This book constitutes the thoroughly refereed post-conference proceedings of the First International Workshop on Personal Analytics and Privacy, PAP 2017, held in Skopje, Macedonia, in September 2017. The 14 papers presented together with 2 invited talks in this volume were carefully reviewed and selected for inclusion in this book and handle topics such as personal analytics, personal data mining and privacy in the context where real individual data are used for developing a data-driven service, for realizing a social study aimed at understanding nowadays society, and for publication purposes.
This book features extended versions of selected papers that were presented and discussed at the 6th International Doctoral Symposium on Applied Computation and Security Systems (ACSS 2019) held in Kolkata, India on 12–13 March, 2019. Organized by the Departments of Computer Science & Engineering and A.K. Choudhury School of Information Technology, both from the University of Calcutta, the symposium’s international partners were Ca' Foscari University of Venice, Italy and Bialystok University of Technology, Poland. The chapters cover topics such as biometrics, image processing, pattern recognition, algorithms, cloud computing, wireless sensor networks and security systems, reflecting the various symposium sessions.
The goal of the book is to present the latest research on the new challenges of data technologies. It will offer an overview of the social, ethical and legal problems posed by group profiling, big data and predictive analysis and of the different approaches and methods that can be used to address them. In doing so, it will help the reader to gain a better grasp of the ethical and legal conundrums posed by group profiling. The volume first maps the current and emerging uses of new data technologies and clarifies the promises and dangers of group profiling in real life situations. It then balances this with an analysis of how far the current legal paradigm grants group rights to privacy and data protection, and discusses possible routes to addressing these problems. Finally, an afterword gathers the conclusions reached by the different authors and discuss future perspectives on regulating new data technologies.
This is an open access title available under the terms of a CC BY-NC-ND 4.0 International licence. It is free to read at Oxford Scholarship Online and offered as a free PDF download from OUP and selected open access locations. Are algorithms ruling the world today? Is artificial intelligence making life-and-death decisions? Are social media companies able to manipulate elections? As we are confronted with public and academic anxieties about unprecedented changes, this book offers a different analytical prism through which these transformations can be explored. Claudia Aradau and Tobias Blanke develop conceptual and methodological tools to understand how algorithmic operations shape the government of self and other. They explore the emergence of algorithmic reason through rationalities, materializations, and interventions, and trace how algorithmic rationalities of decomposition, recomposition, and partitioning are materialized in the construction of dangerous others, the power of platforms, and the production of economic value. The book provides a global trandisciplinary perspective on algorithmic operations, drawing on qualitative and digital methods to investigate controversies ranging from mass surveillance and the Cambridge Analytica scandal in the UK to predictive policing in the US, and from the use of facial recognition in China and drone targeting in Pakistan to the regulation of hate speech in Germany.
This open access book provides researchers and professionals with a foundational understanding of online privacy as well as insight into the socio-technical privacy issues that are most pertinent to modern information systems, covering several modern topics (e.g., privacy in social media, IoT) and underexplored areas (e.g., privacy accessibility, privacy for vulnerable populations, cross-cultural privacy). The book is structured in four parts, which follow after an introduction to privacy on both a technical and social level: Privacy Theory and Methods covers a range of theoretical lenses through which one can view the concept of privacy. The chapters in this part relate to modern privacy phenomena, thus emphasizing its relevance to our digital, networked lives. Next, Domains covers a number of areas in which privacy concerns and implications are particularly salient, including among others social media, healthcare, smart cities, wearable IT, and trackers. The Audiences section then highlights audiences that have traditionally been ignored when creating privacy-preserving experiences: people from other (non-Western) cultures, people with accessibility needs, adolescents, and people who are underrepresented in terms of their race, class, gender or sexual identity, religion or some combination. Finally, the chapters in Moving Forward outline approaches to privacy that move beyond one-size-fits-all solutions, explore ethical considerations, and describe the regulatory landscape that governs privacy through laws and policies. Perhaps even more so than the other chapters in this book, these chapters are forward-looking by using current personalized, ethical and legal approaches as a starting point for re-conceptualizations of privacy to serve the modern technological landscape. The book's primary goal is to inform IT students, researchers, and professionals about both the fundamentals of online privacy and the issues that are most pertinent to modern information systems. Lecturers or teachers can assign (parts of) the book for a “professional issues” course. IT professionals may select chapters covering domains and audiences relevant to their field of work, as well as the Moving Forward chapters that cover ethical and legal aspects. Academics who are interested in studying privacy or privacy-related topics will find a broad introduction in both technical and social aspects.
