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This paper reviews literature on the application of intelligent systems in the libraries with a special issue on the ES/AI and Robot. Also, it introduces the potential of libraries to use intelligent systems, especially ES/AI and robots.

Descriptive and content review methods are applied, and the researchers critically reviewed the articles related to library ESs and robots from Web of Science as a general database and Emerald as a specific database in library and information science from 2007–2017. Four scopes considered to classify the articles as technology, service, user and resource. It is found that published researches on the intelligent systems have contributed to many librarian purposes like library technical services like the organization of information resources, storage and retrieval of information resources, library public services as reference services, information desk and other purposes.

A review of the previous studies shows that ESs are a useable intelligent system in library and information science that mimic librarian expert’s behaviors to support decision making and management. Also, it is shown that the current information systems have a high potential to be improved by integration with AI technologies. In this researches, librarian robots mostly designed for detection and replacing books on the shelf. Improving the technology of gripping, localizing and human-robot interaction are the main concern in recent librarian robot research. Our conclusion is that we need to develop research in the area of smart resources.

This study has a new approach to the literature review in this area. We compared the published papers in the field of ES/AI and robot and library from two databases, general and specific.

The purpose of this paper was to identify whether artificial intelligence (AI) products can possess human rights, how to define their rights and obligations and what ethical standards they should follow. In this study, the human rights ethical dilemma encountered in the application and development of AI technology has been focused on and analyzed in detail in the light of the existing research status of AI ethics.

In this study, first of all, the development and application of AI technology, as well as the concept and characteristics of human rights ethics, are introduced. Second, the human rights ethics of AI technology are introduced in detail, including the human rights endowment of AI machines, the fault liability of AI machines and the moral orientation of AI machines. Finally, the approaches to human rights ethics are proposed to ensure that AI technology serves human beings. Every link of its research, production and application should be strictly managed and supervised.

The results show that the research in this study can provide help for the related problems encountered in AI practice. Intelligent library integrates human rights protection organically so that readers or users can experience more intimate service in this system. It is a kind of library operation mode with more efficient and convenient characteristics, which is based on digital, networked and intelligent information science. It aims at using the greenest way and digital means to realize the reading and research of human rights protection literature in the literature analysis method.

Intelligent library is the future development mode of new libraries, which can realize broad interconnection and sharing. It is people-oriented and can make intelligent management and service and establish the importance of the principle of human rights protection and the specific idea of the principle. The development of science and technology brings not only convenience to people's social life but also questions to be thought. People should reduce its potential harm, so as to make AI technology continue to benefit humankind.

Education is increasingly using Intelligent Tutoring Systems (ITS), both for modelling instructional and teaching strategies and for enhancing educational programs. The first part of the paper introduces the basic structure of an ITS as well as common problems being experienced within the ITS community. The second part describes WITNeSS ‐ an original hybrid intelligent system using Fuzzy‐Neural‐GA techniques for optimising the presentation of learning material to a student. The original work in this paper is related to the concept of a “virtual student”. This student model, modelled using fuzzy technologies, will be useful for any ITS, providing it with an optimal learning strategy for fitting the ITS itself to the unique needs of each individual student. In the third part, experiments focus on problems developing a “virtual student” model, which simulates, in a rudimentary way, human learning behaviour. Part four finishes with concluding remarks.

This paper aims to present a comprehensive overview of the patterns and trends of publications on artificial intelligence (AI) in personalised learning. It addresses the need to investigate the intellectual structure and development of this area in view of the growing amount of related research and practices.

A bibliometric analysis was conducted to cover publications on AI in personalised learning published from 2000 to 2022, including a total of 1,005 publications collected from the Web of Science and Scopus. The patterns and trends in terms of sources of publications, intellectual structure and major topics were analysed.

Research on AI in personalised learning has been widely published in various sources. The intellectual bases of related work were mostly on studies on the application of AI technologies in education and personalised learning. The relevant research covered mainly AI technologies and techniques, as well as the design and development of AI systems to support personalised learning. The emerging topics have addressed areas such as big data, learning analytics and deep learning.

This study depicted the research hotspots of personalisation in learning with the support of AI and illustrated the evolution and emerging trends in the field. The results highlight its latest developments and the need for future work on diverse means to support personalised learning with AI, the pedagogical issues, as well as teachers’ roles and teaching strategies.

Interactions are fundamental for successful relationships and stable cooperation in a business-to-business market. The main assumption in research on interactions, so obvious that usually not stated by researchers, is that they are set between humans. The development of artificial intelligence forces the re-examination of this assumption. This paper aims to conceptualize business virtual assistants (BVAs), a type of intelligent agent, as either a boundary object or an actor within business interactions.

Reference is made to the literature on business interactions, boundary objects and identity attribution to problematize the process of interpretation through which BVA obtains an identity. The ARA model and the model of interaction process is used to create a theoretical framework.

This paper contributes to the literature on business interactions, and to the core of the IMP discussion, in three aspects. The first provides a framework to understand the phenomenon of an artificial entity as an interlocutor in business interactions. While doing that a new type of entity, BVA, is introduced. The second contribution is the exploration and augmentation of the concept of a business actor. The third calls attention to BVA as a boundary object. These issues are seen as essential to move forward the discussion about the meaning of business interaction in the near future.

This paper conceptualizes the presence of a new entity – BVA – in the business landscape.

This study, a theoretical article, aims to introduce new institutionalism as a framework through which business and management researchers can explore the significance of artificial intelligence (AI) in organizations. Although the new institutional theory is a fully established research program, the neo-institutional literature on AI is almost non-existent. There is, therefore, a need to develop a deeper understanding of AI as both the product of institutional forces and as an institutional force in its own right.

