Artificial intelligence, and especially generative AI, has changed the production and distribution of creative and commercial content nowadays. AI can now create text, pictures, songs, and output associated with brands that are highly similar to those created by humans, which brings about a challenge of intellectual property rights specifically copyright and trademark. The copyright and trademark essentially safeguard human creativity and originality of the writer. It further gives the owners and authors exclusive rights. As the outputs of AI are used more and more, the brand image is diluted as there is more confusion with the consumer. The paper focuses on the new concerns of copyright and trademark infringement in the use of generative AI. It examines both the doctrine and empirical evidence in order to comprehend the legal implications of AI on a work under protection and the extent to which legal frameworks are sufficient to address such issues. Having evaluated the gathered data, the study defines gaps in regulations in the existing legal framework. It points to the necessity of the legal framework amendments that would strike a balance between technological development and efficient safeguarding of creators, brand owners, and consumers of the digital economy.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
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