Abstracts

Keynote by Dr. Leo Lo: “From Strategy to Practice: The Role of AI Literacy in the Future of Libraries”

Abstract:

As AI reshapes the information landscape, libraries must evolve from passive adopters to proactive educators in AI literacy. This keynote will explore how library professionals can become AI literate, integrate critical thinking into AI education, and implement effective upskilling strategies. Drawing on case studies and best practices, the talk will provide a roadmap for transitioning from strategy to action, helping libraries empower their staff and users to navigate an AI-driven world. Attendees will gain practical insights, tactical approaches, and inspiration to embed AI literacy into their organizations.

From data to discovery: Empowering research with comprehensive library services at SMU Libraries
Redzuan Abdullah

Abstract:

Academic libraries face increasing challenges in supporting complex research data needs across multiple financial and business databases. These challenges are amplified by the diverse nature of data sources, the intricacy of data extraction processes, and the varying levels of research support required by different user groups. While data quality issues persist, commercial databases in finance, accounting, and economics remain of significant interest for academic research (Liu et al., 2024; Reiter, 2020).

This presentation presents SMU Libraries’ comprehensive research & data services, particularly our specialized Data Discovery support, which emphasizes three distinctive offerings: expert guidance on data navigation and retrieval across platforms, customized data extraction solutions using Python and SQL, and advanced data matching and linking services across multiple databases.

The presentation also shares the essential skills-building capacity required to sustain this service model, highlighting the specialized knowledge needed across various business and finance databases such as WRDS, Refinitiv, Bloomberg, Capital IQ, and CEIC, and technical competency in programming skills.
To support this service framework, the library has also developed other targeted interventions through [1] curated workshops, and [2] knowledge base articles. The workshops include: 

• Navigating the data maze in WRDS: Practical techniques for dataset matching through identifiers 
• Data extraction from WRDS with Python programming
• Data for good: Navigating ESG databases for research success 
• Examples of knowledge base articles:
• Notes and thoughts on retrieving historical members of S&P 500 from WRDS 
• Something Old, Something New, Something Green: A Hop on ESG Data and Insights in Bloomberg and More 

Drawing from case studies and user feedback, the presentation demonstrates how our Data Discovery service model has contributed to advancing research support at SMU Libraries. These outcomes showcase how academic libraries can evolve into vital research partners, particularly in navigating the complexities of financial and business data resources. By sharing our journey and lessons learned, we provide actionable insights for libraries seeking to develop comprehensive research and data services in the age of AI and big data.

References:

• Liu, G., Bordelon, B., Nagar, R., Nguyen, U., Sarti, J., & Boettcher, J. (2024). Data Quality Literacy: A Guidebook. University Libraries Faculty Books. https://digitalcommons.wcupa.edu/libfaculty_books/6 
• Reiter, L. (2020). Commercial data in academic business research: A study on use and access. Journal of Business & Finance Librarianship, 25(3–4), 244–260. https://doi.org/10.1080/08963568.2020.1847546 

Enhancing Research Support through Bibliometric Analyses: Insights from the Central Economics Library
Jure Bresar, Martina Petan, Tomaz Ulcakar

Abstract:

Academic libraries play a critical role in supporting research by providing bibliometric analyses that assess research performance, identify influential publications, and reveal citation patterns. This study examines the Central Economics Library at the University of Ljubljana, School of Economics and Business (UL SEB), focusing on its bibliometric services and exploring the experiences and needs of researchers.

With advancements in network analysis and predictive modelling, AI tools could offer innovative ways to identify academic collaboration opportunities, uncover connections between research topics, and analyse citation dynamics in more sophisticated ways. How can AI-driven tools and machine learning algorithms transform bibliometric analyses in academic libraries? Can they enhance accuracy, uncover emerging research trends, and reveal patterns beyond traditional citation metrics? Advanced visualization technologies could further deepen insights into research ecosystems, offering dynamic perspectives that redefine bibliometric practices.

This study explores researchers’ perceptions of bibliometric tools, such as the h-index and journal impact factor, highlighting their utility for personal career advancement and institutional assessment. It also addresses concerns about the limitations of these tools, including their reliance on quantitative metrics and biases in citation indices. Furthermore, it examines how bibliometric analyses contribute to institutional accreditation and research strategy development.

Feedback from researchers will be collected to evaluate the library’s bibliometric services, focusing on strengths and areas for improvement. Key aspects include the accessibility of bibliometric tools, integration into research workflows, and the library’s role in providing reliable data. AI could enhance these services by automating data collection and analysis, reducing manual effort, and increasing the accuracy and speed of bibliometric reporting.

The study will provide actionable recommendations for academic libraries, such as:

• Expanding bibliometric services to include advanced analyses like collaboration network mapping and field-specific trend identification.
• Strengthening communication between librarians and researchers to align services with evolving research needs.
• Integrating AI-powered tools for real-time data analysis, offering actionable insights that enhance the efficiency of bibliometric support.

By addressing these areas, libraries can position themselves as indispensable partners in fostering research excellence and strengthening institutional reputation. This integration of advanced technologies and tailored services ensures libraries remain at the forefront of supporting academic innovation.

