Technical considerations towards mobile user QoE enhancement via Cloud interaction

This paper discusses technical considerations of a Cloud infrastructure which interacts with mobile devices in order to migrate part of the computational overhead from the mobile device to the Cloud. The aim of the interaction between the mobile device and the Cloud is the enhancement of parameters that affect the Quality of Experience (QoE) of the mobile end user through the offloading of computational aspects of demanding applications. This paper shows that mobile user’s QoE can be potentially enhanced by offloading computational tasks to the Cloud which incorporates a predictive context-aware mechanism to schedule delivery of content to the mobile end-user using a low-cost interaction model between the Cloud and the mobile user. With respect to the proposed enhancements, both the technical considerations of the cloud infrastructure are examined, as well as the interaction between the mobile device and the Cloud

MWQoE: A user-centered context-aware model for evaluating the Mobile Web Quality of Experience

This article presents a human-system interaction modelling approach for quantifying Web Quality of Experience (Web QoE) for mobile devices. It builds on current QoE and Web QoE research, and by fusing together data that is available on modern mobile devices, constructs a novel Mobile Web QoE (MWQoE) model that is user-centered and context-aware. The MWQoE model uses Bayesian Networks and works under uncertainty, while the MWQoE metric uses Utility Theory and delivers a quantified characterization of MWQoE on a single scale in specific scenarios. The importance of MWQoE lies in the fact that online content and service providers need insights into their users in order to understand how the experience in using their products is perceived

Case Study : The Internet of Things and Ethics

The Internet of Things (IoT) may be defined as a network of networks, where the end devices are not user-handled devices but can be computing devices, mechanical and digital machines. In many businesses, IoT-based software is used increasingly as a means to deliver enhanced customer service and improved business management procedures. By using IoT to monitor business operations, through tracking-capable software, businesses are, for instance, able to track products and employees. The issue is further explored through literature review and a case study of a company developing IoT based monitoring software. The review focuses on the effects of using IoT as part of Smart Information Systems, especially systems supported by 5G networks in the near future. The effects on the users of SIS are referred to by the term Quality of Experience (QoE) and the specific effects of 5G networks on QoE are discussed in this background review. Since the user experience is also affected by such actions as employee and asset monitoring with the use of IoT, a brief overview of legal aspects follows the technological details of QoE in an IoT-aware 5G system. The legal/human rights analysis is presented through the literature, and takes into account some suggestions for guidelines and policies on monitoring is offered. A discussion on ethics and perceptions around monitoring and tracking is further presented. The CRM.COM case focuses thereafter on how the company provides tracking software as a service and as a product for businesses nationally and in several countries worldwide. The case study discusses the ethics of such IoT-powered software, by considering both their design and their usage. Overall, the area of using IoT-based tracking and monitoring applications to assist and enhance specific business processes is growing and becoming increasingly popular, both in terms of development and use. Being a new research area, however, it lacks sufficient literature that examines the ethical, social, economic and legal implications of the use of this technology. Such studies into the design, development and use of such IoT-based applications present important relevant information that enriches the state-of-the-art literature on the topic both from an academic and a practical perspective. This report offers an original case study on the use of an IoT related SIS in the software design and development area. Many of the ethical and legal issues discussed in this report have been analysed more generally within academia and assessed in other areas of application, but have rarely been associated with the IoT usage for tracking and monitoring. Therefore, this report will be highly valuable for the development and furthering of theory, knowledge and application for designing, developing and using such IoT based applications

Quality of User Experience in 5G-VANET

The coalescence of 5G networks and vehicular ad-hoc networks (VANETs) will result in intelligent transportation and safety services and in-vehicle entertainment services. As a result, the plethora of connected devices (cars, mobile phones and other communication devices/sensors) will benefit from off-loading of network data on unlicensed bands to support network load balancing, providing guaranteed bit rate services and a reduction in control signaling, hence improving the overall user experience. In this paper we briefly discuss the enabling technologies, various communication scenarios within the 5G-VANET and the crucial user experience perspective. It should be noted that service acceptance depends heavily on user opinion formulated as per their experience. We further address the multi-layer Quality of Experience (QoE) assessment model and propose the way forward to enhance user experience within 5G-VANET. Since it is a work in progress, we discuss the importance of how and where the network performance measurements should be made and their effect on the overall user experience with future contributions in form of network simulations

Technofixing the Future: Ethical Side Effects of Using AI and Big Data to meet the SDGs

While the use of smart information systems (the combination of AI and Big Data) offer great potential for meeting many of the UN’s Sustainable Development Goals (SDGs), they also raise a number of ethical challenges in their implementation. Through the use of six empirical case studies, this paper will examine potential ethical issues relating to use of SIS to meet the challenges in six of the SDGs (2, 3, 7, 8, 11, and 12). The paper will show that often a simple “technofix”, such as through the use of SIS, is not sufficient and may exacerbate, or create new, issues for the development community using SIS

The Ethical Balance of Using Smart Information Systems for Promoting the United Nations’ Sustainable Development Goals

