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Data-Driven Personalisation in Markets, Politics and Law
About this book
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.
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Information
Table of contents
- Cover
- Half-title
- Title page
- Copyright information
- Contents
- List of Figures
- List of Tables
- List of Contributors
- Preface
- Part I Introduction: Theoretical Perspectives
- Part II Themes: Personal Autonomy, Market Choices and the Presumption of Innocence
- Part III Applications: From Personalised Medicine and Pricing to Political Micro-Targeting
- Part IV The Future of Personalisation: Algorithmic Foretelling and Its Limits
- Index