From Promise to Peril: AI Risks and Opportunities for Minoritised Communities
Attila Dabis

Abstract:

Among the agenda items of the INCONECSS 2025 conference, this presentation will contribute to the following topic: “Will AI change everything? – Risks and awareness of limitations.” This agenda topic will be explored from the specific viewpoint of national, ethnic, linguistic, and religious minorities, as well as indigenous and tribal peoples, under the umbrella term “minoritised communities”. Reflections on changing user needs and the evolving AI landscape will thus be presented from the specific hues experienced by minoritised communities.

Apart from the general difficulty of speaking Low Resource Languages (i.e. languages that lack sufficient digital and printed content, making it challenging to develop effective natural language processing tools and applications), minoritised communities experience a wide range of AI-related challenges and opportunities. Accordingly, the presentation will raise awareness of the Janus-faced nature of AI tools, concentrating on the fundamental question: How can AI technologies affect minoritised communities and the erosion or protection of their culture, language and identity? The presentation will briefly examine the harmful uses of AI in perpetuating discrimination and violating human rights while also reflecting on the benefits of AI.

The more positive side will display a variety of examples, with a focus on language revitalisation through AI tools. This part will present initiatives coming from European stateless nations, such as Basques and Catalans (e.g. Projecte AINA), as well as first nations, indigenous and tribal communities, like Māori or Sámi (e.g. FLAIR initiative). The potential drawbacks, on the other hand, will be demonstrated through the Chinese state’s digital authoritarianism practises vis-á-vis the Uyghur community, which is one of the worst existing practices of AI usage in relation to minorities.

The presentation will highlight that good examples and malicious usage, as well as top-down and bottom-up approaches to using Generative AI, exist simultaneously. Consequently, user intentions are pivotal in determining which outcome prevails for certain groups: the blissful impacts or the devastating ramifications.

AI in Action: Integrating Generative AI into Education and Operations at ESMT
Jonathan Demiglio

Abstract:

At ESMT, we are embracing the transformative potential of generative AI to revolutionize teaching, learning, and institutional operations. Through innovative, scenario-based initiatives, we are equipping our community with the skills to understand, apply, and harness AI effectively.

Our first initiative introduces students to the world of generative AI through a comprehensive course focusing on AI fundamentals, prompt engineering, and the strategic use of AI tools to enhance learning. By engaging with real-world scenarios, students gain hands-on experience, enabling them to confidently integrate AI into their academic and professional pursuits.

The second initiative is a tailored crash course designed for staff and faculty, aiming to demystify AI and emphasize the importance of prompt engineering. This program fosters a low-stakes, exploratory environment where participants tackle practical challenges, discovering when, where, and how generative AI can streamline and elevate their work.

Both programs are united by a shared goal: to provide participants with a sandbox for experimentation and discovery, empowering them to critically evaluate AI’s applications and limitations. These initiatives exemplify ESMT’s commitment to fostering a culture of continuous learning and innovation.

By integrating generative AI into our educational and operational frameworks, we are preparing our community to navigate and lead in an increasingly AI-driven world. This presentation will share insights, outcomes, and the impact of these initiatives, offering a roadmap for institutions seeking to adopt AI in meaningful and impactful ways.

Modernizing the Database Information System (DBIS) for Global Collaboration
Brigitte Doss

Abstract:

In an increasingly globalized academic world, efficient access to research resources and the ability to adapt to the diverse needs of researchers and institutions are of great importance. The Database Information System (DBIS) plays a central role in both the international and German information infrastructure.

DBIS allows libraries to individually customize their local DBIS views while benefiting from a shared metadata pool of both free and licensed databases. Currently, it contains information on approximately 14,000 academic databases across all disciplines, including more than 6,000 freely accessible databases. In the fields of Business and Economics, it provides information on 1,468 databases, of which 372 are freely available online. This comprehensive database overview is maintained cooperatively to ensure high quality and up-to-date content. Cooperative data maintenance helps keep the information current, with traffic light symbols indicating database accessibility within participating institutions. DBIS is already utilized by over 400 libraries.

As part of a comprehensive modernization, DBIS is now also available in English, opening up the service to international users. For over two decades, DBIS has offered a detailed overview of academic databases, including extensive coverage of the Business and Economics fields.

DBIS is part of UR Library Services, a product family that also includes the Electronic Journals Library (EZB) and the Regensburger Verbundklassifikation (RVK). These services have been provided by the University Library of Regensburg for decades.

The EZB offers not only comprehensive information about scholarly journals but also insights into publishing, particularly in relation to Open Access.

The subject areas in DBIS and EZB are based on the RVK, which has traditionally been used in German-speaking regions but prospectively becoming more internationally relevant through new English translations and existing concordances.

Open Library Economics (OLEcon): Enabling Diamond Open Access for journals in business and economics
Juliane Finger

Abstract:

Diamond Open Access removes financial barriers for both authors and readers, thereby contributing to equity in the publishing system. However, scholar-led Diamond Open Access journals that are independent of big commercial publishers face significant challenges, especially when it comes to long-term funding.

