Search results

The purpose of this paper is to explore the ethical issues surrounding information systems (IS) practice with a view to encouraging greater involvement in this aspect of IS research. Information integrity relies upon the development and operation of computer-based information systems. Those who undertake the planning, development and operation of these information systems have obligations to assure information integrity and overall to contribute to the public good. This ethical dimension of information systems has attracted mixed attention in the IS academic discipline.

The authors are a multidisciplinary team providing a rich, diverse experience which includes professional and information ethics, management information systems, software engineering, data repositories and information systems development. Each author has used this experience to review the IS ethics landscape, which provides four complimentary perspectives. These are synthesised to tease out trends and future pointers.

It is confirmed that there is a serious lack of research being undertaken relating to the ethical dimension of the Information Systems field. There is limited crossover between the well-established multidisciplinary community of Computer Ethics research and the traditional Information Systems research community.

An outline framework is offered which could provide an opportunity for rich and valuable dialogue across the two communities. This is proposed as the starting point for a proactive research and practice action plan for information systems ethics.

This paper aims to assess the increasing challenges to governing the personal health information (PHI) essential for advancing artificial intelligence (AI) machine learning innovations in health care. Risks to privacy and justice/equity are discussed, along with potential solutions.

This conceptual paper highlights the scale and scope of PHI data consumed by deep learning algorithms and their opacity as novel challenges to health data governance.

This paper argues that these characteristics of machine learning will overwhelm existing data governance approaches such as privacy regulation and informed consent. Enhanced governance techniques and tools will be required to help preserve the autonomy and rights of individuals to control their PHI. Debate among all stakeholders and informed critique of how, and for whom, PHI-fueled health AI are developed and deployed are needed to channel these innovations in societally beneficial directions.

Health data may be used to address pressing societal concerns, such as operational and system-level improvement, and innovations such as personalized medicine. This paper informs work seeking to harness these resources for societal good amidst many competing value claims and substantial risks for privacy and security.

This is the first paper focusing on health data governance in relation to AI/machine learning.

This paper aims to explore the technologization of peace work through “remote support monitors” that use social and digital media technologies like social media to alert local violence prevention actors to potentially violent situations during demonstrations.

Using a distributed cognition lens, the authors explore the information processing of monitors within peace organizations. The authors adopt a qualitative thematic analysis methodology composed of interviews with monitors and documents from their shared communication and discussion channels. The authors’ analysis seeks to highlight how information is transformed between social and technical actors through the process of monitoring.

The authors’ analysis identifies that the technologization of monitoring for violence prevention to assist nonviolent activists produces two principal and related forms of transformation: appropriation and hidden attributes. Monitors “appropriate” information from sources to fit new ends and modes of representation throughout the process of detection, verification and dissemination. The verification and dissemination processes likewise render latent supporting informational elements, hiding the aggregative nature of information flow in monitoring. The authors connect the ideas of appropriation and hidden attributes to broader discourses in surveillance and trust that challenge monitoring and its place in peace work going forward.

To the best of the authors’ knowledge, this study is the first to focus on the communicative and information processes of remote support monitors. The authors demonstrate that adoption of social and digital media information of incipient violence and response processes for its mitigation suggests both a social and technical precarity for the role of monitoring.