This book constitutes the thoroughly refereed post-conference proceedings of the 5th International Conference on Security, Privacy and Trust in a Digital World, e-Democracy 2013, held in Athens, Greece, December 2013. The 20 revised full papers presented were carefully selected from numerous submissions. The papers are organized in topical sections on security, privacy; e-governance; e-government applications, virtualizations; politics, legislation: European initiatives.
The evolution of modern technology has allowed digital democracy and e-governance to transform traditional ideas on political dialogue and accountability. Digital Democracy and the Impact of Technology on Governance and Politics: New Globalized Practices brings together a detailed examination of the new ideas on electronic citizenship, electronic democracy, e-governance, and digital legitimacy. By combining theory with the study of law and of matters of public policy, this book is essential for both academic and legal scholars, researchers, and practitioners.
This book constitutes the refereed proceedings of the 7th International Conference on E-Democracy, E-Democracy 2017, held in Athens, Greece, in December 2017. The 18 revised full papers presented were carefully selected from 44 submissions. The papers are organized in topical sections on e-democracy; privacy; information dissemination and freedom of expression; social networks; electronic identity authentication; ICT in government and in the economy.
Daniel Solove presents a startling revelation of how digital dossiers are created, usually without the knowledge of the subject, & argues that we must rethink our understanding of what privacy is & what it means in the digital age before addressing the need to reform the laws that regulate it.
From one of the leading intellectuals of the digital age, The Digital Republic is the definitive guide to the great political question of our time: how can freedom and democracy survive in a world of powerful digital technologies? A Financial Times “Book to Read” in 2022 Not long ago, the tech industry was widely admired, and the internet was regarded as a tonic for freedom and democracy. Not anymore. Every day, the headlines blaze with reports of racist algorithms, data leaks, and social media platforms festering with falsehood and hate. In The Digital Republic, acclaimed author Jamie Susskind argues that these problems are not the fault of a few bad apples at the top of the industry. They are the result of our failure to govern technology properly. The Digital Republic charts a new course. It offers a plan for the digital age: new legal standards, new public bodies and institutions, new duties on platforms, new rights and regulators, new codes of conduct for people in the tech industry. Inspired by the great political essays of the past, and steeped in the traditions of republican thought, it offers a vision of a different type of society: a digital republic in which human and technological flourishing go hand in hand.
This book gives insight into the ongoing work of the forum on Philosophy, Engineering and Technology (fPET), which brings together philosophers and engineers from all over the world to discuss philosophical issues of engineering across disciplinary boundaries. Drawing on presentations and conversations at the fPET 2020 online conference hosted by the Universidad Técnica Federico Santa María in Chile, the chapters establish connections and describe discoveries that have so far been neglected in the discussions held within the young discipline of philosophy of engineering. This volume appeals to students and researchers in the field, through twenty-four proposals brought forward by leading scholars and emerging voices. Pertinent themes covered are: the broader engagement of engineers in problem-solving beyond the scope of their own profession the exploration of new goals for technology development and the implementation of strategies to reach these goals the need for philosophical content and unique pedagogical approaches to engineering education, digital transformations, artificial intelligence and the ethics of online collaboration in social media critical revisions of fundamental terminology and theoretical modelling of key concepts in engineering design, ethics, innovation and the anthropology of technology
The increased use of digital politics by citizens, groups, and governments over the last 25 years carried the promise of transforming the way politics and government was practiced. This book looks at Canadian political practice and the reality of the political process against those early promises.
This book analyses the legal approach to personal data taken by different fields of law. An increasing number of business models in the digital economy rely on personal data as a key input. In exchange for sharing their data, online users benefit from personalized and innovative services. But companies’ collection and use of personal data raise questions about privacy and fundamental rights. Moreover, given the substantial commercial and strategic value of personal data, their accumulation, control and use may raise competition concerns and negatively affect consumers. To establish a legal framework that ensures an adequate level of protection of personal data while at the same time providing an open and level playing field for businesses to develop innovative data-based services is a challenging task.With this objective in mind and against the background of the uniform rules set by the EU General Data Protection Regulation, the contributions to this book examine the significance and legal treatment of personal data in competition law, consumer protection law, general civil law and intellectual property law. Instead of providing an isolated analysis of the different areas of law, the book focuses on both synergies and tensions between the different legal fields, exploring potential ways to develop an integrated legal approach to personal data.
Effective spatial analysis is an essential element of archaeological research; this book is a unique guide to choosing the appropriate technique, applying it correctly and understanding its implications both theoretically and practically. Focusing upon the key techniques used in archaeological spatial analysis, this book provides the authoritative, yet accessible, methodological guide to the subject which has thus far been missing from the corpus. Each chapter tackles a specific technique or application area and follows a clear and coherent structure. First is a richly referenced introduction to the particular technique, followed by a detailed description of the methodology, then an archaeological case study to illustrate the application of the technique, and conclusions that point to the implications and potential of the technique within archaeology. The book is designed to function as the main textbook for archaeological spatial analysis courses at undergraduate and post-graduate level, while its user-friendly structure makes it also suitable for self-learning by archaeology students as well as researchers and professionals.
Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and biologically-inspired techniques. Mariette Awad and Rahul Khanna’s synthetic approach weaves together the theoretical exposition, design principles, and practical applications of efficient machine learning. Their experiential emphasis, expressed in their close analysis of sample algorithms throughout the book, aims to equip engineers, students of engineering, and system designers to design and create new and more efficient machine learning systems. Readers of Efficient Learning Machines will learn how to recognize and analyze the problems that machine learning technology can solve for them, how to implement and deploy standard solutions to sample problems, and how to design new systems and solutions. Advances in computing performance, storage, memory, unstructured information retrieval, and cloud computing have coevolved with a new generation of machine learning paradigms and big data analytics, which the authors present in the conceptual context of their traditional precursors. Awad and Khanna explore current developments in the deep learning techniques of deep neural networks, hierarchical temporal memory, and cortical algorithms. Nature suggests sophisticated learning techniques that deploy simple rules to generate highly intelligent and organized behaviors with adaptive, evolutionary, and distributed properties. The authors examine the most popular biologically-inspired algorithms, together with a sample application to distributed datacenter management. They also discuss machine learning techniques for addressing problems of multi-objective optimization in which solutions in real-world systems are constrained and evaluated based on how well they perform with respect to multiple objectives in aggregate. Two chapters on support vector machines and their extensions focus on recent improvements to the classification and regression techniques at the core of machine learning.