The poster presents an initiative that supports scholar-led Diamond Open Access in the disciplines of business and economics: the Open Library Economics (OLEcon). OLEcon is an initiative from ZBW – Leibniz Information Centre Economics (Germany). OLEcon helps journal editors who want to flip to a scholar-led Diamond Open Access model for their journals. OLEcon provides guidance for journal editors during the transformation to Diamond Open Access and facilitates sustainable funding. To achieve this, OLEcon is establishing a consortium of academic libraries that co-finance participating journals. From 2023-2026, the initiative receives additional project funding by the German Federal Ministry of Education and Research (BMBF).

The poster highlights experiences with two key aspects of the OLEcon model: First, the transparent selection process through which journal editors apply for OLEcon support. Second, the insights gained during the initial two years of establishing the consortial funding model for the OLEcon journals. The poster will detail effective mechanisms, challenges encountered and the next steps for strengthening and expanding the consortium.

Copyright in the age of AI : stepping into the future
Michel Fraysse

Abstract:

The use of generative Artificial Intelligence (AI) by researchers and information professionals is becoming a daily reality. More and more trainers and teachers, including those in libraries, are using AI tools to develop courses, training materials, presentations and online tutorials. They also need to support doctoral students and researchers in mastering these tools, especially regarding legal issues. In addition to the best-known platforms such as ChatGPT or Midjourney, there are a growing number of generative AI tools, each with its own specialties and specific terms of use, which add complexity. It is important to be aware of these terms and conditions in order to use or reuse documents (text, images, videos, etc.) without risk. Currently, copyright law has not evolved concerning the conditions of protection of works. For now in Europe, the protection of creations remains governed by European Union Directive 2019/790 of the European Parliament and Council, and national laws. To date, the conditions for protection imply a human and original creation, but case law and legislation will undoubtedly change this in the future. The AI act adopted in 2024 contains two copyright-related articles concerning the transparency obligations and opt-out possibilities for copyright owners imposed on companies providing AI.

This presentation aims to analyze the legal copyright situation of AI works in Europe in a comparative perspective, and the initial case law that may shed light on potential solutions to copyright issues for AI. It will also address and answer practical questions on the safe use or reuse of documents produced by AI.

Ethical Dimensions of AI in Education: A Machine Learning Analysis of Perspectives from Librarians and Information Specialists, Faculty, and Students at the Cesar Virata School of Business, College of Home Economics, and School of Economics, University of the Philippines Diliman
Corazon Martinez Gamboa, Grace Albarida Garcia, Jonathan Garcia Medina, Maria Maura Salang Tinao

Abstract:

Artificial intelligence is now integrated into education and all kinds of industries, such as business, economics, and home economics, raising the critical ethical concerns and creating enormous opportunities for innovation. Data privacy, algorithmic bias, job displacement, transparency, and accountability are among the most critical issues in the discussion of technical implications dominating the literature. However, the voices of academic professionals, including librarians and information specialists, remain underexplored. This paper seeks to bridge this gap by analyzing the ethical aspects of AI implementation in education, particularly as librarians and information specialists, faculty, and students see it at the Cesar Virata School of Business, College of Home Economics, and School of Economics, University of the Philippines Diliman.
Five primary objectives will guide this research: (1) investigate the ethical issues posed by AI adoption in teaching and working contexts; (2) compare how different types of actors, specifically librarians, faculty, and students, experience these concerns differently; (3) explore librarians‘ and information specialists‘ roles in addressing and reducing ethical risks; (4) assess strategies proposed for addressing ethical dilemmas regarding AI; and (5) use machine learning approaches to seek out patterns and trends that relate to the perception of ethical concerns, impact, and mitigation. Methods include Natural Language Processing (NLP), clustering algorithms such as K-Means and DBSCAN, and classification models like Support Vector Machines and Random Forest for predictive analysis.

Data collection is a well-structured survey that collects both quantitative and qualitative questions from stakeholders to ensure that the different perspectives are well understood. Through a machine learning analysis of those responses, this research derives subtle insights into ethical concerns regarding responsible AI integration.
Based on those findings, this paper will recommend evidence-actually practical recommendations to balance these competing elements, which should inform ethics-guidance for AI use in learning institutions. The results will expand research in the human and the institutional dimensions of AI and will provide actionable solutions regarding what academia and industry actually know to do about AI.

Developing computational literacy skills at the library for building digital scholarship services
Deborah Grbac

Abstract:

Since 2017, thanks Professors’ suggestions at the Faculty of Political Science, for which I’ve been an educator in Information Literacy courses since 2011, I started to develop my knowledge in text analysis and to stay in touch with the JSTOR Labs at Ithaka on text analysis common interests.

What I was learning was immediately integrated into my Information literacy courses and, since 2020, my knowledge has further developed thanks to my participation, as a beta tester, in the creation of what became a service for teaching, learning and performing text-analysis, produced by JSTOR Labs and called Constellate.

The introduction of discovery tools reading the OPAC underlined, in my opinion, the necessity to give the catalogue users knowledge about bibliographic data intended as data (data literacy) and how search engines index contents using textual data (Information extraction) for Information retrieval purposes. The main issue was to explain how information extraction techniques worked to enable a critical assessment of proposed results.

Constellate, with its unique pedagogy package, was the tool to make the shift from theory to practice, from already settled tools (search engine, text analysis software), to creating customized ones, by learning the empowering knowledge of programming in Phyton to perform the analysis needed.

