This is the accepted manuscript version. The final published version will appear in College & Research Libraries, November 2026. AI Literacy in UAE Libraries: Assessing Competencies, Training Needs, and Ethical Considerations for the Digital Age Zafar Imam Khan, Learning Resources Manager, Hamdan Bin Mohammed Smart University, Dubai, United Arab Emirates, Email: zafarimamkhan@gmail.com, https://orcid.org/0000 - 0003 - 2081 - 0951 Abstract The study explores the current state of artificial intelligence (AI) literacy levels among library professionals employing a quantitative approach consisting of 92 surveys of LIS professionals in the United Arab Emirates (UAE). Findings of the study reveal ed the presence of strong cognitive competencies, while there were gaps observed in behavioral and normative competencies, especially related to AI biases, AI - powered learning, and ethical considerations. There was a disconnect observed between the perceiv ed importance of AI skills and the effectiveness of the current training programs. Introduction Generative AI has created massive disruption in all sectors, such as manufacturing, services, agriculture, medicine, and education, and has transformed a range of operations and services. Libraries are transforming and gearing up to harness the power of AI, which can enhance efficiency, accessibility, and personalization of services; thereby reshaping the traditional library landscape. This transformation has been observed in several of the traditional library services as AI is automating routine tasks such as cataloguing and classification of collections, and enhancing search functionalities and information retrieval, thereby creating a much more accurate and organized library system while librarians have more time to focus on intellectually stimulating act ivities (Preethi, 2024). There is a race to integrate AI into library services at a global level, and this has presented both opportunities and challenges in terms of AI literacy among library professionals. AI literacy involves understanding of AI tools, their applications, and ethical considerations surrounding their use.

In an age of fast-paced technological change, patents have evolved into not only legal mechanisms of intellectual property, but also structured storage containers of knowledge full of metadata, categories, and formal innovation. This chapter proposes to reframe patents in the context of information science, by focusing on patents as knowledge artifacts, and by seeing patents as fundamentally tied to the global movement of scientific and technological knowledge. With a focus on three areas, the inventions of AIs, biotech patents, and international competition with patents, this work considers how new technologies are challenging traditional notions of inventorship, access, and moral accountability.The chapter provides a critical analysis of AI's implications for patent authorship and prior art searches, ownership issues arising from proprietary claims in biotechnology to ethical dilemmas, and the problem of using patents for strategic advantage in a global context of innovation competition. In this analysis, the chapter identified the importance of organizing information, creating metadata standards about originality, implementing retrieval systems to access previous works, and ethical contemplation about patenting unseen relationships in innovation ecosystems. Ultimately, the chapter called for a collaborative, transparent, and ethically-based approach in managing knowledge in the patenting environment highlighting the role for information professionals and policy to contribute to access equity in innovation.

Follow this and additional works at: https://digitalcommons.unl.edu/libphilprac Subaveerapandiyan A Ph.D. Research Scholar Department of Library and Information Science Yenepoya (Deemed to be University), Mangalore, Karnataka, India Email: subaveerapandiyan@gmail.com ORCiD: https://orcid.org/0000-0002-2149-9897 Abstract This study aims to understand the perceptions and opinions of academicians towards ChatGPT-3 by collecting and analyzing social media comments, and a survey was conducted with library and information science professionals. The research uses a content analysis method and finds that while ChatGPT-3 can be a valuable tool for research and writing, it is not 100% accurate and should be cross-checked. The study also finds that while some academicians may not accept ChatGPT-3, most are starting to accept it. The study is beneficial for academicians, content developers, and librarians. Keywords: Conversational Generative Pre-training Transformer (ChatGPT), Artificial Intelligence in Academia, Academic Writing with ChatGPT, Library Services Introduction The OpenAI-developed GPT (Generative Pre-trained Transformer) model has a variation called ChatGPT. The GPT model was initially released in 2018 and trained using the Common Crawl, a sizable dataset of text from the internet. The Transformer design, revealed in a 2017 study by Google researchers, served as the model's foundation. Unsupervised learning was used to train the initial GPT model, which meant that it was trained on a sizable text dataset without any explicit labels or annotations.

How do we ensure that today's workforce has the skills and understanding they need in order to enable them to support their users in participating safely and successfully in a modern world that is increasingly powered by artificial intelligence (AI), machine learning, process automation and robotics? What are the ethical implications of our approach to these technologies – how can we deploy the existing ethical framework for librarians and ensure that it aligns to emerging work on Data Ethics and responsible technology? What should the skillset of the future workforce look like and what is the curriculum by which we will ensure that the next generation of information professionals have the skills to keep pace with future developments in technology? How do we ensure that today's workforce has the skills and understanding they need in order to enable them to support their users in participating safely and successfully in a modern world that is increasingly powered by artificial intelligence (AI), machine learning, process automation and robotics? What are the ethical implications of our approach to these technologies – how can we deploy the existing ethical framework for librarians and ensure that it aligns to emerging work on Data Ethics and responsible technology?

Artificial intelligence has risen to prominence this year. In March 2016, Google DeepMind's AlphaGo won 4-1 in the Chinese game of Go, beating the top Go player in the world over the past decade, Lee Sedol. And IBM's Watson correctly diagnosed a Japanese leukaemia patient in ten minutes after doctors had failed to diagnose her condition over several months. Navigating this information requires vastly more sophisticated tools than hitherto available. Large industry players are aware of this and Google, IBM and Microsoft are all investing heavily.