The most fascinating and profitable subject of predictive algorithms is the human actor. Analysing big data through learning algorithms to predict and pre-empt individual decisions gives a powerful tool to corporations, political parties and the state. Algorithmic analysis of digital footprints, as an omnipresent form of surveillance, has already been used in diverse contexts: behavioural advertising, personalised pricing, political micro-targeting, precision medicine, and predictive policing and prison sentencing. This volume brings together experts to offer philosophical, sociological, and legal perspectives on these personalised data practices. It explores common themes such as choice, personal autonomy, equality, privacy, and corporate and governmental efficiency against the normative frameworks of the market, democracy and the rule of law. By offering these insights, this collection on data-driven personalisation seeks to stimulate an interdisciplinary debate on one of the most pervasive, transformative, and insidious socio-technical developments of our time.
The world is at a crossroads because of industrial change, compounded by a global pandemic. Humanities and social science education is grappling with the meaning of this change, to the effect that there have been some anxieties and misguided perceptions about the irrelevance of the humanities in this emerging new world. With the emergence of new technologies, this book highlights the indispensable centrality of humanity and the humanities going forward. The book will provide a reference point for new and innovative approaches to the humanities in the 4IR in South Africa and Africa. Its diverse content means that it will be useful across the humanities and social science spectrum.
AI appears to disrupt key private law doctrines, and threatens to undermine some of the principal rights protected by private law. The social changes prompted by AI may also generate significant new challenges for private law. It is thus likely that AI will lead to new developments in private law. This Cambridge Handbook is the first dedicated treatment of the interface between AI and private law, and the challenges that AI poses for private law. This Handbook brings together a global team of private law experts and computer scientists to deal with this problem, and to examine the interface between private law and AI, which includes issues such as whether existing private law can address the challenges of AI and whether and how private law needs to be reformed to reduce the risks of AI while retaining its benefits.
This revised and expanded edition of the Research Handbook on International Law and Cyberspace brings together leading scholars and practitioners to examine how international legal rules, concepts and principles apply to cyberspace and the activities occurring within it. In doing so, contributors highlight the difficulties in applying international law to cyberspace, assess the regulatory efficacy of these rules and, where necessary, suggest adjustments and revisions.
This book constitutes papers from the workshops held at the 18th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2019, which took place in Trondheim, Norway, in September 2019. The 11 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 33 submissions to the following workshops: DTIS: Digital Transformation for an Inclusive Society TPSIE: Trust and Privacy Aspects of Smart Information Environments 3(IT): Innovative Teaching of Introductory Topics in Information Technology CROPS: CROwd-Powered e-Services
The Elgar Encyclopedia of Technology and Politics is a landmark resource that offers a comprehensive overview of the ways in which technological development is reshaping politics. Providing an unparalleled starting point for research, it addresses all the major contemporary aspects of the field, comprising entries written by over 90 scholars from 33 different countries on 5 continents.
This open access book focuses on the impact of Artificial Intelligence (AI) on individuals and society from a legal perspective, providing a comprehensive risk-based methodological framework to address it. Building on the limitations of data protection in dealing with the challenges of AI, the author proposes an integrated approach to risk assessment that focuses on human rights and encompasses contextual social and ethical values. The core of the analysis concerns the assessment methodology and the role of experts in steering the design of AI products and services by business and public bodies in the direction of human rights and societal values. Taking into account the ongoing debate on AI regulation, the proposed assessment model also bridges the gap between risk-based provisions and their real-world implementation. The central focus of the book on human rights and societal values in AI and the proposed solutions will make it of interest to legal scholars, AI developers and providers, policy makers and regulators. Alessandro Mantelero is Associate Professor of Private Law and Law & Technology in the Department of Management and Production Engineering at the Politecnico di Torino in Turin, Italy.
For increasingly data-savvy clients, lawyers can no longer give "it depends" answers rooted in anecdata. Clients insist that their lawyers justify their reasoning, and with more than a limited set of war stories. The considered judgment of an experienced lawyer is unquestionably valuable. However, on balance, clients would rather have the considered judgment of an experienced lawyer informed by the most relevant information required to answer their questions. Data-Driven Law: Data Analytics and the New Legal Services helps legal professionals meet the challenges posed by a data-driven approach to delivering legal services. Its chapters are written by leading experts who cover such topics as: Mining legal data Computational law Uncovering bias through the use of Big Data Quantifying the quality of legal services Data mining and decision-making Contract analytics and contract standards In addition to providing clients with data-based insight, legal firms can track a matter with data from beginning to end, from the marketing spend through to the type of matter, hours spent, billed, and collected, including metrics on profitability and success. Firms can organize and collect documents after a matter and even automate them for reuse. Data on marketing related to a matter can be an amazing source of insight about which practice areas are most profitable. Data-driven decision-making requires firms to think differently about their workflow. Most firms warehouse their files, never to be seen again after the matter closes. Running a data-driven firm requires lawyers and their teams to treat information about the work as part of the service, and to collect, standardize, and analyze matter data from cradle to grave. More than anything, using data in a law practice requires a different mindset about the value of this information. This book helps legal professionals to develop this data-driven mindset.
In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.