In 2021 I taught my first course in text analysis, and in 2023 I swapped my information literacy courses for introduction to text analysis thanks to the Constellate subscription. Not only did students and professors, who hosted my classes, appreciate it, but with Constellate I could also address linguistics students interested in text analysis applications to other disciplines as a practical tool.

Moreover, teaching students gained me professors‘ and researchers’ interests that addressed me to discover what text analysis could give to their research methodology, offering new ways, by the data science approach, of tackling a research topic and scaffolding hypothesis by data. Skills that are becoming increasingly important facing the introduction of Artificial Intelligence in research.

The challenge today is to keep ensuring the same level of accuracy and knowledge that the Constellate pedagogy package did, by moving to some local service proposal. The disruption of Constellate, next July 2025, will be an occasion to translate locally the knowledge acquired and further adapt it to local needs.

This issue will be to be able to meet users’ needs, the Faculty of Political Science research methodology ones and the linguists’ ones in applications, preserving Constellate pedagogical approach.

Open access and AI: what power do authors and their institutions have?
Dave Hansen

Abstract:

Open access and AI: what power do authors and their institutions have?  As artificial intelligence systems increasingly rely on publicly accessible content for training data, open access publishing presents both opportunities and challenges for authors and institutions. Who controls how openly shared scholarship is used in AI development? What rights do authors retain over their work in an era of large-scale data mining? And how can institutions ensure that their open access policies align with ethical and legal considerations surrounding AI? This session will explore the intersection of open access and AI, examining the power authors and institutions hold over the use of their work. We will discuss licensing strategies, institutional policies, and emerging legal frameworks that shape the ways AI systems interact with scholarly content. Special attention will be given to the differences in legal approaches worldwide—such as the EU’s approach to text and data mining under the CDSM and the AI Act, compared to the U.S.’s fair use doctrine. Participants will gain insight into how they can navigate these complexities, advocate for responsible AI use, and shape policies that balance open knowledge sharing with author rights.

Open Educational Resources: A Nordic Perspective
Solveig Sandal Johnsen

Abstract:

LearningLib is a shared digital platform for Research and Educational Libraries, aimed at the development, storage, dissemination, and sharing of e-learning objects related to library and information science. The LearningLib collaboration aligns with UNESCO’s definition of Open Educational Resources (OER).

The platform has existed for 10 years and has evolved over the years to meet new pedagogical and technical requirements, as well as to incorporate updated design features. Therefore, it serves as an excellent resource for sharing and reusing learning objects with faculty and students in medium-length higher education and higher education.

Behind LearningLib.org is a consortium of Nordic institutions dedicated to the ongoing development of the platform. The goal is to create an online community among libraries, focusing on the development of teaching and learning materials for our researchers and students. This way of organizing a library specific OER proved to be very effective and valuable for the participating libraries. We would like to spread the word even more, since the resource and the organization behind could be of interest for a broader circle of libraries.

With LearningLib.org, we have a “display window” featuring valuable resources such as quizzes on copyright, videos on how to search for legal documents, steps for conducting a systematic review, a paper fortune teller about Generative AI, and much more. All resources are technically built using WordPress or H5P, making them appealing to the end user. The platform also offers an easy-to-use interface, and as part of the consortium, a dedicated group of information specialists focuses on creating valuable materials.

Open Educational Resources in libraries are not a new concept. With LearningLib.org, we aim to emphasize sharing and collaboration while thinking broadly about creating learning resources and sharing them under a Creative Commons license. However, how can we further advance this agenda in Research Libraries?

Questions for Discussion:

• We have an open platform for sharing, reuse, and learning—how can we encourage information specialists to utilize it more in their daily work?
• How can we better reward this type of work? Is it a responsibility for library leaders or the research community at large?

Press play, press on: Creating videos and synthesizing success
Emily Kingsland

Abstract:

Background
This short presentation will be delivered by an academic subject librarian at a major public research institution. The librarian created a series of instructional video tutorials aimed at graduate students on how to conduct systematic and scoping reviews. The video series was created in 2019 and gained traction among other social sciences, economics, and business librarians at the university.  However, the series requires updates to reflect institutional changes, such as new access to knowledge synthesis software Covidence, and to ensure all content remains accurate and relevant. The librarian will attend the Evidence Synthesis Institute of Canada in early April 2025, and following this, will create a new, updated video series. The updated series will be freely available, offering attendees an immediately applicable resource to support their research and teaching—especially useful for subject librarians, information professionals, graduate students, and early-career researchers.

Evidence synthesis in economics and business librarianship
Systematic and scoping reviews are increasingly valuable in disciplines like economics, management, and finance—particularly in fields emphasizing policy, meta-analyses, and data-driven decision-making. Systematic approaches to literature reviews can enhance evidence-based policymaking, market analysis, and decision-making research.

Video-based instruction as a scalable solution The use of a dedicated, publicly available video tutorial series represents an innovative, scalable approach to research support. Rather than relying solely on one-on-one consultations or in-person workshops, the librarian leverages asynchronous instructional design, expanding their reach to both local and global audiences.

