1,545 research outputs found
Multidisciplinary perspectives on Artificial Intelligence and the law
This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (âAIâ) 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 â 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 CatĂłlica 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
A user-centred collective system design approach for Smart Product-Service Systems:A case study on fitness product design
Emerging technologies have significantly contributed to the evolution of traditional product-service systems (PSS) into smart PSS. This transformation demands a fresh perspective and a more inventive design approach. In response, this study proposes a new User-Centred Collective System Design (CSD) framework and process for Smart PSS design, aiming to enhance stakeholder engagement during the entire design process, thus promoting highly effective and creative design solutions. A case study, titled âNext-G Smart Fitness PSS Designâ, was carried out to test and implement this approach, contrasting the results of the CSD method with a designer-centred method. The outcomes showed a marked improvement in product novelty and user desirability of the design outcomes when using the proposed design framework. The proposed CSD framework could offer beneficial insights and user-centric viewpoints for practitioners dealing with complex challenges linked to smart PSS design
Second-Person Surveillance: Politics of User Implication in Digital Documentaries
This dissertation analyzes digital documentaries that utilize second-person address and roleplay to make users feel implicated in contemporary refugee crises, mass incarceration in the U.S., and state and corporate surveillances. Digital documentaries are seemingly more interactive and participatory than linear film and video documentary as they are comprised of a variety of auditory, visual, and written media, utilize networked technologies, and turn the documentary audience into a documentary user. I draw on scholarship from documentary, game, new media, and surveillance studies to analyze how second-person address in digital documentaries is configured through user positioning and direct address within the works themselves, in how organizations and creators frame their productions, and in how users and players respond in reviews, discussion forums, and Letâs Plays. I build on Michael Rothbergâs theorization of the implicated subject to explore how these digital documentaries bring the user into complicated relationality with national and international crises. Visually and experientially implying that users bear responsibility to the subjects and subject matter, these works can, on the one hand, replicate modes of liberal empathy for suffering, distant âothersâ and, on the other, simulate oneâs own surveillant modes of observation or behavior to mirror it back to users and open up oneâs offline thoughts and actions as a site of critique.
This dissertation charts how second-person address shapes and limits the political potentialities of documentary projects and connects them to a lineage of direct address from educational and propaganda films, museum exhibits, and serious games. By centralizing the userâs individual experience, the interventions that second-person digital documentaries can make into social discourse change from public, institution-based education to more privatized forms of sentimental education geared toward personal edification and self-realization. Unless tied to larger initiatives or movements, I argue that digital documentaries reaffirm a neoliberal politics of individual self-regulation and governance instead of public education or collective, social intervention.
Chapter one focuses on 360-degree virtual reality (VR) documentaries that utilize the feeling of presence to position users as if among refugees and as witnesses to refugee experiences in camps outside of Europe and various dwellings in European cities. My analysis of Clouds Over Sidra (Gabo Arora and Chris Milk 2015) and The Displaced (Imraan Ismail and Ben C. Solomon 2015) shows how these VR documentaries utilize observational realism to make believable and immersive their representations of already empathetic refugees. The empathetic refugee is often young, vulnerable, depoliticized and dehistoricized and is a well-known trope in other forms of humanitarian media that continues into VR documentaries. Forced to Flee (Zahra Rasool 2017), I am Rohingya (Zahra Rasool 2017), So Leben FlĂŒchtlinge in Berlin (Berliner Morgenpost 2017), and Limbo: A Virtual Experience of Waiting for Asylum (Shehani Fernando 2017) disrupt easy immersions into realistic-looking VR experiences of stereotyped representations and user identifications and, instead, can reflect back the userâs political inaction and surveillant modes of looking.
