Search results

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.

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.