Sustainable and adaptive support
The presentation emphasizes sustainability in librarian and information professional workload. By investing upfront in high-quality, reusable video content, the librarian minimizes repetitive instruction, freeing up time for deeper research consultations and other high-impact services.

Enhanced collaboration opportunities
Understanding the role librarians and information professionals play in knowledge synthesis can encourage researchers to collaborate more deeply with their library professionals, streamlining research processes and improving the quality of knowledge syntheses.

The Role of the Subject Library in Driving AI Transformation at the Economics and Management Faculty of Technische Universität Berlin
Franziska Klatt

Abstract:

The Economics & Management Library at Technische Universität Berlin has become the first public institution in Germany to initiate the acquisition of ChatGPT Edu licenses. The target audiences include researchers, educators, and students from Faculty VII, Economics and Management. The initiative stemmed from a retreat of the departmental heads, where Dr. Franziska Klatt, Head of the Teaching Library, introduced various AI tools. Recognizing that university-wide licenses would not be available in the near term, the faculty decided to advance the introduction of AI licenses as a pilot project and sought the library’s support.

The contribution will explore the role the library plays in the faculty’s AI transformation process and the tasks it undertakes in this context. This involvement strengthens the library’s role as a central partner in research and teaching. Researchers and faculty administration highly appreciate this support, as they often lack the time to keep up with the dynamic developments in AI and to facilitate internal exchange within the faculty.

This contribution offers valuable insights for the audience by demonstrating how AI tools and AI literacy programs can be implemented at the faculty level, highlighting the library’s role in supporting the AI transformation process. It provides a compelling approach for universities that lack campus-wide access to such tools.

Navigating the AI-Driven Metadata Landscape: A Human-Centered Approach
Ying-Hsang Liu

Abstract:

This presentation explores the emerging opportunities and challenges of utilizing artificial intelligence (AI) for metadata creation and management, providing valuable insights for information professionals in Economics and Business Studies. Drawing on findings from „The Survey on Metadata and AI“ by the Metadata and AI task group of the DCMI Education Committee, it offers a timely analysis of current perceptions and practices surrounding AI in metadata.

Conducted in October and November 2024, this survey has gathered responses from 295 library and information professionals, with significant representation from those specializing in Organization and Access (44.5%) and Digital and Technology Services (13.1%). The respondent pool is diverse, with the highest participation from China (28.2%) and the United States (21.7%). As data collection continues, the presentation will provide up-to-date findings and emerging trends relevant to the evolving impact of AI on metadata practices within library and information services.

Key findings from the survey reveal a balanced perspective on AI’s potential. While there is enthusiasm for AI’s capacity to enhance metadata processes, significant implementation challenges are also highlighted. Attendees will gain insights into several key areas:

• AI’s Potential to Transform Metadata Practices: The presentation will demonstrate how professionals view AI as a powerful tool for tasks like metadata enrichment, error identification, and inconsistency resolution, leading to more interconnected and accurate records.
• Human Oversight and Ethical Considerations: It will address concerns about transparency, potential biases in AI training data, and the importance of maintaining human judgment in metadata management, especially for nuanced tasks requiring cultural sensitivity.
• Framework for a Human-Centered Approach: Building on survey findings, the presentation will advocate for a balanced approach that integrates AI tools while retaining human oversight. Strategies will be emphasized to ensure accuracy, relevance, and cultural sensitivity of metadata, mitigate biases, and uphold metadata standards for end-users.

Benefits for the Audience:

• Understanding the Latest Trends in AI and Metadata: The presentation provides valuable insights into how AI is perceived and implemented in metadata practices, equipping attendees with knowledge to navigate the evolving landscape of information management.
• Addressing Practical Challenges and Opportunities: By exploring both the benefits and challenges of AI, it helps information professionals in Economics and Business Studies to strategically approach AI implementation, maximizing its potential while mitigating risks.

This presentation is designed to engage information professionals, providing them with the tools and understanding needed to effectively use AI in metadata management.

Evaluating the impact of AI on information literacy and critical thinking in academic libraries
Kamogelo Mphuthi, Clara Ngobeni, Rebecca Bapela

Abstract:

Introduction
This study aims to explore how AI affects critical thinking and information literacy in academic libraries and higher education. Critical thinking, defined as the ability to evaluate information, challenge assumptions, and generate innovative solutions, is fundamental in business education (Essien et al, 2024). Recent studies address concerns that graduates may lack these critical thinking skills. Over the past 20 years, library services have also undergone significant change, and artificial intelligence has unexpectedly contributed to this evolution (Jha, 2023).

Statement of the research problem
This study seeks to evaluate the challenges and opportunities posed by AI, ensuring libraries remain proactive in fostering these essential skills in an AI-driven era. The objectives of this study are therefore:

• To assess whether the use of AI risks diminishing information literacy skills such as critical thinking, evaluating information, and finding credible sources.
• To evaluate the advantages and disadvantages of integrating AI in academic libraries and its role in enhancing or undermining information literacy education.

Methodology
This study utilized desk research as its primary method, reviewing 13 journal articles relevant to the impact of AI on information literacy and critical thinking in HE and academic libraries. Six articles focused on critical thinking and information literacy, two on integrating AI in libraries, three on the impact of AI in HE and libraries, and one on reshaping education in the AI era. One article was deemed irrelevant due to its focus on AI and critical thinking in middle school.

