The Problem of Integrating Ethics into IS Practice

In this paper we discuss a number of implications which follow from the way that the information systems discipline has developed, largely separately, from computer ethics. These include the tendency of quantitative IS studies on ethics to focus on ethical decision making as the most significant activity in the business of behaving morally meaning that other aspects of moral behaviour are overlooked. A second, significant, implication is the difficulty of integrating ethical practice into IS development. This is manifest initially in terms of IS education but later in relation to the development, and use, of IS in the workplace. Focusing on information systems development, we discuss practice, focusing on ethics and IS practice especially rationalistic approach to decision making, the support that conventional development methodologies offer the moral agent followed by learning to practice or the business of integrating ethics into IS education and how to turn moral decision making into teachable ethical constructs. We conclude by offering some suggestions for future directions

Incorporating ethics in software engineering : challenges and opportunities

Ethics is recognised as an important concern in the development and operation of software systems. While there are codes of ethics and sets of ethical principles available to software professionals, there is a lack of tool and process support for systematic ethical deliberation at most stages of the software lifecycle. To create and deploy ethical software, it is vital that ethical concerns of software systems are reflected in their artefacts, such as requirements, software architecture, code and test suites, and that software professionals are supported in considering the ethical as well as technical consequences of their decisions. This paper reports on some early work in identifying the challenges of ethical decision making and opportunities for addressing these challenges in the context of software engineering.Postprin

Ethics of the algorithmic prediction of goal of care preferences: from theory to practice

Artificial intelligence (AI) systems are quickly gaining ground in healthcare and clinical decision-making. However, it is still unclear in what way AI can or should support decision-making that is based on incapacitated patients’ values and goals of care, which often requires input from clinicians and loved ones. Although the use of algorithms to predict patients’ most likely preferred treatment has been discussed in the medical ethics literature, no example has been realised in clinical practice. This is due, arguably, to the lack of a structured approach to the epistemological, ethical and pragmatic challenges arising from the design and use of such algorithms. The present paper offers a new perspective on the problem by suggesting that preference predicting AIs be viewed as sociotechnical systems with distinctive life-cycles. We explore how both known and novel challenges map onto the different stages of development, highlighting interdisciplinary strategies for their resolution

Participatory development of decision support systems: which features of the process lead to improved uptake and better outcomes?

Decision support systems (DSSs) are important in decision-making environments with conflicting interests. Many DSSs developed have not been used in practice. Experts argue that these tools do not respond to real user needs and that the inclusion of stakeholders in the development process is the solution. However, it is not clear which features of participatory development of DSSs result in improved uptake and better outcomes. A review of papers, reporting on case studies where DSSs and other decision tools (information systems, software and scenario tools) were developed with elements of participation, was carried out. The cases were analysed according to a framework created as part of this research; it includes criteria to evaluate the development process and the outcomes. Relevant aspects to consider in the participatory development processes include establishing clear objectives, timing and location of the process; keeping discussions on track; favouring participation and interaction of individuals and groups; and challenging creative thinking of the tool and future scenarios. The case studies that address these issues show better outcomes; however, there is a large degree of uncertainty concerning them because developers have typically neither asked participants about their perceptions of the processes and resultant tools nor have they monitored the use and legacy of the tools over the long term.The authors would like to thank COST Action FP0804-Forest Management Decision Support Systems (FORSYS) for financing a three month Short-Term Scientific Mission (STSM) in Forest Research (Roslin, UK) in 2012, making possible this research; Spanish Ministry of Economy and Competitiveness for supporting the project Multicriteria Techniques and Participatory Decision-Making for Sustainable Management (Ref. ECO2011-27369) where the leading author is involved; and the Regional Ministry of Education, Culture and Sports (Valencia, Spain) for financing a research fellowship (Ref. ACIF/2010/248).Valls Donderis, P.; Ray, D.; Peace, A.; Stewart, A.; Lawrence, A.; Galiana, F. 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Using multi-perspective methodologies to study users’ interactions with the prototype front end of a guideline-based decision support system for diabetic foot care. International Journal of Medical Informatics, 78(7), 482-493. doi:10.1016/j.ijmedinf.2009.02.008Pretty, J. N. (1995). Participatory learning for sustainable agriculture. World Development, 23(8), 1247-1263. doi:10.1016/0305-750x(95)00046-fReed MS. 2008. Stakeholder participation for environmental management: a literature review. Sustainability Research Institute, School of Earth and Environment, University of Leeds.Reed, M. S., & Dougill, A. J. (2010). Linking degradation assessment to sustainable land management: A decision support system for Kalahari pastoralists. Journal of Arid Environments, 74(1), 149-155. doi:10.1016/j.jaridenv.2009.06.016Rowe, G., & Frewer, L. J. (2000). Public Participation Methods: A Framework for Evaluation. 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Leveraging algorithms to improve decision-making workflows for genomic data access and management