Chapter two analyzes web- and social media messenger-based documentaries that position users as outsiders to U.S. mass incarceration. Users are noir-style co-investigators into the crime of the prison-industrial complex in Fremont County, Colorado in Prison Valley: The Prison Industry (David Dufresne and Philippe Brault 2009) and co-riders on a bus transporting prison inmatesâ loved ones for visitations to correctional facilities in Upstate New York in A Temporary Contact (Nirit Peled and Sara Kolster 2017). Both projects construct an experience of carceral constraint for users to reinscribe seeming âoutsideâ places, people, and experiences as within the continuation of the racialized and classed politics of state control through mass incarceration. These projects utilize interfaces that create a tension between replicating an exploitative hierarchy between non-incarcerated users and those subject to mass incarceration while also de-immersing users in these experiences to mirror back the userâs supposed distance from this mode of state regulation.
Chapter three investigates a type of digital game I term dataveillance simulation games, which position users as surveillance agents in ambiguously dystopian nation-states and force users to use their own critical thinking and judgment to construct the criminality of state-sanctioned surveillance targets. Project Perfect Citizen (Bad Cop Studios 2016), Orwell: Keeping an Eye on You (Osmotic Studios 2016), and Papers, Please (Lucas Pope 2013) all create a dual empathy: players empathize with bureaucratic surveillance agents while empathizing with surveillance targets whose emails, text messages, documents, and social media profiles reveal them to be ânormalâ people. I argue that while these games show criminality to be a construct, they also utilize a racialized fear of the loss of oneâs individual privacy to make players feel like they too could be surveillance targets.
Chapter four examines personalized digital documentaries that turn users and their data into the subject matter. Do Not Track (Brett Gaylor 2015), A Week with Wanda (Joe Derry Hall 2019), Stealing Ur Feelings (Noah Levenson 2019), Alfred Premium (JoĂ«l Ronez, Pierre Corbinais, and Ămilie F. Grenier 2019), How They Watch You (Nick Briz 2021), and Fairly Intelligentâą (A.M. Darke 2021) track, monitor, and confront users with their own online behavior to reflect back a corporate surveillance that collects, analyzes, and exploits user data for profit. These digital documentaries utilize emotional fear- and humor-based appeals to persuade users that these technologies are controlling them, shaping their desires and needs, and dehumanizing them through algorithmic surveillance
Digital Traces of the Mind::Using Smartphones to Capture Signals of Well-Being in Individuals
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 individualâs 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 individualâs 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 participantsâ 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 participantsâ 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/
The Politics of Platformization: Amsterdam Dialogues on Platform Theory
What is platformization and why is it a relevant category in the contemporary political landscape? How is it related to cybernetics and the history of computation? This book tries to answer such questions by engaging in multidisciplinary dialogues about the first ten years of the emerging fields of platform studies and platform theory. It deploys a narrative and playful approach that makes use of anecdotes, personal histories, etymologies, and futurable speculations to investigate both the fragmented genealogy that led to platformization and the organizational and economic trends that guide nowadays platform sociotechnical imaginaries
Evidence in practice: how structural and programmatic scaffolds enable knowledge transfer in international development
This inductive study of eight international development interventions across four countries analyzes the mechanisms that enable effective integration of evidence in practice, as an enduring challenge of learning and coordination across occupational and organizational boundaries. We identify how a set of critical, complementary structural and programmatic scaffolding practices, jointly provided a shared architecture for actors across organizations and communities of practice to collaborate and learn within the uncertainty and complexity inherent in the international development context.
Scaffolding practices offered modular, temporary counter-balancing stabilizing and extending support that enabled the unusual and counter normative behaviors and mindsets required for continuous learning and adaptive coordination.
Through 226 in-depth interviews with a range of international development experts, including practitioners engaged in eight matched interventions in India, Mexico, South Africa, and Ghana,we identified and analyzed the mechanisms that explain the varying degrees of effectiveness with which rigorous evidence was integrated in each case.
Our findings have implications for interorganizational innovation and collaboration under conditions of complexity and uncertainty, as well as the dynamic interactions between individuals, their organizations, and their communities of practice when attempting to bring about systemic change.William and Flora Hewlett FoundationAccepted manuscrip
Next Generation Business Ecosystems: Engineering Decentralized Markets, Self-Sovereign Identities and Tokenization
Digital transformation research increasingly shifts from studying information systems within organizations towards adopting an ecosystem perspective, where multiple actors co-create value. While digital platforms have become a ubiquitous phenomenon in consumer-facing industries, organizations remain cautious about fully embracing the ecosystem concept and sharing data with external partners. Concerns about the market power of platform orchestrators and ongoing discussions on privacy, individual empowerment, and digital sovereignty further complicate the widespread adoption of business ecosystems, particularly in the European Union.