Cover -- Half-title -- Title -- Copyright -- Contents -- Introduction -- PART I: ENGAGING THE DATA -- 1 Measuring Political and Policy Preferences Using Item Response Scaling -- 2 Causal Inference with Observational Data -- 3 Causal Inference with Experimental Data -- PART II: EMERGING DATA SOURCES AND TECHNIQUES -- 4 Descriptive Network Analysis: Interest Group Lobbying Dynamics Around Immigration Policy -- 5 Learning from Place in the Era of Geolocation -- 6 Text Analysis: Estimating Policy Preferences from Written and Spoken Words -- 7 Machine Learning and Governance -- PART III: IMPLICATIONS FOR GOVERNANCE -- 8 Governing a Data-Driven Society -- 9 Big Data and Privacy -- 10 Reflections on Analytics: Knowledge and Power -- List of Contributors -- Index -- A -- B -- C -- D -- E -- F -- G -- H -- I -- J -- K -- L -- M -- N -- O -- P -- Q -- R -- S -- T -- U -- V -- W -- Y
In digital markets, data protection and competition law affect each other in diverse and intricate ways. Their entanglement has triggered a global debate on how these two areas of law should interact to effectively address new harms and ensure that the digital economy flourishes. Coherence between Data Protection and Competition Law in Digital Markets offers a blueprint for bridging the disconnect between data protection and competition law and ensuring a coherent approach towards their enforcement in digital markets. Specifically, this book focuses on the evolution of data protection and competition law, their underlying rationale, their key features and common objectives, and provides a series of examples to demonstrate how the same empirical phenomena in digital markets pose a common challenge to protecting personal data and promoting market competitiveness. A panoply of theoretical and empirical commonalities between these two fields of law, as this volume shows, are barely mirrored in the legal, enforcement, policy, and institutional approaches in the EU and beyond, where the silo approach continues to prevail. The ideas that Majcher puts forward for a more synergetic integration of data protection and competition law are anchored in the concept of 'sectional coherence'. This new coherence-centred paradigm reimagines the interpretation and enforcement of data protection and competition law as mutually cognizant and reciprocal, allowing readers to explore, in an innovative way, the interface between these legal fields and identify positive interactions, instead of merely addressing inconsistencies and tensions. This book reflects on the conceptual, practical, institutional, and constitutional implications of the transition towards coherence and the relevance of its findings for other jurisdictions.
Moving away from the strong body of critique of pervasive ?bad data? practices by both governments and private actors in the globalized digital economy, this book aims to paint an alternative, more optimistic but still pragmatic picture of the datafied future. The authors examine and propose ?good data? practices, values and principles from an interdisciplinary, international perspective. From ideas of data sovereignty and justice, to manifestos for change and calls for activism, this collection opens a multifaceted conversation on the kinds of futures we want to see, and presents concrete steps on how we can start realizing good data in practice.
Algorithms are now widely employed to make decisions that have increasingly far-reaching impacts on individuals and society as a whole (“algorithmic governance”), which could potentially lead to manipulation, biases, censorship, social discrimination, violations of privacy, property rights, and more. This has sparked a global debate on how to regulate AI and robotics (“governance of algorithms”). This book discusses both of these key aspects: the impact of algorithms, and the possibilities for future regulation.
»Digital Culture & Society« is a refereed, international journal, fostering discussion about the ways in which digital technologies, platforms and applications reconfigure daily lives and practices. It offers a forum for critical analysis and inquiries into digital media theory and provides a publication environment for interdisciplinary research approaches, contemporary theory developments and methodological innovation. The third issue »Politics of Big Data« edited by Mark Coté, Paolo Gerbaudo, and Jennifer Pybus, critically examines the political and economic dimensions of Big Data and thus details its contestation. The contributions focus on the materialities and processes which manifest Big Data and explore forms of value beyond the state and capital. These range from open data initiatives, social media metrics, machine learning algorithms, data visualisation to data dashboards, critical data analysis, and new modes of data action research and practice.
