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The purpose of this paper is to review and discuss Luciano Floridi’s 2019 book The Logic of Information: A Theory of Philosophy as Conceptual Design, the latest instalment in his philosophy of information (PI) tetralogy, particularly with respect to its implications for library and information studies (LIS).

Nine scholars with research interests in philosophy and LIS read and responded to the book, raising critical and heuristic questions in the spirit of scholarly dialogue. Floridi responded to these questions.

Floridi’s PI, including this latest publication, is of interest to LIS scholars, and much insight can be gained by exploring this connection. It seems also that LIS has the potential to contribute to PI’s further development in some respects.

Floridi’s PI work is technical philosophy for which many LIS scholars do not have the training or patience to engage with, yet doing so is rewarding. This suggests a role for translational work between philosophy and LIS.

The book symposium format, not yet seen in LIS, provides forum for sustained, multifaceted and generative dialogue around ideas.

Research into the interpretability and explainability of data analytics and artificial intelligence (AI) systems is on the rise. However, most recent studies either solely promote the benefits of explainability or criticize it due to its counterproductive effects. This study addresses this polarized space and aims to identify opposing effects of the explainability of AI and the tensions between them and propose how to manage this tension to optimize AI system performance and trustworthiness.

The author systematically reviews the literature and synthesizes it using a contingency theory lens to develop a framework for managing the opposing effects of AI explainability.

The author finds five opposing effects of explainability: comprehensibility, conduct, confidentiality, completeness and confidence in AI (5Cs). The author also proposes six perspectives on managing the tensions between the 5Cs: pragmatism in explanation, contextualization of the explanation, cohabitation of human agency and AI agency, metrics and standardization, regulatory and ethical principles, and other emerging solutions (i.e. AI enveloping, blockchain and AI fuzzy systems).

As in other systematic literature review studies, the results are limited by the content of the selected papers.

The findings show how AI owners and developers can manage tensions between profitability, prediction accuracy and system performance via visibility, accountability and maintaining the “social goodness” of AI. The results guide practitioners in developing metrics and standards for AI explainability, with the context of AI operation as the focus.

This study addresses polarized beliefs amongst scholars and practitioners about the benefits of AI explainability versus its counterproductive effects. It poses that there is no single best way to maximize AI explainability. Instead, the co-existence of enabling and constraining effects must be managed.

The characteristics of the Internet of Things (IoT) are such that traditional models of trust developed within interpersonal, organizational, virtual and information systems contexts may be inappropriate for use within an IoT context. The purpose of this paper is to offer empirically generated understandings of trust within potential IoT applications.

In an attempt to capture and communicate the complex and all-pervading but frequently inconspicuous nature of ubiquitous technologies within potential IoT techno-systems, propositions developed are investigated using a novel mixed methods research design combining a videographic projective technique with a quantitative survey, sampling 1,200 respondents.

Research findings suggest the dimensionality of trust may vary according to the IoT techno-service context being assessed.

The contribution of this paper is twofold. First, and from a theoretical perspective, it offers a conceptual foundation for trust dimensions within potential IoT applications based upon empirical evaluation. Second, and from a pragmatic perspective, the paper offers insights into how findings may guide practitioners in developing appropriate trust management systems dependent upon the characteristics of particular techno-service contexts.

This paper analyzes the ethics of integrating Artificial Intelligence (AI), particularly regarding AI-generated educational content in academia. It attempts to explore how AI customization mimics human interaction and behavior in education, investigate ethical concerns in educational AI adoption, and assess ChatGPT’s ethical use for nurturing curiosity and maintaining academic integrity in education.

Fictional tales may help us think critically and creatively to uncover hidden truths. The narratives are analyzed to determine the affordances and drawbacks of Artificial Intelligence in Education (AIEd).

The study highlights the imperative for innovative, ethically grounded strategies in harnessing AI/GPT technology for education. AI can enhance learning, and human educators’ irreplaceable role is even more prominent, emphasizing the need to harmonize technology with pedagogical principles. However, ensuring the ethical integration of AI/GPT technology demands a delicate balance where the potential benefits of technology should not eclipse the essential role of human educators in the learning process.

This paper presents futuristic academic scenarios to explore critical dimensions and their impact on 21^st century learning. As AI assumes tasks once exclusive to human educators, it is essential to redefine the roles of both technology and human teachers, focusing on the future.

Computing ethics represents a long established, yet rapidly evolving, discipline that grows in complexity and scope on a near-daily basis. Therefore, to help understand some of that scope it is essential to incorporate a range of perspectives, from a range of stakeholders, on current and emerging ethical challenges associated with computer technology. This study aims to achieve this by using, a three-pronged, stakeholder analysis of Computer Science academics, ICT industry professionals, and citizen groups was undertaken to explore what they consider to be crucial computing ethics concerns. The overlap between these stakeholder groups are explored, as well as whether their concerns are reflected in the existing literature.

Data collection was performed using focus groups, and the data was analysed using a thematic analysis. The data was also analysed to determine if there were overlaps between the literature and the stakeholders’ concerns and attitudes towards computing ethics.

The results of the focus group analysis show a mixture of overlapping concerns between the different groups, as well as some concerns that are unique to each of the specific groups. All groups stressed the importance of data as a key topic in computing ethics. This includes concerns around the accuracy, completeness and representativeness of data sets used to develop computing applications. Academics were concerned with the best ways to teach computing ethics to university students. Industry professionals believed that a lack of diversity in software teams resulted in important questions not being asked during design and development. Citizens discussed at length the negative and unexpected impacts of social media applications. These are all topics that have gained broad coverage in the literature.