The authors follow the top-down approach. Accordingly, the authors first briefly describe the new institutionalism, trace its historical development and introduce its fundamental concepts: institutional legitimacy, environment and isomorphism. Then, the authors use those as the basis for the queries to perform a scoping review on the institutional role of AI in organizations.

The findings reveal that a comprehensive theory on AI is largely absent from business and management literature. The new institutionalism is only one of many possible theoretical perspectives (both contextually novel and insightful) from which researchers can study AI in organizational settings.

The authors use the insights from new institutionalism to illustrate how a particular social theory can fit into the larger theoretical framework for AI in organizations. The authors also formulate four broad research questions to guide researchers interested in studying the institutional significance of AI. Finally, the authors include a section providing concrete examples of how to study AI-related institutional dynamics in business and management.

The purpose of the study was to investigate factors promoting innovation and application of internet of things in academic and research information organizations.

Quantitative research design involved survey of selected academic and research information organizations in public and private chartered institutions. Information professionals, digital content managers, information systems and technologists that normally consume big data and technological resources were involved in the process of data collection using structured questionnaire and content analysis. Information organizations and information practitioners were selected from public and private academic and research institutions.

Innovation of internet of things has increasingly transformed and changed academic and research information organizations as the source of knowledge in addition to expanding access to education, data, information and communication anywhere anytime through hyperconnectivity and networking. Internet of things technologies such as mobile of things, web of things, digital information systems and personal devices are widely applied by digital natives in academic and research information organizations. Mobilization platform and devices is the single biggest provider of data, information and knowledge in academic and research organizations. Modern trends in education and knowledge practices in academic institutions and information organizations depends upon internet of things, digital repositories, electronic books and journals, social media interfaces, multimedia applications, information portal hubs and interactive websites, although challenges regarding inadequate information communication technology infrastructure and social computing facilities still persist.

Information organizations in public and private chartered academic and research institutions were adopted in the study. Respondents handling and supporting information management, planning and decision-making provided the necessary data. Information professionals, digital content managers, information systems and technologists are proactively involved in data and information analytics.

Academic and research information organizations are powerhouses that provide knowledge to support research, teaching and learning for sustainable development and the betterment of humanity and society. Innovation of internet of things and associated technologies provides practical aspects of attaining sustainable information development practices in the contemporary knowledge society. Internet of things technologies, principles of economies of scale and investment and customer needs entail that information organizations and practitioners should provide appropriate and smart systems and solutions.

Modern academic and research information organizations have the social corporate responsibility to offer technological innovations to heighten access to knowledge and learning in academic and research institutions. Economically, innovation and application of internet of things provide unlimited access to big data and information in organizations all the time anywhere anytime.

Data management is a growing phenomenon that information practitioners need to fully understand in the digital economies. Information professionals need to embrace and appreciate innovation and application of internet of things technologies whose role in sustainable development practices is critical in academic and research organizations.

Isometric feature mapping (Isomap) is a very popular manifold learning method and is widely used in dimensionality reduction and data visualization. The most time-consuming step in Isomap is to compute the shortest paths between all pairs of data points based on a neighbourhood graph. The classical Isomap (C-Isomap) is very slow, due to the use of Floyd’s algorithm to compute the shortest paths. The purpose of this paper is to speed up Isomap.

Through theoretical analysis, it is found that the neighbourhood graph in Isomap is sparse. In this case, the Dijkstra’s algorithm with Fibonacci heap (Fib-Dij) is faster than Floyd’s algorithm. In this paper, an improved Isomap method based on Fib-Dij is proposed. By using Fib-Dij to replace Floyd’s algorithm, an improved Isomap method is presented in this paper.

Using the S-curve, the Swiss-roll, the Frey face database, the mixed national institute of standards and technology database of handwritten digits and a face image database, the performance of the proposed method is compared with C-Isomap, showing the consistency with C-Isomap and marked improvements in terms of the high speed. Simulations also demonstrate that Fib-Dij reduces the computation time of the shortest paths from O(N³) to O(N²lgN).

Due to the limitations of the computer, the sizes of the data sets in this paper are all smaller than 3,000. Therefore, researchers are encouraged to test the proposed algorithm on larger data sets.

The new method based on Fib-Dij can greatly improve the speed of Isomap.

Studies showed that a proactive delivery system employing innovative artificial intelligence (AI) in urban services might perform better. This has become an important national policy for many countries. Thus, this study aims to explore the influence of AI in urban services in Malaysia.

Official documents such as Structure Plan and Government Transformation Programme Policy Document covering various levels of cities in Malaysia, articles related to urban studies mostly written by researchers regarding urban growth in Malaysia and the Urban Development Bulletin from the Federal Department of Town and Country Planning from 1957 to date were reviewed and analysed.

The findings show that the influence of AI in urban services has long existed and been carefully planned by local authorities since colonial times. The development of global digital technology influences the upgrading of AI in urban services in Malaysia. Also, the success of AI in these municipal services is influenced by the rate of information technology literacy among the urban population. These developments have led to the definition of a conceptual city.

This paper's findings and conclusion were based on reviewed literature but did not compromise the strength of this paper. Thus, as part of the implications for future research, mixed-methods research design has been suggested.

As part of the implications, this article intends to promote AI in urban services in Malaysia and other developing countries with similar urban services challenges.

This paper encourages AI applications in urban services because it enhances service delivery performance. This intends to key stakeholders to promote AI via policies across Malaysia's urban services as part of the study implications.