Findings (preliminary)
The findings for this research at the time of writing this abstract are preliminary (review of four journal articles have been conducted). Currently the following findings are emanating:

• AI integration could improve both basic and advanced critical thinking skills, as outlined in Bloom’s Taxonomy.
• Critical thinking remains multifaceted and influenced by factors beyond AI integration.
• AI text generators can reshape teaching strategies and enhance educational tools

Recommendations
Libraries should require users to validate AI outputs and educate them about the biases and limitations of AI in order to prevent a decline in critical thinking. To ensure that AI enhances rather than replaces human judgment, a balanced approach that combines librarian expertise for advanced critical thinking support with AI automation for routine tasks is used. Frequent evaluations of AI’s effects on user skills can support libraries in keeping an emphasis on lifelong learning and intellectual engagement.

Reimagining University Libraries: A Hybrid Model for Small-Medium Institutions Combining Tradition, Technology, and Innovation
Silvete Osmani + (Astrit Ramadani)

Abstract:

Considering developments in technology and digitization, university libraries are increasingly under pressure to modernize in order to meet the evolving needs of students, lecturers and researchers, while maintaining traditional values such as knowledge preservation, accessibility and community support. This challenge is particularly pronounced in our region for small or medium-sized universities, such as SEEU, where limited resources and budget constraints make it difficult to keep up with technological advances. For these libraries, the adoption of a hybrid model which will combine these advanced technologies such as Artificial Intelligence (AI), Augmented Reality (AR) as well as mobile applications with traditional physical collections represents an innovative way to overcome this gap between progress digital and traditional. Through this paper we will explore the potential benefits and challenges of this hybrid approach, aiming to create a more dynamic, inclusive and engaging learning environment.

This proposed hybrid model will integrate both digital and physical resources and provide easy access to online databases, e-books and virtual learning tools, while still maintaining the traditional print collections that many users preferred by both students and academic staff. Incorporating technologies such as AI for personalized recommendations, AR for interactive learning experiences, and mobile apps for on-the-go access to library services, the model seeks to enhance the educational experience.

This proposal-paper describes in detail the implementation of the hybrid library model, focusing on the infrastructure, staff training, and technology investments required for successful integration. Additionally, it addresses challenges such as ensuring equitable access to resources, overcoming resistance to change, and effectively balancing digital and physical components.

Additionally, this paper discusses the strategies needed to sustain this model over the long term, including ongoing feedback from library users, regular updates to technology tools, and fostering partnerships with academic departments and external technology providers.

By presenting a practical solution and identifying possible obstacles, this paper offers a model for other small and medium-sized universities to modernize their libraries while still maintaining their main mission to encourage the engagement of scholars, researchers and lifelong learning.

In conclusion, this hybrid model for libraries combining tradition and technology is proposed as a sustainable and future-proof approach that meets the diverse needs of academic communities.

The Transformative Role of Artificial Intelligence in Libraries and Archives: An assessment on Opportunities, Challenges and Strategic Solutions
Abdulhalik Pinar

Abstract:

Artificial Intelligence (AI) has transformed library and archive organisations around the world in recent years, offering a wide range of opportunities to increase efficiency, improve accessibility and preserve cultural heritage. This paper analyses findings from 75 case studies in the UK and other countries, focusing on the aims, outcomes and challenges of applying AI in these fields. The findings show that AI tools such as BERT, Transcriber, OCR engines and machine learning frameworks are widely used to automate complex processes such as metadata generation, subject indexing and text recognition.

The results of the case studies emphasise the transformative impact of AI. As a result of this transformation, organisations have achieved faster processing speeds, higher cost efficiency and increased user interaction. AI has played an important role in democratising access to historical, multilingual and audiovisual materials, fostering interdisciplinary research and enabling new forms of cultural discovery. For example, language models such as Newspaper Navigator and Swedish-specific KB-BERT have enriched access to archives and digital collections, while speech-to-speech translation systems such as VoxRex have increased the availability of audiovisual resources.

However, as with any new technology, AI has brought with it various challenges. Data biases, variability in OCR quality, ethics and limitations in training data are among the major barriers. Financial and infrastructural constraints, coupled with staff fears of job loss and knowledge gaps, make AI adoption even more difficult. Case studies, particularly from developing countries, emphasise the need for strategic investments in funding, training and infrastructure to overcome these barriers. Ethical concerns, such as algorithmic biases and decontextualisation, are also critical, particularly for sensitive cultural and historical artefacts.

This study addresses strategic solutions proposed to mitigate the challenges identified in the case studies reviewed and maximise the benefits of AI. Suggestions such as fostering interdisciplinary collaboration, designing scalable and adaptable AI workflows, and integrating human expertise into AI systems to balance automation with inclusivity and ethical oversight are presented. By synthesising global perspectives, this research provides actionable insights into how libraries and archives can leverage AI for cultural heritage preservation and enhanced research capabilities. Properly implemented AI applications can revolutionise the role of libraries and archives in the digital age, ensuring their sustainability and relevance for future generations.

