Guide for Artificial Intelligence Ethical Requirements Elicitation - RE4AI Ethical Guide

Development and use of Artificial Intelligence (AI) based systems are growing at a fast pace in our society, simultaneously ethical concerns are arising from them. Addressing AI ethics is a continual issue and has provoked much debate among researchers. The aim of this work is to provide a Guide for Artificial Intelligence Ethical Requirements Elicitation (RE4AI Ethical Guide). The Design Science Research methodology was adopted in order to understand the problem, develop a prototype and evaluate it through a survey. The proposed Guide, composed of 26 cards along 11 ethical principles, is both useful and practical and can help in the elicitation of ethical requirements for AI in the context of agile development. Our preliminary results reveal that the Guide contributes to bridging the gap between high-level and abstract principles and practice by assisting developers and Product Owners to elicit ethical requirements and implement ethics in AI

Finding the traces of behavioral and cognitive processes in big data and naturally occurring datasets.

Today, people generate and store more data than ever before as they interact with both real and virtual environments. These digital traces of behavior and cognition offer cognitive scientists and psychologists an unprecedented opportunity to test theories outside the laboratory. Despite general excitement about big data and naturally occurring datasets among researchers, three gaps stand in the way of their wider adoption in theory-driven research: the imagination gap, the skills gap, and the culture gap. We outline an approach to bridging these three gaps while respecting our responsibilities to the public as participants in and consumers of the resulting research. To that end, we introduce Data on the Mind ( http://www.dataonthemind.org ), a community-focused initiative aimed at meeting the unprecedented challenges and opportunities of theory-driven research with big data and naturally occurring datasets. We argue that big data and naturally occurring datasets are most powerfully used to supplement-not supplant-traditional experimental paradigms in order to understand human behavior and cognition, and we highlight emerging ethical issues related to the collection, sharing, and use of these powerful datasets

Still minding the gap? Reflecting on transitions between concepts of information in varied domains

This conceptual paper, a contribution to the tenth anniversary special issue of information, gives a cross-disciplinary review of general and unified theories of information. A selective literature review is used to update a 2013 article on bridging the gaps between conceptions of information in different domains, including material from the physical and biological sciences, from the humanities and social sciences including library and information science, and from philosophy. A variety of approaches and theories are reviewed, including those of Brenner, Brier, Burgin and Wu, Capurro, Cárdenas-García and Ireland, Hidalgo, Hofkirchner, Kolchinsky and Wolpert, Floridi, Mingers and Standing, Popper, and Stonier. The gaps between disciplinary views of information remain, although there has been progress, and increasing interest, in bridging them. The solution is likely to be either a general theory of sufficient flexibility to cope with multiple meanings of information, or multiple and distinct theories for different domains, but with a complementary nature, and ideally boundary spanning concepts

Healthcare professionals' perspectives on mental health service provision : a pilot focus group study in six European countries

Background: The mental healthcare treatment gap (mhcGAP) in adult populations has been substantiated across Europe. This study formed part of MentALLY, a research project funded by the European Commission, which aimed to gather qualitative empirical evidence to support the provision of European mental healthcare that provides effective treatment to all adults who need it. Methods: Seven focus groups were conducted with 49 health professionals (HPs), including psychologists, psychiatrists, social workers, general practitioners, and psychiatric nurses who worked in health services in Belgium, Cyprus, Greece, the Netherlands, Norway and Sweden. The focus group discussions centered on the barriers and facilitators to providing quality care to people with mild, medium, and severe mental health problems. Analyses included deductively and inductively driven coding procedures. Cross-country consensus was obtained by summarizing findings in the form of a fact sheet which was shared for triangulation by all the MentALLY partners. Results: The results converged into two overarching themes: (1) Minding the treatment gap: the availability and accessibility of Mental Health Services (MHS). The mhcGAP gap identified is composed of different elements that constitute the barriers to care, including bridging divides in care provision, obstacles in facilitating access via referrals and creating a collaborative 'chain of care'. (2) Making therapeutic practice relevant by providing a broad-spectrum of integrated and comprehensive services that value person-centered care comprised of authenticity, flexibility and congruence. Conclusions: The mhcGAP is comprised of the following barriers: a lack of funding, insufficient capacity of human resources, inaccessibility to comprehensive services and a lack of availability of relevant treatments. The facilitators to the provision of MHC include using collaborative models of primary, secondary and prevention-oriented mental healthcare. Teamwork in providing care was considered to be a more effective and efficient use of resources. HPs believe that the use of e-mental health and emerging digital technologies can enhance care provision. Facilitating access to a relevant continuum of community-based care that is responsive coordinated and in line with people's needs throughout their lives is an essential aspect of optimal care provision

