Data-Driven Personalisation in Markets, Politics and Law

This book critiques the use of algorithms to pre-empt personal choices in its profound effect on markets, democracy and the rule of law.

Uta Kohl (Edited by), Jacob Eisler (Edited by)

9781108835695, Cambridge University Press

Hardback, published 29 July 2021

300 pages
23.5 x 15.8 x 2.1 cm, 0.62 kg

'With vision and panache, Kohl and Eisler, and their contributing authors, identify the hidden perils of the 'personalisation' phenomenon and boldly ask whether its apparent benefits of a 'close personal fit' and efficiency can ever outweigh the damage done to individual agency and communal solidarity, or to our aspirations of equality. Invaluable insights for the policy and legal debates on the use of predictive algorithms in politics, markets and law, which are upon us.' Paul De Hert, Vrije Universiteit Brussels, Tilburg University

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.

Part I. Introduction: Theoretical Perspectives
1. The Pixelated Person – Humanity in the Grip of Algorithmic Personalisation Uta Kohl
2. Personalisation and Digital Modernity: Deconstructing the Myths of the Subjunctive World Kieron O'Hara
3. Personalisation, Power and the Datafied Subject Marc Welsh
4. Personal Data and Collective Value: Data-Driven Personalisation as Network Effect Nick O'Donovan
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 Michèle Finck
6. Personalisation, Markets, and Contract: The Limits of Legal Incrementalism T.T. Arvind
7. 'All Data is Credit Data' – Personalised Consumer Credit Score and Anti-Discrimination Law Noelia Collado-Rogriguez and Uta Kohl
8. Sentencing Dangerous Offenders in the Era of Predictive Technologies: New Skin, Same Old Snake? David Gurnham
Part III. Applications: From Personalised Medicine and Pricing to Political Micro-Targeting
9. 'P4 Medicine' and the Purview of Health Law: The Patient or the Public? Keith Syrett
10. Personalised Pricing: The Demise of the Fixed Price? Joost Poort and Frederik Zuiderveen Borgesius
11. Data-Driven Algorithms in Criminal Justice: Predictions as Self-Fulfilling Prophecies Pamela Ugwudike
12. From Global Village to Smart City: Reputation, Recognition, Personalisation, and Ubiquity Daithí Mac Sithigh
13. Micro-Targeting in Political Campaigns: Political Promise and Democratic Risk Normann Witzleb and Moira Paterson
Part IV. The Future of Personalisation: Algorithmic Foretelling and Its Limits
14. Regulating Algorithmic Assemblages: Looking Beyond Corporatist AI Ethics Andrew Charlesworth
15. Scepticism about Big Data's Predictive Power about Human Behaviour: Making a Case for Theory and Simplicity Konstantinos Katsikopoulos
16. Building Personalisation: Language and the Law Alun Gibbs
17. Conclusion: Balancing Data-Driven Personalisation and Law as Social Systems Jacob Eisler.

Subject Areas: Educational: IT & computing, ICT [YQTU], IT & Communications law [LNQ]