Views of Academic Library Directors on Artificial Intelligence: A Representative Survey in Hungary

Winkler, Bea; Kiszl, Péter

doi:10.1080/13614533.2021.1930076

Cited by 17 publications

(6 citation statements)

References 17 publications

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“…Contrarily, the robots will complement the librarian's efforts. The survey by Winkler and Kiszl (2021) shows that AI is an additional opportunity for academic libraries instead of a threat. It could be helpful in all parts of the library procedure.…”

Section: Resultsmentioning

confidence: 99%

Artificial intelligence (AI) library services innovative conceptual framework for the digital transformation of university education

Okunlaya

Abdullah

Alias

2022

LHT

103

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PurposeArtificial intelligence (AI) is one of the latest digital transformation (DT) technological trends the university library can use to provide library users with alternative educational services. AI can foster intelligent decisions for retrieving and sharing information for learning and research. However, extant literature confirms a low adoption rate by the university libraries in using AI to provide innovative alternative services, as this is missing in their strategic plan. The research develops (AI-LSICF) an artificial intelligence library services innovative conceptual framework to provide new insight into how AI technology can be used to deliver value-added innovative library services to achieve digital transformation. It will also encourage library and information professionals to adopt AI to complement effective service delivery.Design/methodology/approachThis study adopts a qualitative content analysis to investigate extant literature on how AI adoption fosters innovative services in various organisations. The study also used content analysis to generate possible solutions to aid AI service innovation and delivery in university libraries.FindingsThis study uses its findings to develop an Artificial Intelligence Library Services Innovative Conceptual Framework (AI-LSICF) by integrating AI applications and functions into the digital transformation framework elements and discussed using a service innovation framework.Research limitations/implicationsIn research, AI-LSICF helps increase an understanding of AI by presenting new insights into how the university library can leverage technology to actualise innovation in service provision to foster DT. This trail will be valuable to scholars and academics interested in addressing the application pathways of AI library service innovation, which is still under-explored in digital transformation.Practical implicationsIn practice, AI-LSICF could reform the information industry from its traditional brands into a more applied and resolutely customer-driven organisation. This reformation will awaken awareness of how librarians and information professionals can leverage technology to catch up with digital transformation in this age of the fourth industrial revolution.Social implicationsThe enlightenment of AI-LSICF will motivate library professionals to take advantage of AI's potential to enhance their current business model and achieve a unique competitive advantage within their community.Originality/valueAI-LSICF development serves as a revelation, motivating university libraries and information professionals to consider AI in their strategic plan to enable technology to support university education. This act will enable alternative service delivery in the face of unforeseen circumstances like technological disruption and the present global COVID-19 pandemic that requires non-physical interaction.

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Section: Resultsmentioning

confidence: 99%

Artificial intelligence (AI) library services innovative conceptual framework for the digital transformation of university education

Okunlaya

Abdullah

Alias

2022

LHT

103

View full text Add to dashboard Cite

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“…A research study by Arora et al (2020) highlighted the benefits of AI-based resource management systems in developing country libraries, noting improved accuracy in demand prediction, reduced maintenance costs and enhanced collection development practices. Another area identified by Winkler and Kiszl (2021) is that AI presents academic libraries with a supplementary opportunity rather than a perceived threat.…”

Section: Prospects Of Implementing Artificial Intelligence In Library...mentioning

confidence: 99%

“…Libraries need to invest in training programs and capacity-building initiatives to empower their staff with the necessary skills for successful AI implementation (Arora et al , 2020). A study by Winkler and Kiszl (2021) emphasized the importance of comprehensive training programs to bridge the skills gap and ensure the effective utilization of AI technologies in library services. The absence of research activities bridging the gap between AI and librarianship is identified as another factor contributing to the exclusion of AI from library services in developing countries (Arora et al , 2020).…”

Section: Challenges In Implementing Artificial Intelligence In Librar...mentioning

confidence: 99%

Implementing artificial intelligence in library services: a review of current prospects and challenges of developing countries