Quo Vadis Transformative Agreements?
W. Benedikt Schmal

Abstract:

Transformative Agreements between research institutions and academic publishers were meant as a transitory vehicle towards a fully gold open access future. However, these agreements seem quite sticky as they tend to be prolonged instead of replaced. Furthermore, the design of these contracts incentivizes the publishers to attract more and more papers as they get paid per article. Altogether, this raises concerns about a financially sustainable open access transition and leaves many open questions about how to proceed for academic institutions in times of tightening budgets.

Neither a Luddite nor a Lemming: Librarians as the Lorax in our GenAI Obsessed World?
Corey Seeman

Abstract:

The rapid adoption of Generative AI by nearly every industry has been nothing short of remarkable. In just a few years, GenAI has been a driving force in industry, education, news and information. Driving in large by a vague understanding of the potentials in this technology, there is a bonafide arms race to be the leaders and the best. In the realm of business education, this is happening on our campuses, and with our publishers and with our vendors. Librarians and information professionals do not have the opportunity to ignore GeenAI as it directly impacts our work and our community in the race to harness this technology.

There is certainly a great deal that we benefit from artificial intelligence. Enhancements like predictive text, translations on the fly, GPS systems and ease of analyzing data are all tools we and our patrons use. These elements of artificial intelligence are set up to augment and assist our endeavors. But GenAI is different. GenAI appears designed to replace our work – and that has been a driving force in its remarkable growth over the past two years. We are expected to either be a lemming or a luddite when approaching this new technology. But in this context – we should strive to be Dr. Suess’s character The Lorax and try to get people to understand what the costs truly are and what this reality truly is. This fable teaches us that our greed can lead to the destruction of our environment. This is possibly a role that librarians need to play here. While we cannot change the direction of the academy, our role is to get people to understand the impact of these technologies.

In this short presentation, I will share what we are seeing from students and faculty and publishers as it relates to Generative AI and how we can nudge these community members to more acceptable and licensed use of our content. We will use examples from the Ross School of Business (University of Michigan) and how we are helping faculty and students understand the true dynamics of using GenAI tools with our licensed data.

Beyond ChatGPT: Academic Libraries‘ Multi-Level Approaches to Critical Thinking
Lukas Tschopp

Abstract:

The emergence of large language models such as ChatGPT is accelerating a trend that began with social media: the rapid generation and dissemination of information. While these models excel at writing, structuring concepts and developing drafts, they can provide plausible but incorrect information. The tendency of students to rely on such AI-generated answers without critical evaluation raises concerns. These developments remind us of the fundamental importance of critical thinking skills in dealing with information.

This presentation explores how academic libraries are promoting critical thinking skills in relation to ChatGPT. Although focused on undergraduate education, the approaches identified show potential for supporting critical engagement with AI tools across the academic community, including researchers, faculties, and teachers. The interventions operate at three different levels – individual, classroom and institutional – and aim to develop an AI mindset. Based on a literature review and interviews with stakeholders from Singapore Management University libraries and other academic institutions in Singapore, the presentation highlights specific interventions: At the individual level, librarians use targeted questions during one-on-one consultations to encourage precision and reflection in research queries. At the classroom level, libraries offer workshops that integrate the Paul Elder Framework, use problem-based learning approaches, and develop self-paced courses. At the institutional level, initiatives such as interdisciplinary hackathons can foster critical thinking through carefully designed challenges that require creative problem solving and critical evaluation of AI tools. These multi-level interventions aim to cultivate a new way of thinking that enables students to critically engage with AI technologies.

A key challenge highlighted in the presentation is that library staff themselves are part of this transformation. They need to build knowledge and gain practical experience with large language models in order to engage effectively at all levels. This parallel process of learning and teaching is crucial for academic libraries to prepare students for a professional world where AI tools are increasingly prevalent.

Integrating Artificial Intelligence into Library Services for Research Support: Challenges, Opportunities, and Strategies at the University of Rwanda
Berthilde Uwamwezi

Abstract:

The rapid evolution of artificial intelligence (AI) is transforming higher education, particularly in academic support services, with the potential to enhance research efficiency, improve personalized learning, and expand resource accessibility. However, in developing countries like Rwanda, AI adoption in academic environments remains limited due to several challenges, such as insufficient infrastructure, inadequate training, and digital literacy disparities. This study assesses the effectiveness of research support services provided by libraries, with a focus on the integration of artificial intelligence (AI) into these services. Using a mixed-methods approach, the study gathered data through online surveys, with library staff, faculty, and students, and document analysis of institutional policies and resources. Participants included undergraduate and Masters students and teaching staff in the field of Business and Economics as well as library staff. The preliminary findings revealed trends related to the availability of AI tools and the students‘ familiarity with them, deeper insights into the experiences and perceptions of key stakeholders. Preliminary results indicate a significant interest in AI integration, although concerns about infrastructure limitations and training needs persist.They reveal the barriers to AI integration, such as limited access to AI tools, lack of technical skills among library staff and students, and insufficient training programs. These challenges are further compounded by the absence of evaluations of existing research support services, making it difficult to identify gaps and implement solutions. Despite these challenges, the study reveals a strong interest among students and staff in leveraging AI to improve research processes, particularly in managing large datasets and enhancing productivity. To address these issues, the study recommends several strategies to optimize research support services at the University of Rwanda. These include investing in AI infrastructure, launching capacity-building initiatives for both students and staff, and fostering an innovation-driven institutional culture. It is essential to bridge the technological and skill gaps to ensure inclusivity, accessibility, and efficiency in the use of AI tools in research support services. Ultimately, this study provides actionable insights for other institutions in similar resource-constrained settings, offering a roadmap for the successful integration of AI into academic support systems. By addressing the identified barriers and leveraging AI’s potential, the University of Rwanda can enhance the quality of research and academic outcomes for its students, particularly in data-intensive fields like Business and Economics.