Studies on the ethics of automating clinical or research decision making using artificial intelligence and other algorithmic tools abound. Less attention has been paid, however, to the scope for, and ethics of, automating decision making within regulatory apparatuses governing the access, use, and exchange of data involving humans for research. In this article, we map how the binary logic flows and real-time capabilities of automated decision support (ADS) systems may be leveraged to accelerate one rate-limiting step in scientific discovery: data access management. We contend that improved auditability, consistency, and efficiency of the data access request process using ADS systems have the potential to yield fairer outcomes in requests for data largely sourced from biospecimens and biobanked samples. This procedural justice rationale reinforces a broader set of participant and data subject rights that data access committees (DACs) indirectly protect. DACs protect the rights of citizens to benefit from science by bringing researchers closer to the data they need to advance that science. DACs also protect the informational dignities of individuals and communities by ensuring the data being accessed are used in ways consistent with participant values. We discuss the development of the Global Alliance for Genomics and Health Data Use Ontology standard as a test case of ADS for genomic data access management specifically, and we synthesize relevant ethical, legal, and social challenges to its implementation in practice. We conclude with an agenda of future research needed to thoughtfully advance strategies for computational governance that endeavor to instill public trust in, and maximize the scientific value of, health-related human data across data types, environments, and user communities

A Framework of International Competencies for Systems Engineers

In the course of their career, many systems engineers are likely to interact with engineers of other nationalities as they collaborate on large, complex projects and system of system problems. These partnerships are necessary to support international goals, such as those for sustainable development. System engineers may even work onsite in other countries where they must adapt to different styles of doing business. This requires a set of global skill sets for cooperating and decision making, as well as basic social skills for interacting with the local community. These global skills can be included in a graduate level system engineering curriculum by integrating a set of “international competencies” that includes cognitive style differences, culture awareness, communication, ethics, and teamwork. The competencies were identified through a literature review of suggested global engineering skill sets; these five themes consistently appeared throughout the literature. The Graduate Reference Curriculum for Systems Engineering (GRCSE) was then reviewed to link these competencies to established systems engineering learning outcomes and System Engineering Body of Knowledge (SEBOK) topics. Finally, teaching elements are suggested that can be included even in established curriculums to introduce systems engineers to the skills they need to be successful in a global world

Ethical AI: Proposal to bridge the gap in EU regulation on trustworthy AI and to support practical implementation of ethical perspectives

In 2020, GPT-3 defined itself as a thinking robot. The history of AI development is identified with machines becoming increasingly intelligent, but behind it lies the human factor, the soaring of the human mind. However, the question of machine ethics is also a question of cultural ethics. Based on in-depth interviews conducted in seven industries, the author reveals that ethical considerations are not yet taken into account in the development of AI systems. To support practical implementation, the author identifies two shortcomings based on a comparative analysis of the EU’s AI Act and Ethical Guidelines for Trustworthy AI: (1) missing ethical sensitisation and training of AI system developers and supervisors; (2) suggested approaches to handling harmful feedback loops and decision-making biases. The author uses the philosophical and ethical heritage of 21 philosophers as a compass to propose solutions for the identified gaps and deficiencies of organisational integration

Social awareness in design & engineering education and practice: the value of ethics in postgraduate education

This paper describes how the practice of ethics and morality in design and engineering education can foster an industry which is ethically capable of tackling social issues. Through ethically aware design methodologies that postgraduate cross-discipline students developed through workshops, this paper outlines and discusses possible directions and methods that design and engineering education could evolve with further study. What can ethics awareness in postgraduate education trigger and how can it influence future design and engineering practice? For the major role morality and ethics have in ruling social coexistence designers and engineers are called to take responsibility of any action that shapes behaviour between people, products and systems. To respond to the need of a collective ethical etiquette that products and systems can encode, design research at the Royal College of Art has been supporting a practice that acknowledges impacts and people’s responsibilities. A series of workshops explores the role of collaboration and engagement in drawing ethically aware design and engineering processes; it evidences how these are strategic in modulating relationships and behaviours and in guiding the mapping of the interactions of people with people and machines to acknowledge roles, responsibilities and the ownership of decision-making. The intention of this paper is not to draw conclusions on what ethics is and how it should be practiced, but to support the development of guidelines that can engage design and engineering education and industry with debates on responsibilities and decision-making across the lifecycle of a product, system, service or infrastructure. This paper intends to be an engaged, collegial and collaborative contribution to the topic of ethics in design/engineering education and practice

SERIES:eHealth in primary care. Part 2: Exploring the ethical implications of its application in primary care practice

Background: eHealth promises to increase self-management and personalised medicine and improve cost-effectiveness in primary care. Paired with these promises are ethical implications, as eHealth will affect patients' and primary care professionals' (PCPs) experiences, values, norms, and relationships.Objectives: We argue what ethical implications related to the impact of eHealth on four vital aspects of primary care could (and should) be anticipated.Discussion: (1) EHealth influences dealing with predictive and diagnostic uncertainty. Machine-learning based clinical decision support systems offer (seemingly) objective, quantified, and personalised outcomes. However, they also introduce new loci of uncertainty and subjectivity. The decision-making process becomes opaque, and algorithms can be invalid, biased, or even discriminatory. This has implications for professional responsibilities and judgments, justice, autonomy, and trust. (2) EHealth affects the roles and responsibilities of patients because it can stimulate self-management and autonomy. However, autonomy can also be compromised, e.g. in cases of persuasive technologies and eHealth can increase existing health disparities. (3) The delegation of tasks to a network of technologies and stakeholders requires attention for responsibility gaps and new responsibilities. (4) The triangulate relationship: patient-eHealth-PCP requires a reconsideration of the role of human interaction and 'humanness' in primary care as well as of shaping Shared Decision Making.Conclusion: Our analysis is an essential first step towards setting up a dedicated ethics research agenda that should be examined in parallel to the development and implementation of eHealth. The ultimate goal is to inspire the development of practice-specific ethical recommendations