2,050 research outputs found

    Multidisciplinary perspectives on Artificial Intelligence and the law

    Get PDF
    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Measuring the Impact of China’s Digital Heritage: Developing Multidimensional Impact Indicators for Digital Museum Resources

    Get PDF
    This research investigates how to best assess the impact of China’s digital heritage and focuses on digital museum resources. It is motivated by the need for tools to help governing bodies and heritage organisations assess the impact of digital heritage resources. The research sits at the intersection of Chinese cultural heritage, digital heritage, and impact assessment (IA) studies, which forms the theoretical framework of the thesis. Informed by the Balanced Value Impact (BVI) Model, this thesis addresses the following questions: 1. How do Western heritage discourses and Chinese culture shape ‘cultural heritage’ and the museum digital ecosystem in modern China? 2. Which indicators demonstrate the multidimensional impacts of digital museum resources in China? How should the BVI Model be adapted to fit the Chinese cultural landscape? 3. How do different stakeholders perceive these impact indicators? What are the implications for impact indicator development and application? This research applies a mixed-method approach, combining desk research, survey, and interview with both public audiences and museum professionals. The research findings identify 18 impact indicators, covering economic, social, innovation and operational dimensions. Notably, the perceived usefulness and importance of different impact indicators vary among and between public participants and museum professionals. The study finds the BVI Model helpful in guiding the indicator development process, particularly in laying a solid foundation to inform decision-making. The Strategic Perspectives and Value Lenses provide a structure to organise various indicators and keep them focused on the impact objectives. However, the findings also suggest that the Value Lenses are merely signifiers; their signified meanings change with cultural contexts and should be examined when the Model is applied in a different cultural setting. This research addresses the absence of digital resource IA in China’s heritage sector. It contributes to the field of IA for digital heritage within and beyond the Chinese context by challenging the current target-setting culture in performance evaluation. Moreover, the research ratifies the utility of the BVI Model while modifying it to fit China’s unique cultural setting. This thesis as a whole demonstrates the value of using multidimensional impact indicators for evidence-based decision-making and better museum practices in the digital domain

    The use of proxies in designing for and with autistic children: supporting friendship as a case study

    Get PDF
    Participatory Design (PD) is an approach for designing new technologies which involves end users in the design process. It is generally accepted that involving users in the design process gives them a sense of ownership over the final product which enhances its usability and acceptance by the target population. Employing a PD approach can introduce multiple challenges especially when working with autistic children. Many approaches for involving autistic children and children with special needs were developed to address these challenges. However, these frameworks introduce their own limitations as well. There is an ethical dilemma to consider in the involvement of autistic children in the design process. Although we established the ethical benefit of involving children, we did not address the ethical issues that will result from involving them in these research projects. Among other issues, the nature of design workshops we as a community currently run require working with unfamiliar researchers and communicating with them while social and communication differences are one of the main diagnostic criteria for autism. When designing for autistic children and other vulnerable populations an alternative (or most often an additional) approach is designing with proxies. Proxies for the child can be one of several groups of other stakeholders, such as: teachers, parents and siblings. Each of these groups may inform the design process, from their particular perspective, and as proxies for the target group of autistic children. Decisions need to be made about what stages in the design process are suited to their participation, and the role they play in each case. For this reason, we explore the role of teachers, parents, autistic adults and neurotypical children as proxies in the design process. To explore the roles of proxies we chose friendship between autistic and neurotypical children as the context we are designing for. We are interested in understanding the nature of children's friendships and the potential for technology to support them. Although children themselves are the ones who experience friendship and challenges around its development and peer interaction, they might find it difficult to articulate the challenges they face. Furthermore, it is unrealistic to expect children to identify strategies to help them overcome the challenges with friendship development that they are facing as it assumes children have the social skills to come up with these strategies in the first place. Hence, it is necessary in this context to consider proxies who can identify challenges and suggest ways to overcome them

    NEMISA Digital Skills Conference (Colloquium) 2023

    Get PDF
    The purpose of the colloquium and events centred around the central role that data plays today as a desirable commodity that must become an important part of massifying digital skilling efforts. Governments amass even more critical data that, if leveraged, could change the way public services are delivered, and even change the social and economic fortunes of any country. Therefore, smart governments and organisations increasingly require data skills to gain insights and foresight, to secure themselves, and for improved decision making and efficiency. However, data skills are scarce, and even more challenging is the inconsistency of the associated training programs with most curated for the Science, Technology, Engineering, and Mathematics (STEM) disciplines. Nonetheless, the interdisciplinary yet agnostic nature of data means that there is opportunity to expand data skills into the non-STEM disciplines as well.College of Engineering, Science and Technolog

    Microcredentials to support PBL

    Get PDF

    Resilience in higher education settings during the COVID-19 pandemic:A scoping literature review with implications for policy and practice