HUMAN RESOURCE MANAGERS’ ROLE IN THE DIGITAL ERA

The file attached to this record is the Publisher's final version.In any one organization, in Business, Service, Industry or State, Human Resource Management (HRM) is perceived as a set of activities that creates value to both the organization itself in terms of bottom line results and to employees, in terms of well – being and employment/ contract terms. Organizations, to a more or lesser extent, have adopted Digital technologies and as a result HR activities are affected, in terms of speed, accuracy, quality, cost innovation, flexibility. The aims of this theoretical study are to highlight HRM in the era of digitalization, emphasize the roles of HR managers in contemporary organizations and discuss the impact of technological changes on HR practices. In order to achieve our aims, we adopt a conceptual approach. Our results summarize the contemporary HRM definitions, discuss the impact of digital technologies in certain HR areas and emphasize the new digital role of human resource manager (d-HRM)

Beneficial Artificial Intelligence Coordination by means of a Value Sensitive Design Approach

This paper argues that the Value Sensitive Design (VSD) methodology provides a principled approach to embedding common values in to AI systems both early and throughout the design process. To do so, it draws on an important case study: the evidence and final report of the UK Select Committee on Artificial Intelligence. This empirical investigation shows that the different and often disparate stakeholder groups that are implicated in AI design and use share some common values that can be used to further strengthen design coordination efforts. VSD is shown to be both able to distill these common values as well as provide a framework for stakeholder coordination

Society-in-the-Loop: Programming the Algorithmic Social Contract

Recent rapid advances in Artificial Intelligence (AI) and Machine Learning have raised many questions about the regulatory and governance mechanisms for autonomous machines. Many commentators, scholars, and policy-makers now call for ensuring that algorithms governing our lives are transparent, fair, and accountable. Here, I propose a conceptual framework for the regulation of AI and algorithmic systems. I argue that we need tools to program, debug and maintain an algorithmic social contract, a pact between various human stakeholders, mediated by machines. To achieve this, we can adapt the concept of human-in-the-loop (HITL) from the fields of modeling and simulation, and interactive machine learning. In particular, I propose an agenda I call society-in-the-loop (SITL), which combines the HITL control paradigm with mechanisms for negotiating the values of various stakeholders affected by AI systems, and monitoring compliance with the agreement. In short, `SITL = HITL + Social Contract.'Comment: (in press), Ethics of Information Technology, 201

The regulatory gap in digital health and bridging it via alternative pathways

Physicians and Patients are overwhelmed with the number and variety of digital health technologies coming to market. Marketing authorizations by the U.S. FDA and its European counterparts normally bear signal effects: A product has been tested in a way that it is safe and efficacious for its intended purpose. This is currently not the case for digital health technologies (DHTs) given their characteristics, changes in actors and use contexts and lack of specific regulation in regard to those challenges. This regulatory gap, i.e. the lack of effective regulation of such technologies, poses a threat to patient-consumers. Alternatives to regulatory agency-based assessments are evaluated and proposed to offer some value in bridging the current regulatory gap until it is closed but cannot replace the role of regulatory agencies