Data-Driven Personalisation in Markets, Politics and Law
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A termék adatai:
- Kiadó Cambridge University Press
- Megjelenés dátuma 2024. április 18.
- ISBN 9781108813082
- Kötéstípus Puhakötés
- Terjedelem332 oldal
- Méret 229x151x21 mm
- Súly 500 g
- Nyelv angol 723
Kategóriák
Rövid leírás:
This book critiques the use of algorithms to pre-empt personal choices in its profound effect on markets, democracy and the rule of law.
TöbbHosszú leírás:
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.
'Exploring the societal sea changes that emerge from the unleashed power of data-driven personalization, Uta Kohl and Jacob Eisler are gifting us a book that is the intellectual equivalent of a beautiful flower bouquet: a diverse and colorful, yet carefully chosen and elegantly arranged set of contributions from scholars representing different disciplines, perspectives, and temperaments, making it an insightful collection that is more than the sum of its individual parts.' Urs Gasser, Executive Director, Berkman Klein Center for Internet & Society and Professor of Practice, Harvard Law School
Tartalomjegyzék:
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 Mich&&&232;le 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 Daith&&&237; 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.
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