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This book is a thorough and practical guide to minimizing personally identifiable information (PII) in every conceivable use case across Finance, Healthcare, Insurance, Legal, Marketing, HR, and Government. Most data protection laws and regulations require that businesses only use as much PII as is required for each specific processing purpose. In some cases, processing is only permitted when the data is fully anonymized. Hence, PII Minimization describes a spectrum from redacting very few, if any, direct identifiers to full anonymization. It is woefully unclear what exactly is required in terms of PII minimization. The feasibility and the degree of PII minimization crucially depend on what personal identifiers are present in the data set to be processed as well as the use case for processing it. Industry- and use-case-specific PII-Minimization Standards supplies expert insights from academia as well as the seven industries to be covered. These experts clarify what personal identifiers are commonly present in the data sets collected by or otherwise available to them, what use cases for data processing are prevalent in their industry, and which personal identifiers are (un)necessary for each use case. The book also features companies that are developing technological solutions to solve the difficult problem of data minimization. The practical insights to be gained here are how to achieve data minimization in specific use cases and with high accuracy to meet the regulatory requirements. As an example, for the development of facial recognition software, images of human faces must be used in machine-identifiable form. However, today’s technology can modify facial images for other use cases in such a way that they remain identifiable by human viewers but prevent the identification by automated systems. You Will:Explore the range of techniques for minimizing PII, from basic data reduction strategies to complete anonymization. Examine AI-specific regulations and their implications for data minimization, focusing on the most influential frameworks. Discuss the inherent challenges faced by general-purpose AI systems in implementing data minimization due to their extensive data needs and broad applications. Define key terms and concepts related to PII minimization technologies. Overview current and emerging technologies for minimizing PII in structured data, addressing their potential impacts and limitations. Explore methods and challenges in minimizing PII in unstructured data. Review data minimization in different industries and use cases. Who This Book is for:Data protection regulators as well as risk officers, privacy and data protection officers, product leaders, cybersecurity officers, information officers, and data leaders within organizations operating in Finance, Healthcare, Insurance, Legal, Marketing, HR, and Government that collect or process PII for purposes that require certain personal identifiers to be removed or obfuscated to meet data minimization requirements. The book is also for regulators developing actionable data minimization standards for these seven industries.
829 kr
I lager, skickas inom 4 till 5 vardagar
Peter Yaworski
Craig Smith
Justin Seitz, Tim Arnold
Alex Hidalgo
Tracy Fullerton
Alan Beaulieu
Jon Gjengset
Al Sweigart
Nicola Askham
Paul Kingsnorth
Janelle Shane
Martin Fowler
V. Anton Spraul
Ruha Benjamin
Mana Takahashi
Lee Vaughan
Cole Nussbaumer Knaflic
Alejandro Reyes
Bonaventura Di Bello
Paul Williams
John Whittington
Editorial Committee of the Madrid Code
Martin Durrell
Sarah Easter Collins
Frida Skybäck
Liz Moore
Colleen Hoover
Kristin Fägerskjöld
Armando Lucas Correa
Sharon Bolton
Ruth Lillegraven
Santa Montefiore
Kelly Rimmer
Martha Hall Kelly
Svenja O'Donnell
Nathan Harris
Holly Jackson
Louise Boije af Gennäs
Tina Norin
Kristin Fägerskjöld
Pernilla Lindroos
Anna Lönnqvist
Jessie Burton
Malin Nordström
Marc Levy
Emma Donoghue
Snezana Lindskog, Andie Lindskog
Tony Samuelsson
Andrev Walden
Tina Harnesk
Kathrine Nedrejord
Anthony Doerr
Marieke Lucas Rijneveld
Lauren Groff
Claire Messud
Claire Lynch
Sebastian Barry
Ray Celestin
Simon Stranger
Alice Munro
Linda Boström Knausgård
Marit Kapla
Ulf Stark
Sarah Easter Collins
Liz Moore
Ursula Scavenius
Colleen Hoover
Michel Jean