In recent years, the impact of ICT on society and the environment at large has grown tremendously. From this fast-paced growth, a myriad of ethical concerns have arisen. The analysis aims to shed light on what a diverse group of stakeholders consider the most important social impacts of technology and whether these concerns are reflected in the literature on computing ethics. The outcomes of this analysis will form the basis for new teaching content that will be developed in future to help illuminate and address these concerns.

The multi-stakeholder analysis provides individual and differing perspectives on the issues related to the rapidly evolving discipline of computing ethics.

This study advances a reconceptualization of data and information which overcomes normative understandings often contained in data policies at national and international levels. This study aims to propose a conceptual framework that moves beyond subject- and collective-centric normative understandings.

To do so, this study discusses the European Union (EU) and China’s approaches to data-driven technologies highlighting their similarities and differences when it comes to the vision underpinning how tech innovation is shaped.

Regardless of the different attention to the subject (the EU) and the collective (China), the normative understandings of technology by both actors remain trapped into a positivist approach that overlooks all that is not and cannot be turned into data, thus hindering the elaboration of a more holistic ecological thinking merging humans and technologies.

Revising the philosophical and political debate on data and data-driven technologies, a third way is elaborated, i.e. federated data as commons. This third way puts the subject as part by default of a collective at the centre of discussion. This framing can serve as the basis for elaborating sociotechnical alternatives when it comes to define and regulate the mash-up of humans and technology.

The purpose of this study is to review the extant literature on chatbots and stakeholder interactions to identify major trends and shed light on knowledge gaps.

A systematic literature review was conducted combining qualitative and quantitative approaches. A code book based on early systematic literature reviews was developed and used to extract information from 62 discrete peer-reviewed English articles. An inductive approach was used to analyse definitions of chatbots, topics, metrics, perspectives and implications.

Chatbots have been studied by many different disciplines, but not much from organizational, stakeholder and corporate communication perspectives. Existing studies focus on the technical developments of chatbots and chatbot language and conversations skills. Research has remained anchored at the micro-level understanding of the phenomenon, that is, the nature of chatbots, but has not yet taken into consideration the meso (organizational) or macro (societal) levels.

This study focused only on academic peer-reviewed papers in English and excluded conference proceeding, books, book chapters and editorials that may have offered other important and relevant reflections. The limited number of studies in communication-related disciplines shows that corporate communication scholars could contribute more to the discussion of chatbot–stakeholder interactions.

This is the first research in the field of corporate communication that examines organizational chatbot–stakeholder interactions. Results of this review offer important information on chatbots' organizational capabilities and affordances, which, arguably, must be taken into consideration when stakeholder engagement strategies are set.

Following the call for strengthening the third pillar of knowledge in entrepreneurship as well as work-applied management contexts constituted by pragmatic design principles, we present a case study on an insurtech for insurance firms specialized in smart contract insurance solutions such as flight delay or ski resort insurance.

Design science.

This not only serves as a pointer for how insurances may master their digital transformation while remaining competitive. But moreover, on the meta level, we find that the adoption of entrepreneurial design principles by the students, whose experiential project represents our case study, does not necessarily require continuous support or foundational knowledge to be delivered beforehand. However, for a deeper or more holistic assessment of the case sketched in their project, it makes sense to introduce them to newer developments such as the simple, practical framework of the Entrepreneur's Question Index.

Innovative teaching method on innovative topics.

The term “agent-based modelling” (ABM) is a buzzword which is widely used in the scientific literature even though it refers to a variety of methodologies implemented in different disciplinary contexts. The numerous works dealing with ABM require a clarification to better understand the lines of thinking paved by this approach in economics. All modelling tasks are a means and a source of knowledge, and this epistemic function can vary depending on the methodology. this paper is to present four major ways (deductive, abductive, metaphorical and phenomenological) of implementing an agent-based framework to describe economic systems. ABM generates numerous debates in economics and opens the room for epistemological questions about the micro-foundations of macroeconomics; before dealing with this issue, the purpose of this paper is to identify the kind of ABM the author can find in economics.

The profusion of works dealing with ABM requires a clarification to understand better the lines of thinking paved by this approach in economics. This paper offers a conceptual classification outlining the major trends of ABM in economics.

There are four categories of ABM in economics.

This paper suggests a methodological categorization of ABM works in economics.

Considering the significance of the human resource management (HRM) and corporate social responsibility (CSR) relationship, the aim of this research is twofold: first is to measure the cultural differences between HRM, CSR and sustainable performance relationship (study 1) and second is to identify the how HRM instigates CSR and sustainable performance (study 2) in the hospitality industry of UK and Pakistan.

A mixed-method approach was used to collect the qualitative and quantitative data from upscale hotels. In Study 1, a multi-respondent and time-lagged strategy was employed to collect the data from 162 Pakistani and 290 UK upscale hotels. In Study 2, in-depth semi-structured interviews were conducted to understand the HRM–CSR–performance nexus.

The results of Study 1 highlight the significant cultural differences in the relationships of HRM–CSR–performance, while Study 2 explains that ethical culture, shared objectives, transparency, training and development, and economic incentives are the factors that push the employees to take part in CSR-related activities and attaining higher sustainable performance.

This study addresses the debate on the difference between cross-cultural studies related to implementing Western theories in shaping, developing and implementing business strategies, including CSR, HRM and sustainable performance in an Asian context.