abstract In today online platforms, physical and biometric based identification is of paramount importance. Thus, to cater the high-processing needs of such applications, Artificial Intelligence (AI) based techniques have been a game-changer. These AI models works on user histories, that include user information, his photos, body and facial postures, and form matching identifications and similar community involvement recommendations. Deep Learning (DL), in particular, is used to work on facial and matching capabilities. In the context of missing persons reports filed to local authorities, thes

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Gans-Combe, Caroline. "Automated Justice: Issues, Benefits and Risks in the Use of Artificial Intelligence and Its Algorithms in Access to Justice and Law Enforcement." In Research Ethics Forum. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15746-2_14.

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AbstractThe use of artificial intelligence (AI) in the field of law has generated many hopes. Some have seen it as a way of relieving courts’ congestion, facilitating investigations, and making sentences for certain offences more consistent—and therefore fairer. But while it is true that the work of investigators and judges can be facilitated by these tools, particularly in terms of finding evidence during the investigative process, or preparing legal summaries, the panorama of current uses is far from rosy, as it often clashes with the reality of field usage and raises serious questions regar

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Turchan, Krzysztof, and Krzysztof Piotrowski. "Low Voltage Warning System for Stand-Alone Metering Station Using AI on the Edge." In Digital Interaction and Machine Intelligence. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11432-8_10.

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AbstractArtificial intelligence is used in many different aspects of life these days. It is also increasingly used to create intelligent embedded devices. Their main task is to demonstrate intelligent features using limited hardware resources. This paper introduces the possibility of using AI on the Edge as a system to warn of low voltage on the battery in a stand-alone metering station powered by solar panels. The paper presents theoretical knowledge about artificial intelligence on the Edge, time series and algorithms in time series forecasting. In addition, a practical approach is presented

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Del Rio, Mauro, Luca Lianas, Oskar Aspegren, et al. "AI Support for Accelerating Histopathological Slide Examinations of Prostate Cancer in Clinical Studies." In Lecture Notes in Computer Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13321-3_48.

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AbstractWhile studies in pathology are essential for the progress in the diagnostic and prognostic techniques in the field, pathologist time is becoming an increasingly scarce resource, and can indeed become the limiting factor in the feasibility of studies to be performed. In this work, we demonstrate how the Digital Pathology platform by CRS4, for supporting research studies in digital pathology, has been augmented by the addition of AI-based features to accelerate image examination to reduce the pathologist time required for clinical studies. The platform has been extended to provide comput

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Ching, Vivian, and Dinesh Mothi. "Legal and Regulatory Frameworks for AI-Generated Creative Works." In AI for Creatives. Auerbach Publications, 2025. https://doi.org/10.1201/9781003533016-7.

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Kazeeva, Iana. "Sui Generis Intellectual Property Protection for Works Generated by AI Systems." In Sui Generis Intellectual Property Protection. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8897-6_5.

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Actes de conférences sur le sujet "AI-Generated work"

Xie, Yejuan, Yunzhe Wang, Yushi Li, Rongrong Chen, Peiyu Hu, and Chengtao Ji. "Create3DHistory: Creating and Customizing Historical Timelines with AI-Generated Content." In 2025 28th International Conference on Computer Supported Cooperative Work in Design (CSCWD). IEEE, 2025. https://doi.org/10.1109/cscwd64889.2025.11033575.

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Hoshiar, Singh, and Sharma Kiran. "Copyright in the Age of Artificial Intelligence: Unravelling the Complexities For the Protection of AI-Generated Work." In 2024 ITU Kaleidoscope: Innovation and Digital Transformation for a Sustainable World (ITU K). IEEE, 2024. https://doi.org/10.23919/ituk62727.2024.10772817.

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Shahhoseyni, Shabnam, Arijit Chakraborty, Mohammad Reza Boskabadi, Venkat Venkatasubramanian, and Seyed Soheil Mansouri. "Hybrid machine-learning for dynamic plant-wide biomanufacturing." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.174465.

