Pseudonymised Data
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AI, Data and Private Law
Author: Gary Chan Kok Yew
language: en
Publisher: Bloomsbury Publishing
Release Date: 2021-09-23
This book examines the interconnections between artificial intelligence, data governance and private law rules with a comparative focus on selected jurisdictions in the Asia-Pacific region. The chapters discuss the myriad challenges of translating and adapting theory, doctrines and concepts to practice in the Asia-Pacific region given their differing circumstances, challenges and national interests. The contributors are legal experts from the UK, Israel, Korea, and Singapore with extensive academic and practical experience. The essays in this collection cover a wide range of topics, including data protection and governance, data trusts, information fiduciaries, medical AI, the regulation of autonomous vehicles, the use of blockchain technology in land administration, the regulation of digital assets and contract formation issues arising from AI applications. The book will be of interest to members of the judiciary, policy makers and academics who specialise in AI, data governance and/or private law or who work at the intersection of these three areas, as well as legal technologists and practising lawyers in the Asia-Pacific, the UK and the US.
Introduction to Data Protection Law
This textbook considers cases and materials introducing European Union (EU) data protection law to data protection enthusiasts while acting as a reference point for students and practitioners. The book's utility is twofold: the cases and materials can be used as a textbook as well as reference point for research. The book will benefit individuals new to this area and those at an intermediate level of familiarity with data protection law. It includes judgements delivered by the Court of Justice of the European Union (CJEU)/ European Court of Justice (ECJ) and decisions delivered by Data Protection Authorities (DPA) in the EU. While providing an overview of data protection law in the EU, the book introduces basic concepts of data protection law, principles of data protection law and rights and duties and remedies under the data protection law. Students would greatly benefit from the book by using it as an introduction to data protection law and as a reference point for research and assessments. Course instructors would benefit from the book by using it as core reading material.
Linking Sensitive Data
This book provides modern technical answers to the legal requirements of pseudonymisation as recommended by privacy legislation. It covers topics such as modern regulatory frameworks for sharing and linking sensitive information, concepts and algorithms for privacy-preserving record linkage and their computational aspects, practical considerations such as dealing with dirty and missing data, as well as privacy, risk, and performance assessment measures. Existing techniques for privacy-preserving record linkage are evaluated empirically and real-world application examples that scale to population sizes are described. The book also includes pointers to freely available software tools, benchmark data sets, and tools to generate synthetic data that can be used to test and evaluate linkage techniques. This book consists of fourteen chapters grouped into four parts, and two appendices. The first part introduces the reader to the topic of linking sensitive data, the second part covers methods and techniques to link such data, the third part discusses aspects of practical importance, and the fourth part provides an outlook of future challenges and open research problems relevant to linking sensitive databases. The appendices provide pointers and describe freely available, open-source software systems that allow the linkage of sensitive data, and provide further details about the evaluations presented. A companion Web site at https://dmm.anu.edu.au/lsdbook2020 provides additional material and Python programs used in the book. This book is mainly written for applied scientists, researchers, and advanced practitioners in governments, industry, and universities who are concerned with developing, implementing, and deploying systems and tools to share sensitive information in administrative, commercial, or medical databases. The Book describes how linkage methods work and how to evaluate their performance. It covers all the major concepts and methods and also discusses practical matters such as computational efficiency, which are critical if the methods are to be used in practice - and it does all this in a highly accessible way!David J. Hand, Imperial College, London