Discrimination And Privacy In The Information Society

Vast amounts of data are nowadays collected, stored and processed, in an effort to assist in making a variety of administrative and governmental decisions. These innovative steps considerably improve the speed, effectiveness and quality of decisions. Analyses are increasingly performed by data mining and profiling technologies that statistically and automatically determine patterns and trends. However, when such practices lead to unwanted or unjustified selections, they may result in unacceptable forms of discrimination. Processing vast amounts of data may lead to situations in which data controllers know many of the characteristics, behaviors and whereabouts of people. In some cases, analysts might know more about individuals than these individuals know about themselves. Judging people by their digital identities sheds a different light on our views of privacy and data protection. This book discusses discrimination and privacy issues related to data mining and profiling practices. It provides technological and regulatory solutions, to problems which arise in these innovative contexts. The book explains that common measures for mitigating privacy and discrimination, such as access controls and anonymity, fail to properly resolve privacy and discrimination concerns. Therefore, new solutions, focusing on technology design, transparency and accountability are called for and set forth.

This book on privacy and data protection offers readers conceptual analysis as well as thoughtful discussion of issues, practices, and solutions. It features results of the seventh annual International Conference on Computers, Privacy, and Data Protection, CPDP 2014, held in Brussels January 2014. The book first examines profiling, a persistent core issue of data protection and privacy. It covers the emergence of profiling technologies, on-line behavioral tracking, and the impact of profiling on fundamental rights and values. Next, the book looks at preventing privacy risks and harms through impact assessments. It contains discussions on the tools and methodologies for impact assessments as well as case studies. The book then goes on to cover the purported trade-off between privacy and security, ways to support privacy and data protection, and the controversial right to be forgotten, which offers individuals a means to oppose the often persistent digital memory of the web. Written during the process of the fundamental revision of the current EU data protection law by the Data Protection Package proposed by the European Commission, this interdisciplinary book presents both daring and prospective approaches. It will serve as an insightful resource for readers with an interest in privacy and data protection.

In the contemporary information society, organisations increasingly rely on the collection and analysis of large-scale data (popularly called ‘big data’) to make decisions. These processes, which take place largely beyond the individual’s knowledge, produce a cascade of effects that go beyond privacy and data protection. Should we focus on the possibilities of tackling these often negative effects through other areas of law, or maybe even find new solutions to cope with the dark side of big data? This ground-breaking book is the first to address this crucially important question in detail. Among the issues raised in the analysis are such vital elements as the following: − what is meant by ‘big data’; – ‘privacy’ according to the European Court of Human Rights and the Court of Justice of the European Union; – what the European Union legal framework on privacy and data protection consists of and how it functions in the light of big data; – what companies, governments and other organisations are permitted to do with big data under the current regulatory framework; – the central importance of personal autonomy; – circumstances that influence whether or not the right to privacy is triggered; – big data’s possible impact on democracy through, inter alia, potentially limiting freedom of expression; – how governmental or corporate surveillance chills the receiver’s gathering of information and ideas; – selective offering of choices or information, or manipulation of people’s ideas; – procedural aspects that influence the extrapolation of normative concepts of privacy and data protection; and – how discrimination occurs in big data. This book foregrounds a critical scrutiny of commercial uses of big data – its scale, its limited capacity for independent oversight and the expected prevalence of interference with individuals’ rights. The author’s conclusions explore possible legal alternatives to mitigate the negative impact of big data, using legal instruments, case law and legal academic literature in her analysis. Because the amount of digital data keeps growing and the private lives of individuals are increasingly taking place online – and because of the opacity of the big data process, the fundamental values that are at stake, and the speed of technological developments compared to the pace of legal reform – this comprehensive assessment of flaws in the current framework and possible practical solutions will be warmly welcomed by practitioners, policymakers and government officials in all legal fields related to privacy and data protection.

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.

Papers originally presented at the World Summit on the Information Society, November 2005.

The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.