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This study focuses on biomanufacturing case study, i.e. Lovastatin production, employing a hybrid modeling framework that combines mechanistic and data-driven approaches. A time-series dataset was generated using the KT-Biologics I (KTB1) plantwide model, a dynamic simulation of continuous biomanufacturing. The dataset captures critical parameters such as nutrient concentrations and API production. The AI-DARWIN framework was used to develop interpretable machine learning models with constrained functional forms, ensuring both accuracy and clarity. The resulting polynomial-based models reveal

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Jiang, Hang, Doug Beeferman, William Brannon, Andrew Heyward, and Deb Roy. "Bridging Dictionary: AI-Generated Dictionary of Partisan Language Use." In CSCW '24: The 27th ACM Conference on Computer-Supported Cooperative Work and Social Computing. ACM, 2024. http://dx.doi.org/10.1145/3678884.3681820.

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Almutairi, Mohammed, Charles Chiang, Yuxin Bai, and Diego Gomez-Zara. "tAIfa: Enhancing Team Effectiveness and Cohesion with AI-Generated Automated Feedback." In CHIWORK '25: Proceedings of the 4th Annual Symposium on Human-Computer Interaction for Work. ACM, 2025. https://doi.org/10.1145/3729176.3729197.

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Li, Xian, Yuanning Han, Di Liu, Pengcheng An, and Shuo Niu. "FlowGPT: Exploring Domains, Output Modalities, and Goals of Community-Generated AI Chatbots." In CSCW '24: The 27th ACM Conference on Computer-Supported Cooperative Work and Social Computing. ACM, 2024. http://dx.doi.org/10.1145/3678884.3681875.

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Ilic, Peter, and Nicholas Carr. "Work in Progress: Safeguarding Authenticity: Strategies for Combating AI-Generated Plagiarism in Academia." In 2023 IEEE Frontiers in Education Conference (FIE). IEEE, 2023. http://dx.doi.org/10.1109/fie58773.2023.10343337.

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Park, Sohyun, Someen Park, Jaehoon Kim, and Kyungsik Han. "Exploring the Impact of AI-Generated Images on Political News Perception and Understanding." In CSCW '24: The 27th ACM Conference on Computer-Supported Cooperative Work and Social Computing. ACM, 2024. http://dx.doi.org/10.1145/3678884.3681907.

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Sharma, Taruna, Priyansha Sachdev, Priya, and Supriya Kumari. "Unveiling Writing Styles: A Comparative Analysis of AI-Generated and Human Generated Content." In 2nd International Conference on Emerging Applications of Artificial Intelligence, Machine Learning and Cybersecurity. AIJR Publisher, 2025. https://doi.org/10.21467/proceedings.178.22.

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Artificial Intelligence (AI) has revolutionized the process of producing content, and this has raised many questions about the kind of difference the writing styles of material produced by AI and that of humans differ from each other in. This is essential in exploring this important topic by comparing or contrasting a wide range of writing style indicators. It attempts to identify observable trends and differences in writing styles by looking at the complexity of words, semantics, readability, sentiment analysis, vocabulary variety, and plagiarism rate. Using a strict methodology, the content

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Ho, Amic. "Redefining Creativity and Artistic Endeavours: Exploring the Impact of AI-Generated Digital Art on Human Society." In 12th International Conference on Human Interaction and Emerging Technologies (IHIET 2024). AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1005476.

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Artificial intelligence has transformed the field of creative work, challenging existing ideas of creativity and creative work. AI-generated digital art has emerged at the crossroads of innovative technology and human creativity and prompted an extensive investigation into its potential consequences on a wide range of human activity. Students also consider whether AI-generated digital art influences individuals’ willingness to engage in art-related activities and produce their work. The use of AI in art evokes components of self-consciousness and identity. Furthermore, the researchers examined

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