Book contents
- Data-Driven Personalisation in Markets, Politics and Law
- Data-Driven Personalisation in Markets, Politics and Law
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Preface
- Part I Introduction: Theoretical Perspectives
- Part II Themes: Personal Autonomy, Market Choices and the Presumption of Innocence
- 5 Hidden Personal Insights and Entangled in the Algorithmic Model: The Limits of the GDPR in the Personalisation Context
- 6 Personalisation, Markets, and Contract: The Limits of Legal Incrementalism
- 7 ‘All Data Is Credit Data’: Personalised Consumer Credit Score and Anti-Discrimination Law
- 8 Sentencing Dangerous Offenders in the Era of Predictive Technologies: New Skin, Same Old Snake?
- Part III Applications: From Personalised Medicine and Pricing to Political Micro-Targeting
- Part IV The Future of Personalisation: Algorithmic Foretelling and Its Limits
- Index
5 - Hidden Personal Insights and Entangled in the Algorithmic Model: The Limits of the GDPR in the Personalisation Context
from Part II - Themes: Personal Autonomy, Market Choices and the Presumption of Innocence
Published online by Cambridge University Press: 09 July 2021
- Data-Driven Personalisation in Markets, Politics and Law
- Data-Driven Personalisation in Markets, Politics and Law
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Preface
- Part I Introduction: Theoretical Perspectives
- Part II Themes: Personal Autonomy, Market Choices and the Presumption of Innocence
- 5 Hidden Personal Insights and Entangled in the Algorithmic Model: The Limits of the GDPR in the Personalisation Context
- 6 Personalisation, Markets, and Contract: The Limits of Legal Incrementalism
- 7 ‘All Data Is Credit Data’: Personalised Consumer Credit Score and Anti-Discrimination Law
- 8 Sentencing Dangerous Offenders in the Era of Predictive Technologies: New Skin, Same Old Snake?
- Part III Applications: From Personalised Medicine and Pricing to Political Micro-Targeting
- Part IV The Future of Personalisation: Algorithmic Foretelling and Its Limits
- Index
Summary
In the European Union, regulatory analysis of artificial intelligence in general and personalisation more specifically often starts with data protection law, more specifically the General Data Protection Regulation (GDPR). This is unsurprising due to the fact that training data often contains personal data and that the output of these systems can also take the form of personal data. There are, however, limits to data protection’s ability to function as a general AI law. This chapter highlights the importance of being realistic about the GDPR’s opportunities and limitations in this respect. It examines the application of certain elements of the GDPR to data-driven personalisation and highlights that whereas the Regulation indeed applies to the processing of personal data, it would be erroneous to frame it as a general ‘AI law’ capable of addressing all normative concerns around personalisation.
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- Information
- Data-Driven Personalisation in Markets, Politics and Law , pp. 95 - 107Publisher: Cambridge University PressPrint publication year: 2021
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