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Data-driven personalisation in markets, politics and law

Data-driven personalisation in markets, politics and law
Data-driven personalisation in markets, politics and law
The use of technology to gather data on personal behaviour, aggregate it into big data sets, analyse it through complex learning algorithms and finally use it to predict future individual decision-making is vastly influential, but frequently hidden. This interdisciplinary volume analyses the breadth of practices in which data-driven personalisation occurs – from behavioural advertising and personalised pricing to political micro-targeting, from precision medicine to predictive policing and sentencing - and offers a range of philosophical, sociological, legal and socio-legal critiques of this emerging highly pervasive phenomenon. Despite the different social contexts and disciplinary perspectives, emerging recurrent themes are: choice, personal autonomy and agency versus efficiency and control; individual interests versus collective goods and solidarity, and the power of law and regulation in restraining the practices. This volume seeks to stimulate an interdisciplinary debate on one of the most important socio-technical developments of the 21st century.
Algorithm, Big Data, predictive models, micro targeting, personalisation, machine learning algorithms, artificial intelligence, actuarial models, law and statistics, contestation
Cambridge University Press
Kohl, Uta
813ff335-441f-4027-801b-4e6fc48409c3
Eisler, Jacob
a290dee3-c42f-4ede-af9a-5ede55d0135a
Kohl, Uta
813ff335-441f-4027-801b-4e6fc48409c3
Eisler, Jacob
a290dee3-c42f-4ede-af9a-5ede55d0135a

Kohl, Uta and Eisler, Jacob (eds.) (2020) Data-driven personalisation in markets, politics and law , Cambridge University Press (In Press)

Record type: Book

Abstract

The use of technology to gather data on personal behaviour, aggregate it into big data sets, analyse it through complex learning algorithms and finally use it to predict future individual decision-making is vastly influential, but frequently hidden. This interdisciplinary volume analyses the breadth of practices in which data-driven personalisation occurs – from behavioural advertising and personalised pricing to political micro-targeting, from precision medicine to predictive policing and sentencing - and offers a range of philosophical, sociological, legal and socio-legal critiques of this emerging highly pervasive phenomenon. Despite the different social contexts and disciplinary perspectives, emerging recurrent themes are: choice, personal autonomy and agency versus efficiency and control; individual interests versus collective goods and solidarity, and the power of law and regulation in restraining the practices. This volume seeks to stimulate an interdisciplinary debate on one of the most important socio-technical developments of the 21st century.

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More information

Accepted/In Press date: 2020
Keywords: Algorithm, Big Data, predictive models, micro targeting, personalisation, machine learning algorithms, artificial intelligence, actuarial models, law and statistics, contestation

Identifiers

Local EPrints ID: 443582
URI: http://eprints.soton.ac.uk/id/eprint/443582
PURE UUID: d7b2ce83-1109-4f82-b01d-f08e1b93addc
ORCID for Uta Kohl: ORCID iD orcid.org/0000-0002-8616-9469
ORCID for Jacob Eisler: ORCID iD orcid.org/0000-0003-4422-5255

Catalogue record

Date deposited: 03 Sep 2020 01:47
Last modified: 18 Feb 2021 17:38

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Contributors

Editor: Uta Kohl ORCID iD
Editor: Jacob Eisler ORCID iD

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