The Sustainable Development Goals (SDGs) are internationally agreed goals that allow us to determine what humanity, as represented by 193 member states, finds acceptable and desirable. The paper explores how technology can be used to address the SDGs and in particular Smart Information Systems (SIS). SIS, the technologies that build on big data analytics, typically facilitated by AI techniques such as machine learning, are expected to grow in importance and impact. Some of these impacts are likely to be beneficial, notably the growth in efficiency and profits, which will contribute to societal wellbeing. At the same time, there are significant ethical concerns about the consequences of algorithmic biases, job loss, power asymmetries and surveillance, as a result of SIS use. SIS have the potential to exacerbate inequality and further entrench the market dominance of big tech companies, if left uncontrolled. Measuring the impact of SIS on SDGs thus provides a way of assessing whether an SIS or an application of such a technology is acceptable in terms of balancing foreseeable benefits and harms. One possible approach is to use the SDGs as guidelines to determine the ethical nature of SIS implementation. While the idea of using SDGs as a yardstick to measure the acceptability of emerging technologies is conceptually strong, there should be empirical evidence to support such approaches. The paper describes the findings of a set of 6 case studies of SIS across a broad range of application areas, such as smart cities, agriculture, finance, insurance and logistics, explicitly focusing on ethical issues that SIS commonly raise and empirical insights from organisations using these technologies

An AI ethics ‘David and Goliath’: value conficts between large tech companies and their employees

Artifcial intelligence ethics requires a united approach from policymakers, AI companies, and individuals, in the development, deployment, and use of these technologies. However, sometimes discussions can become fragmented because of the diferent levels of governance (Schmitt in AI Ethics 1–12, 2021) or because of diferent values, stakeholders, and actors involved (Ryan and Stahl in J Inf Commun Ethics Soc 19:61–86, 2021). Recently, these conficts became very visible, with such examples as the dismissal of AI ethics researcher Dr. Timnit Gebru from Google and the resignation of whistle-blower Frances Haugen from Facebook. Underpinning each debacle was a confict between the organisation’s economic and business interests and the morals of their employees. This paper will examine tensions between the ethics of AI organisations and the values of their employees, by providing an exploration of the AI ethics literature in this area, and a qualitative analysis of three workshops with AI developers and practitioners. Common ethical and social tensions (such as power asymmetries, mistrust, societal risks, harms, and lack of transparency) will be discussed, along with proposals on how to avoid or reduce these conficts in practice (e.g., building trust, fair allocation of responsibility, protecting employees’ autonomy, and encouraging ethical training and practice). Altogether, we suggest the following steps to help reduce ethical issues within AI organisations: improved and diverse ethics education and training within businesses; internal and external ethics auditing; the establishment of AI ethics ombudsmen, AI ethics review committees and an AI ethics watchdog; as well as access to trustworthy AI ethics whistle-blower organisations

An Experience Report on the Effectiveness of Five Themed Workshops at Inspiring High School Students to Learn Coding

Today there is a high demand for computing programmers, and at the same time a shortage of skilled professionals. This has triggered the creation of many initiatives in the past few years, with the aim of reversing the phenomenon. To achieve this, such events are designed to promote a more appealing image for programming, both as a profession and as a skill. This paper describes one such initiative, which uses a unique blend of differently themed, parallel workshops to motivate high school students to learn programming. With the use of questionnaires, we survey the participants and present our findings concerning the effectiveness of these workshops to engage the participants, to promote the value of coding, and to encourage the participants to consider a career in the field. We evaluate our results both at a general level, as well as by comparison among five individually themed workshops

Organisational responses to the ethical issues of artificial intelligence

The ethics of artificial intelligence (AI) is a widely discussed topic. There are numerous initiatives that aim to develop the principles and guidance to ensure that the development, deployment and use of AI are ethically acceptable. What is generally unclear is how organisations that make use of AI understand and address these ethical issues in practice. While there is an abundance of conceptual work on AI ethics, empirical insights are rare and often anecdotal. This paper fills the gap in our current understanding of how organisations deal with AI ethics by presenting empirical findings collected using a set of ten case studies and providing an account of the cross-case analysis. The paper reviews the discussion of ethical issues of AI as well as mitigation strategies that have been proposed in the literature. Using this background, the cross-case analysis categorises the organisational responses that were observed in practice. The discussion shows that organisations are highly aware of the AI ethics debate and keen to engage with ethical issues proactively. However, they make use of only a relatively small subsection of the mitigation strategies proposed in the literature. These insights are of importance to organisations deploying or using AI, to the academic AI ethics debate, but maybe most valuable to policymakers involved in the current debate about suitable policy developments to address the ethical issues raised by AI

Research and Practice of AI Ethics: A Case Study Approach Juxtaposing Academic Discourse with Organisational Reality

This study investigates the ethical use of Big Data and Artificial Intelligence (AI) technologies (BD + AI)-using an empirical approach. The paper categorises the current literature and presents a multi-case study of 'on-the-ground' ethical issues that uses qualitative tools to analyse findings from ten targeted case-studies from a range of domains. The analysis coalesces identified singular ethical issues, (from the literature), into clusters to offer a comparison with the proposed classification in the literature. The results show that despite the variety of different social domains, fields, and applications of AI, there is overlap and correlation between the organisations' ethical concerns. This more detailed understanding of ethics in AI + BD is required to ensure that the multitude of suggested ways of addressing them can be targeted and succeed in mitigating the pertinent ethical issues that are often discussed in the literature