Fostering Open Educational Resources Through FAIR Principles in Danish University Libraries
Lorna Wildgaard

Abstract:

Over the past two years, we have explored the opportunities and challenges of creating Open Educational Resources (OER) within the context of Danish university libraries. Through workshops, storytelling sessions, and surveys, we examined staff awareness of and engagement with the OER platform LearningLib across the Royal Danish Library network, including Copenhagen University Library (KUB), Roskilde University Library (RUB), and Aarhus University Library (AUL).

Our aim is to align with the current university strategy for innovation in teaching and learning by producing a guide and supporting professional development for implementing FAIRbyDesign workflows in OER. These workflows integrate the FAIR (Findable, Accessible, Interoperable, and Reusable) principles into the creation of educational materials and outreach initiatives about Open Science. By providing resources that are targeted at researchers and openly accessible as OER, we aim to build a FAIR culture that promotes the recognition, reuse, and sharing of learning materials.

Observations during the workshops focused on how participants interacted with LearningLib as an OER platform, both in terms of their processes for developing educational resources and their responses to the workshop’s format, design, and content. Insights were drawn from moments of frustration, such as challenges encountered while using the platform, as well as from “aha!” moments when participants grasped new concepts or gained skills. These interactions provided critical data on the effectiveness of the platform, content of the guide and structure of future workshops.

Key findings revealed cultural challenges in sharing and disseminating educational materials, highlighting barriers to creating a sustainable FAIR culture. These include hesitations around intellectual property, concerns over the quality and reusability of shared materials, and varying levels of digital literacy.

Our research underscores the importance of fostering institutional support and competence development to overcome these challenges and leverage OER as a tool for promoting Open Science. This work contributes to the growing field of Open Education by offering practical insights and actionable strategies for integrating FAIRbyDesign principles into the development and dissemination of learning resources within academic institutions.

Artificial Intelligence in Academic Writing. University Policy and the Supporting Role of the Library
Agnieszka Wolanska

Abstract:

The presentation aims to demonstrate the role of artificial intelligence (AI) tools in the process of student academic writing and the policy implemented by Coventry University in this regard. It will discuss examples of AI tools that, when used appropriately, are acceptable as aids in the writing process, as well as those outlined in the University’s regulations as not recommended and leading to violations of academic ethics. Additionally, the presentation will highlight the Library’s role in implementing the guidelines established by the University and in providing students with information about them.

Tables are tricky. Testing Text Encoding Initiative (TEI) Guidelines for FAIR upcycling of digitised historical statistics
Gabi Wuethrich

Abstract:

Quantitative social sciences such as economics, finance, and business administration, as well as memory institutions such as archives and libraries should consciously consider how to sustainably preserve their flood of digital data for future generations. This paper explores the challenges and progress made in digitizing complex historical statistical tables in the context of a project on 1918 pandemic mortality data in Zurich. The basic idea of the data management assignment was to prepare tables of historical health statistics in a sustainable way in order to make them reusable, interoperable, and machine-readable in a platform-independent way – i.e. in a way that our research community can use the data for their analyses.

The project tested XML structures based on the Text Encoding Initiative (TEI),, a standardized XML vocabulary for text encoding, to process these historical tables. The data was first captured semi-automatically OCRed into Excel files and then converted into TEI-compliant XML documents. These structured XML outputs are designed for use with statistical tools commonly used in economic and business history research. However, OCR’s limitations in handling tabular data required significant manual corrections, highlighting the challenges posed by structured tables compared to narrative text. AI tools such as ChatGPT 4.0 and Microsoft Copilot were also tested but produced error-prone results and proved insufficient for accurate table processing.

In TEI, tables seem to have had a shadowy existence so far – or, as TEI pioneer Lou Burnard remarked: “Tables are tricky”. Yet, TEI principles offer ways of conceptualizing the organization of such data and ensuring traceable editing, particularly for serial statistics as demonstrated by the successful application by a project on early-modern Basle account books. In addition, the clearly structured textual preparation of the TEI could provide a training basis for improving the quality of AI-based table text recognition.

To overcome OCR and AI limitations, the project adopts workflows from economic history research by Aurelius Noble, Melissa Dell, and Mengye Zhao, which emphasize page and text segmentation to improve OCR accuracy. By testing these workflows on the digitized pandemic mortality tables, the project aims to create a FAIR (Findable, Accessible, Interoperable, Reusable) process that can be adapted to other digitization projects within academic and GLAM (Galleries, Libraries, Archives, Museums) settings. Ultimately, this approach underscores the value of FAIR encoding for improving data accessibility and AI training, promoting sustainable, machine-readable data for research and data preservation in economics and business research.