Barsha¹,

Munshi²

2023

LHTN

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Purpose Artificial intelligence (AI) is one of today’s rising technologies. AI is a commonly used technology in library services that have the potential to revolutionise the best offerings in the information age. With AI in libraries, users can explore the world of knowledge like never before with smart recommendations tailored to their needs. Overall, AI can enhance the library experience of both the users and library professionals with innovation and smart decisions. Hence, there is no doubt that AI and libraries have a close relationship; nonetheless, the usage and understanding of AI in library services continue to raise concerns, especially in the developing countries which this paper addresses. The purpose of this research paper is to review the current prospects and challenges of implementing AI in library services in developing countries. The primary objective of the study is to discern the pivotal predicaments and obstacles these nations face while implementing AI-based solutions and to propose pragmatic solutions. Design/methodology/approach The present study adopts a qualitative approach, using content analysis techniques to glean meaningful insights. An extensive review of the extant literature on the subject was conducted, which was meticulously analysed to furnish the findings of this study. The review is limited to English language sources, and searches were conducted using various online academic databases. Findings The review reveals that the prospects of implementing AI in library services in developing countries are significant, with potential benefits including improved access to information, increased efficiency and productivity and enhanced user experience. However, the review also identifies several challenges, including the lack of infrastructure and resources, the shortage of skilled personnel, the absence of data privacy regulations, digital divide and the high cost of implementing AI-based solutions. Practical implications The review suggests several practical solutions to overcome the challenges faced by developing countries in implementing AI in library services. These include partnerships between libraries and technology firms, investment in infrastructure and resources, training and capacity building for library staff and the development of regulatory frameworks to protect user data. Originality/value This research paper provides a comprehensive review of the prospects and challenges of implementing AI in library services in developing countries. The study is original in its focus on the perspectives of developing countries, their problems and obstacles. The study also provides practical recommendations that can be used by library managers, policymakers and technology firms to support the implementation of AI-based solutions in developing countries.

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“…The field of AI, which has recently been put into practice and is expanding, was once viewed as the future work problem. The good news is that librarians are becoming more aware of AI (Hervieux and Wheatley, 2021), and its usage is anticipated to expand (Ali et al, 2020;Winkler and Kiszl, 2022). Technology adoption decisions become more complex due to the range of available AI solutions and the need to select the most suitable one for specific library requirements.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Synchronizing innovation: unveiling the synergy of need-based and curiosity-based experimentation in AI technology adoption for libraries

Gupta,

Gupta

2023

LHTN

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Purpose In the context of libraries adopting artificial intelligence (AI) technology, this paper aims to demonstrate the synergy between two different yet complimentary frameworks, need-based experimentation (NBE) and curiosity-based experimentation (CBE). It looks at how these frameworks interact and operate together to promote technological innovation and innovation in libraries. Design/methodology/approach The authors’ extensive professional experience in the AI adoption and innovation of libraries is drew upon in this paper. The methodology encompasses empirical observations of various libraries engaging in digital innovations through experimentations with AI technology adoption practices. Using the frameworks of NBE and CB), these observations are examined to find patterns, relationships and mutual reinforcement between the two methods. The analysis of this study is built on the authors’ observations and real-world case studies. Findings The research reveals that NBE and CBE work together to provide libraries with all-encompassing adoption methods for AI technology. This study indicates a dynamic interaction between NBE and CBE that boosts libraries’ methods for adopting AI technology. NBE acts as a catalyst for CBE by raising awareness of specific library needs, prompting librarians to explore AI technologies aligned with those needs. This synergy empowers librarians to creatively experiment with technology solutions that directly address pressing library challenges. Conversely, CBE fuels NBE by promoting group learning among diverse team members and fostering individual motivation to tackle library needs collaboratively. As they explore AI technology out of personal curiosity, librarians make important contributions that enhance NBE. Originality/value The novel aspect of this study is the recognition of the complementarity between NBE and CBE frameworks, which suggests that libraries should view them as intertwined rather than two separate approaches. Focusing on both methodologies increases the culture of experimentation and improves the problem-solving abilities of librarians. Innovation is fueled by controlled experimentation and innate curiosity in an atmosphere that is fostered by the mutual influence of NBE and CBE. This synthesis offers libraries a comprehensive strategy for adopting AI technology, empowering them to manage the shifting environment and realize the revolutionary promise of AI technologies.

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Views of Academic Library Directors on Artificial Intelligence: A Representative Survey in Hungary

Cited by 17 publications

References 17 publications

Artificial intelligence (AI) library services innovative conceptual framework for the digital transformation of university education

Artificial intelligence (AI) library services innovative conceptual framework for the digital transformation of university education

Implementing artificial intelligence in library services: a review of current prospects and challenges of developing countries

Synchronizing innovation: unveiling the synergy of need-based and curiosity-based experimentation in AI technology adoption for libraries

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