In this context, technological innovations in Web3, including blockchain and other distributed ledger technologies, have emerged as potential catalysts for disrupting centralized gatekeepers and enabling a strategic shift towards user-centric, privacy-oriented next-generation business ecosystems. However, existing research efforts focus on decentralizing interactions through distributed network topologies and open protocols lack theoretical convergence, resulting in a fragmented and complex landscape that inadequately addresses the challenges organizations face when transitioning to an ecosystem strategy that harnesses the potential of disintermediation.
To address these gaps and successfully engineer next-generation business ecosystems, a comprehensive approach is needed that encompasses the technical design, economic models, and socio-technical dynamics. This dissertation aims to contribute to this endeavor by exploring the implications of Web3 technologies on digital innovation and transformation paths. Drawing on a combination of qualitative and quantitative research, it makes three overarching contributions:
First, a conceptual perspective on \u27tokenization\u27 in markets clarifies its ambiguity and provides a unified understanding of the role in ecosystems.
This perspective includes frameworks on: (a) technological; (b) economic; and (c) governance aspects of tokenization.
Second, a design perspective on \u27decentralized marketplaces\u27 highlights the need for an integrated understanding of micro-structures, business structures, and IT infrastructures in blockchain-enabled marketplaces. This perspective includes: (a) an explorative literature review on design factors; (b) case studies and insights from practitioners to develop requirements and design principles; and (c) a design science project with an interface design prototype of blockchain-enabled marketplaces.
Third, an economic perspective on \u27self-sovereign identities\u27 (SSI) as micro-structural elements of decentralized markets. This perspective includes: (a) value creation mechanisms and business aspects of strategic alliances governing SSI ecosystems; (b) business model characteristics adopted by organizations leveraging SSI; and (c) business model archetypes and a framework for SSI ecosystem engineering efforts.
The dissertation concludes by discussing limitations as well as outlining potential avenues for future research. These include, amongst others, exploring the challenges of ecosystem bootstrapping in the absence of intermediaries, examining the make-or-join decision in ecosystem emergence, addressing the multidimensional complexity of Web3-enabled ecosystems, investigating incentive mechanisms for inter-organizational collaboration, understanding the role of trust in decentralized environments, and exploring varying degrees of decentralization with potential transition pathways
Parameterizing the Spillage Left Behind: Datafication, Machine Learning Algorithms, and the Question of Ecological Agency
With âdataficationâ practices becoming more common in digital ecologies, humans have become increasingly reliant on emerging technologies and other actors that can store, comprehend, and analyze information. This thesis offers a proposed model of mediative agency to address the importance of interrogating how non-human actors interpret and make meaning from data. Mediative agents contribute to the disbursement of rhetoric, as well as our understanding of information, by granting visibility and assigning value to data. These processes effectively play a role in shaping reality through agentsâ parameterization of data broadly, allowing non-human actors to take on a complex agency that can alter rhetorical trajectories. In interrogating the structures of power that contribute to the dissemination of rhetoric within digital ecologies, mediative agency acts as a speculative modeling approach that allows rhetors to theorize various functions of agency and anticipate how non-human agency might further develop as technological environments change in the immediate future
A Review of the Role of Causality in Developing Trustworthy AI Systems
State-of-the-art AI models largely lack an understanding of the cause-effect
relationship that governs human understanding of the real world. Consequently,
these models do not generalize to unseen data, often produce unfair results,
and are difficult to interpret. This has led to efforts to improve the
trustworthiness aspects of AI models. Recently, causal modeling and inference
methods have emerged as powerful tools. This review aims to provide the reader
with an overview of causal methods that have been developed to improve the
trustworthiness of AI models. We hope that our contribution will motivate
future research on causality-based solutions for trustworthy AI.Comment: 55 pages, 8 figures. Under revie
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