    Get PDF
    With the onset of the COVID-19 pandemic, the construct of resilience has received growing attention in the higher education literature. The pandemic, acting as an external stressor, impacted multiple higher educational settings in 2020 during the period of lockdowns, when universities had to temporarily close on-campus activities and shift to online emergency responses. The objective of this scoping review is to explore how resilience was conceptualized in the higher education research literature during the initial emergency response phase of the pandemic, and how conceptual and research design choices in this early body of literature shaped policy recommendations aimed at enhancing resilience of individuals and support systems in higher education settings. This article, thus, contributes to the ongoing discussion in the academic and policy-relevant literature on how to better prepare universities as organizations and communities for a response not only during the emergency pandem ic, but also beyond in post-pandemic higher education settings. In particular, the paper examines five related questions, as pertaining to the early literature on the university emergency response in higher education: 1) how, and at which levels (i.e. individual, community, organization, system) was resilience conceptualized, 2) what types of research questions on resilience were being explored in this literature (i.e. determinants of resilience, or impacts of resilience), 3) how, and via which instruments, resilience was measured, 4) which factors were found to be facilitative for resilience, and 5) which factors were found to be impacts of resilience. The article synthesizes the findings of the early literature on resilience in higher education during the pandemic emergency response, and discusses important areas for further academic research, highlighting the implications for relevant support policies and interventions

    Digital Traces of the Mind::Using Smartphones to Capture Signals of Well-Being in Individuals

    Get PDF
    General context and questions Adolescents and young adults typically use their smartphone several hours a day. Although there are concerns about how such behaviour might affect their well-being, the popularity of these powerful devices also opens novel opportunities for monitoring well-being in daily life. If successful, monitoring well-being in daily life provides novel opportunities to develop future interventions that provide personalized support to individuals at the moment they require it (just-in-time adaptive interventions). Taking an interdisciplinary approach with insights from communication, computational, and psychological science, this dissertation investigated the relation between smartphone app use and well-being and developed machine learning models to estimate an individual’s well-being based on how they interact with their smartphone. To elucidate the relation between smartphone trace data and well-being and to contribute to the development of technologies for monitoring well-being in future clinical practice, this dissertation addressed two overarching questions:RQ1: Can we find empirical support for theoretically motivated relations between smartphone trace data and well-being in individuals? RQ2: Can we use smartphone trace data to monitor well-being in individuals?Aims The first aim of this dissertation was to quantify the relation between the collected smartphone trace data and momentary well-being at the sample level, but also for each individual, following recent conceptual insights and empirical findings in psychological, communication, and computational science. A strength of this personalized (or idiographic) approach is that it allows us to capture how individuals might differ in how smartphone app use is related to their well-being. Considering such interindividual differences is important to determine if some individuals might potentially benefit from spending more time on their smartphone apps whereas others do not or even experience adverse effects. The second aim of this dissertation was to develop models for monitoring well-being in daily life. The present work pursued this transdisciplinary aim by taking a machine learning approach and evaluating to what extent we might estimate an individual’s well-being based on their smartphone trace data. If such traces can be used for this purpose by helping to pinpoint when individuals are unwell, they might be a useful data source for developing future interventions that provide personalized support to individuals at the moment they require it (just-in-time adaptive interventions). With this aim, the dissertation follows current developments in psychoinformatics and psychiatry, where much research resources are invested in using smartphone traces and similar data (obtained with smartphone sensors and wearables) to develop technologies for detecting whether an individual is currently unwell or will be in the future. Data collection and analysis This work combined novel data collection techniques (digital phenotyping and experience sampling methodology) for measuring smartphone use and well-being in the daily lives of 247 student participants. For a period up to four months, a dedicated application installed on participants’ smartphones collected smartphone trace data. In the same time period, participants completed a brief smartphone-based well-being survey five times a day (for 30 days in the first month and 30 days in the fourth month; up to 300 assessments in total). At each measurement, this survey comprised questions about the participants’ momentary level of procrastination, stress, and fatigue, while sleep duration was measured in the morning. Taking a time-series and machine learning approach to analysing these data, I provide the following contributions: Chapter 2 investigates the person-specific relation between passively logged usage of different application types and momentary subjective procrastination, Chapter 3 develops machine learning methodology to estimate sleep duration using smartphone trace data, Chapter 4 combines machine learning and explainable artificial intelligence to discover smartphone-tracked digital markers of momentary subjective stress, Chapter 5 uses a personalized machine learning approach to evaluate if smartphone trace data contains behavioral signs of fatigue. Collectively, these empirical studies provide preliminary answers to the overarching questions of this dissertation.Summary of results With respect to the theoretically motivated relations between smartphone trace data and wellbeing (RQ1), we found that different patterns in smartphone trace data, from time spent on social network, messenger, video, and game applications to smartphone-tracked sleep proxies, are related to well-being in individuals. The strength and nature of this relation depends on the individual and app usage pattern under consideration. The relation between smartphone app use patterns and well-being is limited in most individuals, but relatively strong in a minority. Whereas some individuals might benefit from using specific app types, others might experience decreases in well-being when spending more time on these apps. With respect to the question whether we might use smartphone trace data to monitor well-being in individuals (RQ2), we found that smartphone trace data might be useful for this purpose in some individuals and to some extent. They appear most relevant in the context of sleep monitoring (Chapter 3) and have the potential to be included as one of several data sources for monitoring momentary procrastination (Chapter 2), stress (Chapter 4), and fatigue (Chapter 5) in daily life. Outlook Future interdisciplinary research is needed to investigate whether the relationship between smartphone use and well-being depends on the nature of the activities performed on these devices, the content they present, and the context in which they are used. Answering these questions is essential to unravel the complex puzzle of developing technologies for monitoring well-being in daily life.<br/

    30th European Congress on Obesity (ECO 2023)

    Get PDF
    This is the abstract book of 30th European Congress on Obesity (ECO 2023
    • …
    corecore